#How to enable adblock extension in chrome windows 10

[techcoreglimp]

How To Enable Adblock Extension In Chrome

How To Enable Adblock Extension In Chrome

How to enable adblock extension in chrome, Hey there, tech-savvy friend! Are those pesky ads ruining your online adventures? Don't let them steal your thunder! Let me show you how to enable the Adblock extension in Chrome, so you can surf the web without any interruptions.

What is AdBlock extension?

Alright, before we dive in, let's get the basics straight. AdBlock extension is like your digital guardian angel. It's a free browser extension that swoops in and saves the day by blocking those annoying ads on websites. You can get it for Chrome, Firefox, Edge, and Opera, so it's got your back no matter your browser flavor. Plus, it's got a fan club of over 100 million users worldwide.

keep in touch : metech-arm.com

How does AdBlock extension work?

Now, how does this magic happen? AdBlock extension is a superhero with a variety of tricks up its digital sleeves. It scans web pages for known ad domains and vanquishes them, using methods like keyword matching, URL matching, and element blocking. It's like an ad-blocking ninja, always one step ahead!

Benefits of using AdBlock extension

Why should you care about this extension, you ask? Well, buckle up, because it can improve your online life in some pretty cool ways:

Block intrusive and annoying ads: AdBlock extension doesn't discriminate; it takes down pop-ups, video ads, banner ads – the whole squad of annoying ad formats!

Speed up your browsing speed: By making ads disappear, it lightens the load on your internet connection, letting you surf the web at warp speed.

Protect your privacy: AdBlock extension stands up against those ad trackers that sneakily gather your data without your permission. Your browsing habits are your business!

How to install AdBlock extension in Chrome

Enough chit-chat! Let's get AdBlock extension in Chrome:

Go to the Chrome Web Store.

In the search bar, type "AdBlock extension."

Find the "Add to Chrome" button and give it a good old click.

Confirm by clicking "Add extension."

How to enable AdBlock extension in Chrome

Alright, you've got it installed, but how do you turn it on? Easy peasy:

See that AdBlock extension icon in the Chrome toolbar? Give it a click.

Look for the toggle switch and flip it on.

How to manage AdBlock extension settings in Chrome

Let's say you want to customize AdBlock extension's behavior. No problem! Here's how to do it:

Click that trusty AdBlock extension icon in the Chrome toolbar.

Seek out the "Options" button and click it.

Ta-da! You've opened the AdBlock extension settings page, and you can tweak things to your heart's content.

Troubleshoot common AdBlock extension problems

Sometimes, even the best of us run into problems. If you're having issues with AdBlock extension, try these fixes:

Restart your Chrome browser.

Disable all other browser extensions – sometimes they clash.

Clear your Chrome browser's cache and cookies for a fresh start.

Make sure your AdBlock extension is up to date by installing the latest version.

But, if all else fails, you can always reach out to the friendly folks at AdBlock support for a helping hand.

How to block specific ads in Chrome

Let's talk about precision. If there's a specific ad bugging you, there are two ways to target it:

Using the Chrome developer tools:

Open Chrome and go to the website with the bothersome ad.

Right-click on the ad and select "Inspect" – you're diving into the developer tools.

In the developer tools, click on the "Elements" tab.

Find the ad's HTML code and right-click on it.

Choose "Block element."

Using an ad blocker extension:

There are plenty of ad blocker extensions out there. Once you have one installed, open its settings, and add the website to the whitelist.

How to whitelist specific websites in Chrome

Maybe you love a website and want to support it by letting their ads through. Here's how:

Go to the site you want to whitelist in Chrome.

Click the lock icon in the address bar.

Hit "Site settings."

Under "Ads," turn off the "Block ads on this site" toggle switch.

How to use AdBlock extension to protect your privacy

Privacy matters! AdBlock extension can be your trusty ally in this department. Here's how to use it to shield your online life:

Open the AdBlock extension settings.

Click on the "Privacy" tab.

Make sure that the "Block ad trackers" option is enabled – no sneaky trackers allowed!

How to troubleshoot common AdBlock extension problems (again!)

In case you missed it the first time:

Restart your Chrome browser.

Disable other browser extensions if they're causing issues.

Clear your Chrome browser's cache and cookies.

Keep AdBlock extension up to date.

Still stuck? Head over to AdBlock support – they've got your back!

Additional tips for blocking specific ads in Chrome

Sometimes, you need a more surgical approach. If you can't block a specific ad, try creating a custom filter. Custom filters are like secret weapons to vanquish your foes – in this case, pesky ads.

Ready to take control of your browsing experience? Get that AdBlock extension in gear and surf the web in style!

FAQ: How to enable AdBlock extension in Chrome

Image: A yellow sign that says "how to en"

Answer:

To enable AdBlock extension in Chrome, follow these steps:

Go to the Chrome Web Store and search for "AdBlock extension".

Click the Add to Chrome button.

Click the Add extension button to confirm.

Click the AdBlock extension icon in the Chrome toolbar.

Click the toggle switch to turn on AdBlock extension.

Additional information:

AdBlock extension is a free browser extension that blocks ads from appearing on web pages.

AdBlock extension is available for Chrome, Firefox, Edge, and Opera browsers.

AdBlock extension is one of the most popular browser extensions in the world, with over 100 million active users.

Troubleshooting:

If you are having problems enabling AdBlock extension in Chrome, try the following:

Restart your Chrome browser.

Disable all other browser extensions.

Clear your Chrome browser's cache and cookies.

Update AdBlock extension to the latest version.

If you are still having problems, you can visit the AdBlock support website for more help.

[miniaturestarlightsandwich]

Download Ad Blocker For Mac Free

Written by Eyeo GmbH

Free Ad Blocker Windows 7

Ad Blocker For Mac Safari Free Download

Best Free Ad Blocker Mac

Ad Blocker For Macbook Air

Best Free Ad Blocker

Category: Productivity

Release date: 2019-11-27

Licence: Free

Software version: 2.1.0

File size: 19.24 MB

Compatibility: Windows 10/8.1/8/7/Vista and Mac OS X 10.12.6

Adblock Plus for Safari for PC and Mac Screenshots

Adblock for Mac, free and safe download. Adblock latest version: Block ads in Google Chrome. UBlock, the fastest, most powerful ad blocker for Mac is here. UBlock blocks all annoying pop-ups and ads while you browse on your Mac. It’s simple, easy-to-install, and best of all- completely free. Download uBlock ad blocker for Mac and browse faster today.

Key Features

Latest Version: 2.1.0

Licence: Free

Rated 3/5 By 740 People

What does Adblock Plus for Safari do? Adblock Plus for Safari is a totally free ad blocker that allows you to block annoying ads on your favorite websites and video channels. Simply install the app, and see the web in a better way. No more pop-ups, banners or autoplay ads. The Adblock Plus app for Mac supports great websites with Acceptable Ads (on by default). Don’t want to see any ads? Simply deactivate Acceptable Ads. You can also have the option to whitelist websites you trust.By downloading and installing the application, you agree to our Terms of Use. https://adblockplus.org/terms

Download for MacOS - server 1 --> Free

Download and Install Adblock Plus for Safari

Download for PC - server 1 --> MAC:

Download for MacOS - server 1 --> Free Thank you for visiting our site. Have a nice day!

PC Compactibility/Requirements for Installation

Compactible OS list:

Windows 10

Windows 8.1

Windows 7

Windows Vista

Free Ad Blocker Windows 7

Requirements for MacOS Installation

Ad Blocker For Mac Safari Free Download

Intel, 64-bit processor, OS X 10.7 or later.

Compactible OS list:

OS X 10.10: Yosemite

OS X 10.11: El Capitan

macOS 10.12: Sierra

macOS 10.13: High Sierra

macOS 10.14: Mojave8

macOS 10.15: Catalina

Adblock Plus for Safari - how do I download the app on PC?

If you want to download the software on your pc or mac, you could either first visit the Mac store or Windows AppStore and search for the app OR you can easily use any of the download links we provided above under the 'Download and Install' header section to download the application

Adblock Plus for Safari - Is it safe to download?

Yes. The app is 100 percent (100%) safe to download and Install. Our download links are from safe sources and are frequently virus scanned to protect you

By Glendale2x

New framework seems to have performance issues

This version of ABP for the new Safari framework unfortuantely seems to kill performance on my computers. Maybe it’s partially related to them being a bit older (one is a Mid 2011 Mini, the other is a 2012 iMac), but with ABP enabled I can’t even open a new tab/window and type a URL into the bar and expect Safari to accept the input without having to hold down the return key until it goes or wait a minute after opening a new tab or window. I also noticed that using Twitter was jumpy and lagged even with simple typing, it felt like all the dynamic content it relies on was just struggling to be processed through whatever framework Apple is forcing. Hopefully the devloper can figure out the performance issues because it’s really, really bad now.

By Ramblin'Rose

why isn’t this working?

I have ABP and it wasn’t perfect but worked fairly well for my needs. Recently, it simply disappeared. (I see someone else said that could be from the latest iOS update, but I don’t have that on my desktop yet). When I tried to reinstall, it showed me two boxes to check. The way I read it, if you checked the box that said you wanted the icon visible in the toolbar, it would be able to read sensitive information of all kinds on any page. What good is an app of any kind that allows for that?! As it was, with only the one box checked, it only blocked very few ads, and I was still getting requests from sites to be whitelisted without being able to fnd any way to do it. I’ve got all kinds of garage showing up on my Facebook page, and you guys have ruined what was a reasonable product. WHY?

By PeopleRsad

Still works for me

Almost didn’t download the new version based on the recent reviews, however after looking at the other apps here that claim to be ad blockers I didn’t’t see too many alternatives. I decided to go ahead and get the new version and so far its pretty much the same as the old version, lots of ads blocked. I’m happy, just make sure you go through the simple set-up.

By achilds19

Works well but

After much research, I understand the issue with Apple changing the rules on the devs so they had to build this app from scratch. Works well for me so far, except for one annoying problem. I use Yahoo mail and it's not hiding the ad that appears in the top line of the inbox even with unchecking the Acceptable Ads box, which is super annoying. I know the devs are watching these reviews, so if someone can point me to an extension or something that will fix that, I'd appreciate it. Was using AdGuard and it fixed that problem, but that app behaves like spyware and is constantly running in the background even after you close Safari.

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[bangsterlicious]

SIGNAL BOOST

SUPPORT YONGGUK’S SOLO ALBUM

BABYz, it’s almost time and Yongguk’s first solo album will be released! I for one am super excited as it’s literally a dream come true for me personally! Are you as excited as I am? Only 5 more days to go!!

I am sure Yongguk will upload the MV to “Hikikomori” to his Youtube channel (or possibly to Consentmedia’s if they already have one) – and this is where we (you & me!) come in!

We all know that sadly our fandom (BABYz/B.A.P’s) is not as big as it used to be…so there is not all that much attention on what the guys are doing. Which means we will have to work hard to get them the recognition they deserve!

Yongguk’s doing his best to establish his solo career here (any maybe lay groundwork for when B.A.P comes back?!) so let’s support him as best we can!

THE IMPORTANCE OF YOUTUBE VIEWS

YouTube views are extremely important. As we know, Korean music shows count them to decide weekly winners. The views will determine how popular the group/artist is internationally and are converted to points together with SNS popularity. The artist also gets paid depending on the number of views/clicks – and we all know that Yongguk probably paid for the production of his album all by himself, so he depends on the success of it! More views also mean the video will get featured more often on the start page and/or next to relevant/related videos which will increase his popularity & thus the chance of more views and maybe even new fans!

OUR GOAL

2 Million in 24 hours

Every view counts! Now, how do we increase the views successfully?

Sadly, Youtube has caught on to how we increased views in the past, so simply having the video on loop (and possible muted) won’t work anymore. Here are the steps / different methods to make our views count:

Computor/Laptop

1. Please use a browser that uses addons/extensions (Chrome, Firefox etc)

2. Download extensions for Auto Reload (or Auto Refresh), Auto HD and Adblock and enable them

3. For Auto HD, the quality should be 720p or more to guarantee a view, as for Auto Reload, set it to 5 min (Or 4 min 30 sec if you have a fast internet)

4. Disable Autoplay on youtube and play the MV

5. Make sure to delete your cookies and history before rewatching to increase views!

6. Use a VPN to hide your ip address so that your ip isn't marked as spam!

Android/iPhone

1.    Open youtube and play the Music Video.

2.    After it ends, close the video and go to settings.

3.    From settings, go to the privacy section and delete your watch history.

4.    Rewatch the mv and repeat step 1-2

Creating a playlist

1. If you want to create a Playlist, create one with the official MV and his official performances (at least 3 videos) from your YouTube account. MAKE SURE YOU SET THE PLAYLIST IN PUBLIC.

- Get the link and log out from your account.

- Open an incognito tab and load your Playlist.

- Set the Playlist on autoplay.

REMEMBER TO CLEAR HISTORY AND DELETE COOKIES EVERY ONCE IN AWHILE

 2. Loop a Playlist on incognito in one window, use auto refresh on another window and occasionally watch the MV after another video on the third window.

 3. Use as many streaming devices as you can - Computer, ipad/tablets, phone and use the Playlist method.

IMPORTANT ADVICE FOR STREAMING

1. Don’t stream in incognito mode (if it’s not a playlist!) as that wouldn’t increase views and would be counted as spam!

2. Don’t stream the video by putting it on loop (for browsers) as it will not increase views! Loop will work if you have it on a playlist!!

3. Don’t pause or increase/decrease the speed of the music video! You need to be logged in as well!

4. If you’re not using an adblock watch out for ads because they make sure your view is being counted!

5. Some browsers do need to be logged out and in to stream but I haven’t had a problem streaming the way I mentioned!

6. You can always try the “easy” version by logging out, deleting history and logging back in to stream!

7. The volume has to be at 50% or higher. If you intended to just have it play in the background, mute your pc/speakers, not youtube itself or use headphones (you don`t actually have to wear them 😉 ).

8. Watch at least 2-3 videos before rewatching “Hikikomori” as there has to be a gap for the views to be counted, otherwise it will be counted as spam and deleted. You could always watch one of Yongguk’s other MVs such as “Yamazaki” or “Drunkenness” to support him further!

9. YouTube is trying to get rid of low-quality playback, they analyze a collection of views to distinguish those that are real compared to those that are 'robot-like'. So with that in mind, show YouTube that you are human, stream in high-quality.

10. Remember to clear your cookies every 9 – 15 views or else Youtube will probably catch on to what you’re doing!

11. Like, comment & share the MV: Share the link on all your social media accounts (Twitter, fb, Tumblr, etc.), clicks from shared links will count as views. Ask all your friends!!! THE MORE VIEWS AND COMMENTS AN MV HAS, THE MORE IT IS SUGGESTED ON EVERY OTHER KPOP MVS.

That’s it! I know it sounds like a lot of work but I promise it isn`t as difficult as it sounds at first. 😊

Please keep in mind that Yongguk is working very hard to bring something awesome to us again and that he tends to work too much and too long because he wants it to be perfect for us. Show him how much we appreciate and love him for it! Please also remember the topic of “Hikikomori”. Yongguk is putting himself out there to address the issue and it seriously hits close to home. Not only for himself but to many of us I imagine. That takes a lot of courage and bravery, so please show him how much we respect him for it!

There are also a number of other fan projects out there, check them out and participate if possible!

Links to other projects: Twitter & Tumblr

Disclaimer: The explanations are not mine, credit to the awesome people who wrote them! ♥

[listinghunter252]

Youtube Video Downloader Mp3

VidPaw for Mac is a versatile solution to help you convert YouTube videos to MP3, MP4 at the same place. You can choose the output format based on you need.

Our HD Mp3 converter is a smart online YouTube to Mp3 converter that allows users to convert their favorite YouTube videos into Mp3 format (mp3 file). It provides fast conversion and high quality for every file. You will only have to do 2 steps before you get your converted output file.

Video Downloader Pro for Edge lets you download multiple versions in HD and SD from many popular video websites. ✓ Video Downloader Pro detects enables you to dowload multiple formats. ✓ Convert video to MP3 with buildin video to mp3 converter. ✓ Supports MP4, MOV, AVI, ASF, MPG, MP3 and many more. ✓ Easy, fast, safe light! ✓ Compatible with Adblock, AdBlock Pus, uBlock Origin and Adblocker for Youtube extension.

Are you looking for an excellent YouTube to mp3 converter to convert YouTube videos or playlists to mp3 to listen to your favorite music or courses offline? Then you have come to the right place! In this article, we will share with you 12 of the best YouTube to mp3 converters on the market, you can select from any one of them to do your job. Without further ado, let’s check out the full list below!

Have you ever tried to convert a youtube video to mp3? With the help of Ytmp3 Converter Online, it is no big deal.you can convert and easily download youtube videos into mp3 and mp4 formats. The conversion process hardly takes 2 minutes. Downloading youtube to mp4, youtube to mp3, or mp3 to wav has never been easier before Ytmp3 Converter.

1. 4K YouTube to MP3 Converter

Jihosoft 4K Video Downloader is a powerful YouTube video downloader and converter. Using it, you can not only download YouTube videos but also batch convert YouTube videos to MP3/M4A format. In addition to YouTube, it also allows you to download music from SoundCloud. Here is how to use it:

Step 1. Download and install the YouTube to mp3 converter on your computer then run it.

Step 2. Go to YouTube, find the video or playlist you want to convert to mp3, then copy its link address.

Step 3. Open the software, paste the URL into the program, and select “Convert to MP3” from the pop-up box.

Step 4. Click the Download button, the software will automatically convert YouTube videos to mp3.

More wonderful features of Jihosoft 4K Video Downloader:

Download 4K & 8K UHD, 360°, VR, 3D, 60FPS videos

Download the entire YouTube channel or playlist

Save videos from Facebook, Twitter, Instagram, Vimeo, etc

Convert local videos to MP4, MOV, MKV, AVI, etc

Download Twitch clips and highlights

2. YtMP3 (YouTube to MP3)

YtMP3 is a free online YouTube to mp3 converter. By using this tool, you can easily convert YouTube videos to mp3 or mp4 files and download them to your computers, tablets, or mobile devices. The best part is that the YouTube to mp3 converter does not require any software or even registration. To convert YouTube videos to mp3, all you need to do is enter the URL into the required box, choose a format, and then tap the convert button. The conversion process merely takes a few minutes. However, there is a bit of attention here, you must ensure that the video you’re ready to convert is not more than 1 hour.

3. Y2Mate (YouTube to MP3/MP4)

The most popular YouTube to MP3 and YouTube to MP4 converter on the internet, Y2mate allows you to download YouTube videos online and save them in various formats like MP3, M4V, 3GP, WMV, FLV, MOV, WEBM, etc. It is compatible with all browsers, thus you can access the website on any device, whether you own a PC or a tablet. An additional feature is that it lets you upload the converted files to your DropBox and Google Drive, which is not provided by most services.

4. Flvto (YouTube to MP3/MP4)

One of the best YouTube to mp3 converters in our list, Flvto is an online website dedicated to providing high-quality conversion services. With this converter, you can convert YouTube videos to MP3, AVI, MOV, MP4, WMV, and any other format you like with just a few clicks. It is fast, safe and easy to use. You can use it online or install it on Windows, Mac and Linux devices absolutely free of cost. Apart from YouTube, it also supports many other video-hosting sites, including TikTok, Instagram, Facebook, Vimeo, Dailymotion, Metacafe, etc.

5. MP3Converter.to

Similar to Y2MP3, MP3Converter.to is another leading YouTube to MP3 converter online. With the help of this tool, you can download and convert YouTube videos to MP3 or MP4 format in seconds. To get started with MP3Converter.to, there is no software download or registration needed, simply paste the YouTube video URL into the box and select the output format, then click the “Convert” button, it will save the audio or video file to your device in a few minutes.

6. Online Video to MP3 Converter

Online video converter is a great web tool. Using it, you can convert online video or local video to MP3, WMV, M4A, MP4, AVI, MPEG, MOV, FLV, 3GP, and almost all mainstream audio/video formats. Unlike other YouTube to mp3 converters, this site has no limit on the number of files that can be converted. After conversion, your files will be automatically deleted from their servers after a few hours, and no one can access them except you. In addition, all its functions are accessible free of charge, so you don’t have to pay anything to use it. The only limitation is that you can only upload files up to 2GB.

Youtube To Mp3 Download Converter

7. 2Conv.com (YouTube to MP3)

Compared to most online YouTube to mp3 converters, 2Conv is faster and more reliable. The site does not come with malware attached to downloads. There is no registration process required, and you are done with an easy conversion in a couple of clicks. The best part is that the service is available in languages such as Spanish, Portuguese, and Turkish for a more user-friendly experience!

8. ClipConverter (YouTube to MP3)

Clip Converter is a browser-based tool that provides multiple conversion services and supports a lot of video and audio formats. You can use it on any device, whether it’s Mac, Windows, Linux, Android or iPhone. Its interface is very simple and intuitive, thus does not require any additional operations! To convert YouTube videos to mp3, just paste the video URL into the box, choose the desired format, and click “Convert”, then you will get a result immediately.

9. 4K Video Converter

Convert YouTube videos to MP3 files quickly. 4K Video Converter allows the conversion of 4k video to MP3 for audio extraction and works on both Windows and Mac operating systems. There is no risk of malware; the software has been scanned by 52 leading antiviruses.

All you need to do is to drag and drop links to your favorite tracks and get the converted MP3 files to your computer. The software is user-friendly, and you can transfer songs directly to your iPod, iPhone, and iPad on the go. If you love the idea of audiobooks, download them hassle-free and listen to them offline while lounging.

With its easy proxy setup, you can change your IP address from the settings and have access to downloadable videos that are otherwise banned in your region!

10. YTD YouTube to MP3 Converter

Download unlimited videos and playlists from YouTube, Facebook, and various other popular sites with the basic version of YTD free of cost. You can easily convert videos to your iPhone or iPad in MP4, WMV, AVI, and MP3 format. It supports multiple video downloads at a fast speed of 4x and has an automatic resume/retry feature, which helps to resume the download when the internet connection fails.

There is an advanced panel that monitors recent and past activity. Unlike other YouTube to MP3 software, YTD provides an ad-free experience with no install offers. Moreover, the software offers free email support in case of bugs or downloading errors.

11. Freemake YouTube to MP3 Converter

Looking for something truly free? Music lovers will certainly rejoice by knowing that Freemake has been recognized as one of the best YouTube converters for seven years with a user base of about 80 million till date. It is so user-friendly that allows you to copy and paste YouTube links or type the name of song artists and it will find & convert the music.

Its multithread technology is ground-breaking and fast. With a perfect size of 320 kbps MP3s, it automatically detects high-quality videos. As there is no video to audio re-encoding, there is no chance of loss of sound quality.

The other unique features of this free YouTube to MP3 converter include download history, preview before conversion, and direct play of the music in the software right after download.

It is super-reliable, offering 24/7 support, making it one of our favorites.

12. Apowersoft Video to MP3 Converter

Apowersoft Limited is a Hong Kong-based company with a vision to provide accessible digital media solutions. The software has a smooth conversion process to convert videos to MP3 by a direct search from YouTube or local browsing from a destination folder 100% free with no trial limitations or gimmicks.

Apowersoft is compatible with various web-browsers like Google Chrome, Safari, Firefox, Opera amongst others on both Windows and Mac OS. You can also convert videos or streams from Dailymotion, Vimeo, Ustream to MP3, AVI, MOV, and MP4 format.

More, you can choose the file size as per your choice. You can convert multiples files simultaneously within a few minutes, which is useful in case you need to convert a batch of files.

Which is the best YouTube to mp3 converter?

Above are the 12 best YouTube to mp3 converters we have collected. Which one do you like best? Choose one of them and start your work!

Related Articles

New Articles

At times, while browsing, you'll come across the perfect YouTube video to use for your own content. “If only there was a way to download it without asking the owner” – you mutter. The good news is, there are certain websites and applications, commonly referred to as YouTube Downloader, that let you do just that.

There are tons of options when it comes to YouTube downloaders.

While some may cost you a good few dollars to acquire, most are 100% free.

In fact, there are certain platforms that don’t even require you to download any software (all you need is the video URL and you’re good to go).

Indesign chromebook. If you’ve never done this before, and are paranoid that you might end up with a malware, keep reading.

We’ve talked about YouTube video editors in the past. This time, we’ll take you through 15 of the best free YouTube downloaders to try in 2021. In the end, I’ll also take you through quick do’s and don’ts of using these video downloaders.

Let’s get started.

The Best YouTube Downloaders to Try This Year

The following YouTube video grabber tools will reign supreme in 2021. Opera gx black screen.

1. KeepVid

Let’s start off with the most basic (and one of the most popular) tools.

KeepVid (by iTubeGo) is the go-to website to download YouTube videos in MP4 format.

Apart from individual videos, the tool also lets you conveniently download complete YouTube playlists in one go.

Other than that, you can also download videos from Facebook, Instagram, and Dailymotion.

2. y2mate

y2mate is another (rather simple) YouTube to MP4 converter.

Simply copy and paste the video link into the field on the homepage and click “start.”

A great thing about y2mate is that it allows you to download videos in different resolutions, from 144p to 1080p.

Additionally, the tool also lets you download just the audio, or convert and download videos into MP3 files.

3. Videoder

Videoder is a free video downloader available for Windows and Android.

The software lets you download 4K videos from not only YouTube, but over 1,000 other websites, as well (whereas the android version lets you download from a little over 50 different sites).

Furthermore, the desktop version lets you create personal collections of videos and audios. This means no more buffering or browsing through a clutter of files.

4. Snaptube

Snaptube is another user-friendly tool that lets you download YouTube videos in different resolutions and formats.

Some of the formats that Snaptube supports include M4A, MP4, and MP3.

As of now, the tool is only available for Android, but it isn't available on Google Play - so you’ll need to download the APK.

Similar to the Android version of Videoder, Snaptube lets you download videos from over 50 different sites, besides YouTube.

5. Airy

Airy is a renowned YouTube video downloader that lets you convert videos into various formats and resolutions (including Ultra HD).

Some of the supported formats include:

MP4

FLV

3GP

MP3

Unlike some plug-and-play tools, you'll need to download Airy before you can use it. As of now, it’s available for both Windows and Mac OS.

The tool also integrates with all popular browsers, including:

Chrome

Firefox

Safari

Opera

This allows you to “save” the videos you like, and download them later.

6. TubeMate

TubeMate is another standard YouTube downloader that lets you grab your favorite videos in MP4 and 4GP formats (as well as in audio formats, including MP3 and WAV).

The tool also comes with its own video player and a built-in search feature that lets you find videos conveniently.

TubeMate is available for both Android and Windows.

7. 4K Video Downloader

4K Downloader is a well-known provider of free content-grabbing products. Norwegian post box.

Their most popular tool is the 4K Video Downloader, which lets you download videos from YouTube, Vimeo, Facebook, and more.

As with TubeMate, this is another tool you'll need to download before you can start using it. At the moment, it’s only available for Windows.

Like a few of the tools discussed earlier, the 4K Video Downloader also lets you download complete playlists. Furthermore, it lets you download complete channels in one go.

8. YT Cutter

At times, we only need certain parts of videos.

While there are many free tools that let you trim and embed videos, only a few let you actually download them.

One of them is YT Cutter - it lets you download the bits that you like in a few different formats, like so:

It even lets you download files as a GIF. However, if you’d like to learn how to make a GIF, I suggest using a different tool.

9. Gihosoft TubeGet

Gihosoft is a renowned provider of (both paid and free) data recovery tools, file encryption, video convertor, and downloading tools.

One of their popular products include the Gihosoft TubeGet – a standard, user-friendly YouTube downloader – that’s available for Windows and Mac operating systems.

The tool allows you to download videos in 4 different formats (MP4, MKV, AVI, and MOV).

Youtube Video Downloader Mp3 Addon For Firefox

In addition, it also lets you:

Convert downloaded videos from WebM into various popular formats

Add subtitles to your videos

There are both free and paid versions available for Gihosoft TubeGet. The only differences between the two versions is that with the later, you also get license(s) and technical support.

10. YTOFFLINE

Mp3 From Youtube Video

YTOFFLINE is a plug-and-play, ready-to-go, YouTube downloader that lets you save your favorite videos on the go.

Just copy and paste the URL into the field and click “Go.”

Once it finishes processing your video, follow these steps:

Scroll down and right click on the “Download” button.

Select “save link as” (will vary from browser to browser), choose where you want your video to be saved, and click on “Save.”

YTOFFLINE is 100% secure and uses SSL encryption.

11. VideoProc

VideoProc is an extensive video processing software (by Digiarty), with a wide range of capabilities.

Big sur camping. Paragon NTFS on macOS Big Sur A great third-party app to use is Mircosoft NTFS for Mac by Paragon Software. This app allows you to edit, copy, move, delete, and read NTFS files from your Mac computer. It is super fast and has a really easy interface so you do not get confused during the process. Mar 22, 2021 #Fast #Safe #free NTFS for Mac Big Sur #NTFS for M1 Mac NTFS for Mac, like iBoysoft NTFS for Mac, Paragon NTFS for Mac, or Tuxera NTFS for Mac, is a third-party file system driver that enables writing to NTFS-formatted drives on Mac. But only iBoysoft NTFS for Mac has been proven to have the highest performance.

With the help of this tool, you can cut, merge, crop, rotate, and do much more to make click-worthy videos.

In addition, the software also includes an built-in “media downloader,' which lets you download videos from over 1,000 websites.

The tool also lets you convert downloaded videos into MP4, MP3, and other formats supported by both iPhones and Android devices.

VideoProc is available for free (for Windows and Mac). There’s also a pro-version with advanced features and additional services.

12. VidMate

Next on the list is VidMate, yet another YouTube downloader for Android.

The platform lets you download videos from YouTube, along with over 200 other platforms.

It also lets you stream online videos in HD.

A key feature of VidMate is its integrated downloader, which provides fast download speeds (even with slow internet connections).

Like all video downloaders, this tool isn’t available on Google Play due to Google’s policy against downloading content from YouTube. Due to that, you’ll have to download the APK and install it manually on your device.

13. iTubeGo YouTube Downloader

iTubeGo is an extensive content-grabbing tool that lets you download music and video.

On top of that, it also lets you convert videos into MP3 (audio), download YouTube playlists at once, and manage multiple downloads.

Right now, it’s available for both Windows and Mac. You can enjoy all of the main features with the free version.

14. Softorino YouTube Converter 2

Built for Mac and Windows, Softorino YouTube Converter 2 allows you to convert and download YouTube videos into different formats.

Apart from YouTube, the software also supports up to 60 other platforms.

15. ClipGrab

Marketed as a “friendly downloader for YouTube,” ClipGrab is the last on the list.

However, that doesn’t mean that it’s not as good as the others. In fact, in terms of simplicity and ease-of-use, it’s one of the best tools out there.

Not only does it allow you to download videos from YouTube, but Vimeo and Facebook, as well.

As of now, ClipGrab is only compatible with Windows.

Is Downloading YouTube Videos Legal?

Whether you want to do video marketing or just want to keep content saved on your device, it is illegal to download YouTube videos.

Because of that, most of the tools discussed above aren’t available for download from major app stores.

You should only download a video if:

It’s your own property

It’s a royalty-free stock footage

You get permission from the original owner/uploader

The reason why YouTube discourages downloading is to protect its users and retain them on their platform.

Enjoy Your Videos

Now that you’ve downloaded your favorite video(s), it’s time to spice them up and make them your own assets.

Remember – you can always use Lumen5 to create stunning videos with just a few clicks.

Youtube Video Downloader Mp3 Mp4

Obaid is the Founder & Creative Director of Planet Content. His focus lies on content creation, 2D animation, and taking the boring & annoying out of marketing.

[wickedbananas]

How Much Data Is Missing from Analytics? And Other Analytics Black Holes

Posted by Tom.Capper

If you’ve ever compared two analytics implementations on the same site, or compared your analytics with what your business is reporting in sales, you’ve probably noticed that things don’t always match up. In this post, I’ll explain why data is missing from your web analytics platforms and how large the impact could be. Some of the issues I cover are actually quite easily addressed, and have a decent impact on traffic — there’s never been an easier way to hit your quarterly targets. ;)

I’m going to focus on GA (Google Analytics), as it's the most commonly used provider, but most on-page analytics platforms have the same issues. Platforms that rely on server logs do avoid some issues but are fairly rare, so I won’t cover them in any depth.

Side note: Our test setup (multiple trackers & customized GA)

On Distilled.net, we have a standard Google Analytics property running from an HTML tag in GTM (Google Tag Manager). In addition, for the last two years, I’ve been running three extra concurrent Google Analytics implementations, designed to measure discrepancies between different configurations.

(If you’re just interested in my findings, you can skip this section, but if you want to hear more about the methodology, continue reading. Similarly, don’t worry if you don’t understand some of the detail here — the results are easier to follow.)

Two of these extra implementations — one in Google Tag Manager and one on page — run locally hosted, renamed copies of the Google Analytics JavaScript file (e.g. www.distilled.net/static/js/au3.js, instead of www.google-analytics.com/analytics.js) to make them harder to spot for ad blockers. I also used renamed JavaScript functions (“tcap” and “Buffoon,” rather than the standard “ga”) and renamed trackers (“FredTheUnblockable” and “AlbertTheImmutable”) to avoid having duplicate trackers (which can often cause issues).

This was originally inspired by 2016-era best practice on how to get your Google Analytics setup past ad blockers. I can’t find the original article now, but you can see a very similar one from 2017 here.

Lastly, we have (“DianaTheIndefatigable”), which just has a renamed tracker, but uses the standard code otherwise and is implemented on-page. This is to complete the set of all combinations of modified and unmodified GTM and on-page trackers.

Two of Distilled’s modified on-page trackers, as seen on https://www.distilled.net/

Overall, this table summarizes our setups:

Tracker

Renamed function?

GTM or on-page?

Locally hosted JavaScript file?

Default

No

GTM HTML tag

No

FredTheUnblockable

Yes - “tcap”

GTM HTML tag

Yes

AlbertTheImmutable

Yes - “buffoon”

On page

Yes

DianaTheIndefatigable

No

On page

No

I tested their functionality in various browser/ad-block environments by watching for the pageviews appearing in browser developer tools:

Reason 1: Ad Blockers

Ad blockers, primarily as browser extensions, have been growing in popularity for some time now. Primarily this has been to do with users looking for better performance and UX on ad-laden sites, but in recent years an increased emphasis on privacy has also crept in, hence the possibility of analytics blocking.

Effect of ad blockers

Some ad blockers block web analytics platforms by default, others can be configured to do so. I tested Distilled’s site with Adblock Plus and uBlock Origin, two of the most popular ad-blocking desktop browser addons, but it’s worth noting that ad blockers are increasingly prevalent on smartphones, too.

Here’s how Distilled’s setups fared:

(All numbers shown are from April 2018)

Setup

Vs. Adblock

Vs. Adblock with “EasyPrivacy” enabled

Vs. uBlock Origin

GTM

Pass

Fail

Fail

On page

Pass

Fail

Fail

GTM + renamed script & function

Pass

Fail

Fail

On page + renamed script & function

Pass

Fail

Fail

Seems like those tweaked setups didn’t do much!

Lost data due to ad blockers: ~10%

Ad blocker usage can be in the 15–25% range depending on region, but many of these installs will be default setups of AdBlock Plus, which as we’ve seen above, does not block tracking. Estimates of AdBlock Plus’s market share among ad blockers vary from 50–70%, with more recent reports tending more towards the former. So, if we assume that at most 50% of installed ad blockers block analytics, that leaves your exposure at around 10%.

Reason 2: Browser “do not track”

This is another privacy motivated feature, this time of browsers themselves. You can enable it in the settings of most current browsers. It’s not compulsory for sites or platforms to obey the “do not track” request, but Firefox offers a stronger feature under the same set of options, which I decided to test as well.

Effect of “do not track”

Most browsers now offer the option to send a “Do not track” message. I tested the latest releases of Firefox & Chrome for Windows 10.

Setup

Chrome “do not track”

Firefox “do not track”

Firefox “tracking protection”

GTM

Pass

Pass

Fail

On page

Pass

Pass

Fail

GTM + renamed script & function

Pass

Pass

Fail

On page + renamed script & function

Pass

Pass

Fail

Again, it doesn’t seem that the tweaked setups are doing much work for us here.

Lost data due to “do not track”: <1%

Only Firefox Quantum’s “Tracking Protection,” introduced in February, had any effect on our trackers. Firefox has a 5% market share, but Tracking Protection is not enabled by default. The launch of this feature had no effect on the trend for Firefox traffic on Distilled.net.

Reason 3: Filters

It’s a bit of an obvious one, but filters you’ve set up in your analytics might intentionally or unintentionally reduce your reported traffic levels.

For example, a filter excluding certain niche screen resolutions that you believe to be mostly bots, or internal traffic, will obviously cause your setup to underreport slightly.

Lost data due to filters: ???

Impact is hard to estimate, as setup will obviously vary on a site-by site-basis. I do recommend having a duplicate, unfiltered “master” view in case you realize too late you’ve lost something you didn’t intend to.

Reason 4: GTM vs. on-page vs. misplaced on-page

Google Tag Manager has become an increasingly popular way of implementing analytics in recent years, due to its increased flexibility and the ease of making changes. However, I’ve long noticed that it can tend to underreport vs. on-page setups.

I was also curious about what would happen if you didn’t follow Google’s guidelines in setting up on-page code.

By combining my numbers with numbers from my colleague Dom Woodman’s site (you’re welcome for the link, Dom), which happens to use a Drupal analytics add-on as well as GTM, I was able to see the difference between Google Tag Manager and misplaced on-page code (right at the bottom of the <body> tag) I then weighted this against my own Google Tag Manager data to get an overall picture of all 5 setups.

Effect of GTM and misplaced on-page code

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Chrome

100.00%

98.75%

100.77%

99.80%

94.75%

Safari

100.00%

99.42%

100.55%

102.08%

82.69%

Firefox

100.00%

99.71%

101.16%

101.45%

90.68%

Internet Explorer

100.00%

80.06%

112.31%

113.37%

77.18%

There are a few main takeaways here:

On-page code generally reports more traffic than GTM

Modified code is generally within a margin of error, apart from modified GTM code on Internet Explorer (see note below)

Misplaced analytics code will cost you up to a third of your traffic vs. properly implemented on-page code, depending on browser (!)

The customized setups, which are designed to get more traffic by evading ad blockers, are doing nothing of the sort.

It’s worth noting also that the customized implementations actually got less traffic than the standard ones. For the on-page code, this is within the margin of error, but for Google Tag Manager, there’s another reason — because I used unfiltered profiles for the comparison, there’s a lot of bot spam in the main profile, which primarily masquerades as Internet Explorer. Our main profile is by far the most spammed, and also acting as the baseline here, so the difference between on-page code and Google Tag Manager is probably somewhat larger than what I’m reporting.

I also split the data by mobile, out of curiosity:

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Desktop

100.00%

98.31%

100.97%

100.89%

93.47%

Mobile

100.00%

97.00%

103.78%

100.42%

89.87%

Tablet

100.00%

97.68%

104.20%

102.43%

88.13%

The further takeaway here seems to be that mobile browsers, like Internet Explorer, can struggle with Google Tag Manager.

Lost data due to GTM: 1–5%

Google Tag Manager seems to cost you a varying amount depending on what make-up of browsers and devices use your site. On Distilled.net, the difference is around 1.7%; however, we have an unusually desktop-heavy and tech-savvy audience (not much Internet Explorer!). Depending on vertical, this could easily swell to the 5% range.

Lost data due to misplaced on-page code: ~10%

On Teflsearch.com, the impact of misplaced on-page code was around 7.5%, vs Google Tag Manager. Keeping in mind that Google Tag Manager itself underreports, the total loss could easily be in the 10% range.

Bonus round: Missing data from channels

I’ve focused above on areas where you might be missing data altogether. However, there are also lots of ways in which data can be misrepresented, or detail can be missing. I’ll cover these more briefly, but the main issues are dark traffic and attribution.

Dark traffic

Dark traffic is direct traffic that didn’t really come via direct — which is generally becoming more and more common. Typical causes are:

Untagged campaigns in email

Untagged campaigns in apps (especially Facebook, Twitter, etc.)

Misrepresented organic

Data sent from botched tracking implementations (which can also appear as self-referrals)

It’s also worth noting the trend towards genuinely direct traffic that would historically have been organic. For example, due to increasingly sophisticated browser autocompletes, cross-device history, and so on, people end up “typing” a URL that they’d have searched for historically.

Attribution

I’ve written about this in more detail here, but in general, a session in Google Analytics (and any other platform) is a fairly arbitrary construct — you might think it’s obvious how a group of hits should be grouped into one or more sessions, but in fact, the process relies on a number of fairly questionable assumptions. In particular, it’s worth noting that Google Analytics generally attributes direct traffic (including dark traffic) to the previous non-direct source, if one exists.

Discussion

I was quite surprised by some of my own findings when researching this post, but I’m sure I didn’t get everything. Can you think of any other ways in which data can end up missing from analytics?

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[gauravrajput]

Google Analytics is an excellent tool, but it is not perfect. In Gaurav Digital we use it every day, and that's why we decided to translate the following analysis that Tom Capper did for Search Engine Land about the data gaps in Analytics. Here, the first part about  ad blockers and browsers with "no track" option.

Analytics black holes

If you have ever compared two Analytics implementations in one place, or if you have compared your Analytics with what your company is reporting in sales, you have probably noticed that things do not always coincide. In this publication we will explain why there is a lack of data in the web analysis platforms and how big the impact could be. Some of these problems are fairly easy to address and have a decent impact on traffic. There has never been an easier way to achieve your quarterly goals. We will focus on Google Analytics because it is the most commonly used provider. But most on-page analysis platforms  have the same problems. Platforms that depend on server logs avoid some problems, but they are quite rare; We will not cover them in depth.

Reason 1: Ad Blockers

The Ad Blockers, mainly as browser extensions have been growing in popularity for some time. More than anything, this has had to do with users looking for better performance and user experience on sites full of ads. In recent years the emphasis on privacy has also increased: that is why the possibility of analytical blockade.

Effects of  Ad Blockers

Some ad blockers block web analysis platforms by default and others can be configured to do so. We tested with Adblock Plus and uBlock Origin, two of the most popular ad blocking desktop browser add-ons. Also, it's worth noting that ad blockers are becoming more frequent on smartphones. So it went to the configurations we tested:

It would seem that the configurations have not served much!

Data lost by  ad blockers: ~ 10%

The use of  ad blockers can range from 15-25% depending on the region, but many of these facilities will be default configurations of AdBlock Plus. As we have seen previously, they do not block tracking. The estimates of the AdBlock Plus market share among ad blockers vary from 50 to 70%, and the most recent reports tend more towards the former. Therefore, if we assume that, at most, 50% of the ad blockers installed block the analysis, that leaves their exposure around 10%.

Reason 2: browsers with "do not track" option

This is another function motivated by privacy, but this time from the browsers themselves. You can enable it in the configuration of most current browsers. It is not mandatory for sites or platforms to obey the "do not track" request, but Firefox offers a stronger function with the same set of options, which we have also decided to try.

Effects of "do not track"

Most browsers now offer the option to send a "do not track" message. We have tested the latest versions of Firefox and Chrome for Windows 10.

Again, it does not seem that the adjusted settings are doing a lot of work for us here.

Data lost due to "not tracking": <1%

Only the "Tracking Protection" of Firefox Quantum, introduced in February, had some effect on our crawlers. Firefox has a 5% market share, but Tracking Protection is not enabled by default. The launch of this feature had no effect on the trend of Firefox traffic in our test. In the second part of the article we will talk about the filters and Google Tag Manager vs on-page.

Reason 3: Analytics filters

It's a bit obvious, but the filters you've set up in your Analytics can intentionally reduce (or not) the reported traffic levels. For example, a filter that excludes certain niche screen resolutions that you create (perhaps without sufficient reasons) that are mainly bots or internal traffic. These cases, obviously, will cause your configuration to not be reported correctly.

Impact of data loss by filters?:

The impact is difficult to estimate: the configuration will obviously vary site by site. We recommend having a "master" view duplicated and unfiltered in case you realize too late that you've lost something you did not intend to lose.

Reason 4: GTM vs. on-page vs.On-page poorly implemented

Google Tag Manager has become an increasingly popular way to implement analysis in recent years, due to its great flexibility and the ease of making changes. However, we have noticed for some time that you may have to report fewer on-page configurations. We were also curious about what would happen if we did not follow Google's guidelines when setting up the code on the page. By combining our numbers with the site numbers of a colleague who uses a Drupal and GTM add-on, we could see the difference between Google Tag Manager and a badly implemented on-page code (just at the bottom of the <body tag>). We ponder this with our own Google Tag Manager data to get an overall picture of the 5 settings.

Effect of GTM and poorly implemented on-page codes

Traffic as a percentage of the baseline (standard implementation of Google Tag Manager):

How Much Data is Missing from Analytics and Other Analytics Black Holes Moz

There are some main points here:

The on-page code usually reports more traffic than GTM.

The modified code usually has a margin of error; A separate case is the modified GTM code in Internet Explorer (see note below).

The badly located Analytics code will cost you up to a third of the traffic compared to the correctly implemented on-page code, depending on the browser (!).

Custom configurations, which are designed to get more traffic by avoiding ad blockers , are not doing anything like that.

It is also worth noting that custom implementations actually got less traffic than implemented. For the on-page code, this is within the margin of error, but for GTM there is another reason (because we use unfiltered profiles for comparison, there is a lot of spam bots in the main profile, which mainly masquerades as Internet Explorer. We also divide the data by devices:

How Much Data is Missing from Analytics and Other Analytics Black Holes Moz

Apparently mobile browsers, such as Internet Explorer, may have difficulties with Google Tag Manager.

Data lost by GTM: 1-5%

On our colleague's site, the impact of poorly implemented code was around 7.5% vs. the GTM. Taking into account that the GTM itself presents erroneous reports, the total loss could easily be within 10%.

Bonus: lost data from channels

We have focused on areas where data may be missing altogether. However, there are also many ways in which data may be misrepresented, or details may be missing. The main problem is dark traffic.

Dark traffic

Dark traffic is direct traffic that did not really come via direct (and that is becoming increasingly common). The typical causes are:

Email campaigns without labels.

Campaigns in applications without labels (especially Facebook, Twitter, etc.)

Organic poorly represented.

Data sent from failed tracking implementations (which can also appear as self-referrals)

It is also worth noting the trend towards genuinely direct traffic that, historically, would have been organic. For example, due to the increasingly sophisticated browser autocompletes, the history of various devices, etc., people end up "typing" a URL that they would historically have searched for.

[rsharma6431]

How to Speed Up Firefox

Your web browser of choice is truly the gateway into accessing the global Internet. The web has been growing exponentially, and we have seen tremendous changes to browsing software as well. Mozilla has been keeping up well considering the recent release of Firefox 10 which has seen mostly positive review. But as we all know, your web browser tends to slow down over time with repeated use. Firefox is not immune to this, but there are some tweaks you can use to optimize the browsing experience. The key values we’re looking for include startup speed, reduced load times, and accessible web pages. Check out some of my tips in the guide below if you’re looking to enhance the Firefox experience!

Quick Shortcut Commands

A good place to start is with a few handy keyboard shortcuts. These can be difficult to memorize at first, but over repeated use you’ll begin to adopt the routine. And I feel there’s no better way to speed up your web browsing experience than mastering a few shortcut keys. Only a couple examples may seem relevant to your needs. We don’t all require the same knowledge and so one command may be totally pointless to somebody else. If you check through Google you’ll likely find very helpful articles for the more common shortcuts.

1. Clear Private Data

Security is of the utmost importance to consider whenever you’re surfing the web. Even by today’s standards things are a lot less risky than 5 or 10 years ago. But you should understand how private browsing data is stored and what you can do to clear your info.

This short menu which pops up is a condensed version of the settings panel. You can choose how far back in time to clear out along with specific types of data such as cookies, cached pages, active login sessions, etc. I recommend that you clear everything within the list every time you close down the browser window. This is only my personal preference to keep my data secure – but of course you should adopt some form of routine cleanup which works best for you. Shortcut – Ctrl + Shift + Delete

2. Add-Ons Toolbar

The Firefox add-ons menu is a small toolbar which appears at the bottom of your Firefox window. From here you can access add-on commands and menus which are normally reserved from within the regular plug-ins area. This may be one of the lesser-known shortcuts but does come in handy frequently. If you like to keep your browser slim with reduced add-ons then this may pose as a bit uninteresting. And I have to agree that fewer 3rd-party extensions means much quicker browser performance. Just keep this in mind as you’re testing out new add-ons from time to time. Shortcut – Ctrl + /

3. Open Downloads Window

There have been numerous instances using Firefox where I’ve been downloading files and accidentally clicked out of the downloads window. It’s a harmless gesture, though it can be a pain to find your menu again. This command brings up not just your active downloads but also recent history of previous files – very handy when you forget which folder you saved into! Shortcut – Ctrl+J Note: For Mac users, replace Ctrl with Command.

Increase Local Cache Storage

When Firefox saves a cached version of website content it reduces any future requests needed for re-downloading code. By default you can only max out to 1GB of saved cache from the web. But this is likely such a small amount compared to your overall disk space, it’s well worth the effort to update your cache sizes. I recall Firefox 8.0 had local cache storage at 256MB by default. Honestly this is a fair amount of room, especially if you’re clearing out private data at the end of each session. Yet if you browse for hours at a time each repeat website visit will accumulate possibly 10-15 minutes of saved load screens.

In the top menu open Tools -> Options or Firefox -> Preferences... on Mac and click on the Advanced Tab. Somewhere in the middle of this menu you’ll see “Limit cache to” along with a number input. I’ve chosen 1024MB which happens to be the maximum allowed. Simply hit OK and restart the browser for this to take effect.

Popular yet Minimalist Add-Ons

It’s a good idea to keep wary of installing too many extensions into Firefox. The browser will begin to lag fairly quickly if you neglect to disable unused add-ons, but luckily it’s also an easy process to remove them. Below are a couple of the most popular user-voted add-ons which won’t interfere with your speed or page performance.

1. Download Status Bar

In particular this is a very helpful addon I’ve come to love since first installing. The download statusbar is not obtrusive or even displayed in any way until you download a file. Instead of having a new window appear you get a neat toolbar at the very bottom of your browser window.

From this you can check the total file size and amount remaining, along with an estimate of time remaining for the download to complete. You can single-click on a file to pause and even remove items from the queue. My process of downloading files has become more streamlined than ever now that I’m not dealing with a new window for my items list. If you haven’t tried this out yet I highly recommend giving it a shot!

2. WOT – Check Trustworthy Websites

The funky plug-in with a weird name actually has taken me by surprise! As the title says: WOT – Know Which Websites to Trust provides a rating for every website you visit. These are backed by users of the software who have given rankings to sites all over the Internet.

Many users feel this has little-to-no purpose since you can gauge the legitimacy of a website within the first few seconds of landing. Definitely true, but I do frequently cycle through random websites found in social network communities like StumbleUpon. In this scenario I feel WOT hasn’t provided any first step security, but it does help me build credibility and trust for domains I run into through differing sources.

3. Element Hiding Helper for ABP

Most Firefox users are familiar with Adblock Plus which has proven time and again as a sure-fire ads remover. From this core a developer Wladimir Palantfrom ABP released an extension called Element Hiding Helper. Now you can target any specific page element and choose to block it regardless of the internal content. This is perfect for when you don’t want to block all advertisements on a website but you need to remove 1 or 2 of them for whatever reason. Often times video websites will have loud audio ads start playing out of nowhere – and this plug-in is the perfect remedy. You can choose to remove things other than advertisements, such as annoying JavaScript apps or specific HTML blocks within the page layout.

4. Speed Dial

This feature has become standard to users of the Opera browser and more recently has been picked up by Google Chrome. Yet the speed dial home page setup was never implemented into Firefox in any majorly functional way.

This plug-in gives you total control over which links appear where in the 9-box grid system. You have easy access to manipulate settings as well, such as default thumbnail height/width and a few keyboard shortcuts. Overall the software has a lot of support from the Mozilla userbase. If you want to learn more check out the official website for detailed features and release notes.

System Edits in about:config

Firefox users have the ability to edit internal variables within the software from the configuration area. Simply open a new tab, type about:config and hit enter. You’ll come to a warning page mentioning the dangers of blindly changing these settings. But we know what we’re doing, so just hit “I’ll be careful” and you’ll be directed to sorted table of values.

Each of the values in the far left column are associated with a type of variable name. These control instances of how the software runs and performs in the background. I have just a few suggestions for reliable edits.

1. Increase pipelining

In the filter box at the top type in network.http.pipelining.maxrequests. This should limit your field to a single value row set at 4. We can increase this number to 8, which means Firefox can request data through 8 different channels rather than 4 – greatly decreasing your waiting time! Once you edit this value above you’ll need to enable pipelining to see any major effects. Do a search for network.http.pipelining and the first value should be set to false by default. You want to change this to true by double-clicking on the table row.

2. Disable placeholder images

Sometimes when Firefox realizes a page is going to take a while to download it will apply placeholder images. This is to prevent page content from rendering improperly while waiting for the image data. It seems like a good idea in concept, and it does have value but I feel disabling this feature will keep the requested content organized. In the filter box do a search for browser.display.show_image_placeholders which should be set as true. Double-click to change this to false and we should be all set.

3. Disable interface animations

While we’re removing unnecessary features let’s turn our attention to the browser UI. By default Firefox uses a small animation effect whenever you open or switch onto a new tab. It seems small at a glance but once you disable this you’ll be shocked at how much quicker you can move and create tabs. Just do a search for browser.tabs.animate and change the value to false.

4. Increase persistent connections

This variable is similar to pipelining except now we’re looking to open more connections on the server end. This is set much lower at first to keep Firefox downloading at a steady pace. But if you are downloading larger content such as streaming audio or video more persistent connections will mean more data collected at once. In the filter box enter network.http.max-persistent-connections-per-server and you should find only one result. By default the value should be 6, but double-click and change to 8. Then hit okay and restart your browser for these effects to kick in!

Conclusion

With so many options in today’s browser market Firefox appears to be holding a steady place. Their engineers know how to build stable software as it has been a reliable brand for years. With the endless number of plugins and extensions free to download there are solutions for practically any problem. I hope these tips can provide a solid foundation for optimizing your web browsing experience. If you have any other great ideas for speeding up Firefox please let us know in the discussion area. Read the full article

[techcoreglimp]

Best Youtube Adblock Chrome Extension

Best YouTube Adblock Chrome Extension

What is a YouTube Adblock Chrome Extension?

A YouTube Adblock Chrome extension is a software program that blocks ads from appearing on YouTube. These extensions work by filtering out the code that is used to display ads. This can include pre-roll ads, banner ads, and pop-up ads.

Benefits of Using a YouTube Adblock Chrome Extension

There are many benefits to using a YouTube Adblock Chrome extension. Some of the most notable benefits include:

Improved user experience: Ads can be disruptive and annoying, especially when they are long or intrusive. Blocking ads can improve the user experience by making YouTube videos more enjoyable to watch.

Faster loading times: Ads can slow down the loading time of YouTube videos. Blocking ads can improve the loading time of videos, which can be especially beneficial for people with slow internet connections.

Reduced data usage: Ads can consume a lot of data, especially if they are high-quality videos. Blocking ads can reduce your data usage, which can be especially beneficial for people with limited data plans.

Increased privacy: Some ads can track your browsing activity and collect personal data. Blocking ads can help to protect your privacy by preventing advertisers from tracking you.

Find More at metech-arm.com

How to Choose the Best YouTube Adblock Chrome Extension

There are many different YouTube Adblock Chrome extensions available. When choosing an extension, it is important to consider the following factors:

Effectiveness: Make sure to choose an extension that is effective at blocking a wide variety of ads, including pre-roll ads, banner ads, and pop-up ads.

Usability: Choose an extension that is easy to use and configure.

Performance: Make sure to choose an extension that does not slow down the loading time of YouTube videos or consume too much memory.

Reputation: Choose an extension from a reputable developer with a good track record.

Top 10 Best YouTube Adblock Chrome Extensions in 2023

AdBlock: AdBlock is one of the most popular adblock Chrome extensions, and for good reason.

uBlock Origin: uBlock Origin is another popular adblock Chrome extension.

Ghostery: Ghostery is a privacy-focused adblock Chrome extension.

AdGuard: AdGuard is another adblock Chrome extension that is focused on privacy.

Enhancer for YouTube: Enhancer for YouTube is an adblock Chrome extension that offers a number of features in addition to ad blocking.

YouTube AdBlocker: YouTube AdBlocker is a simple and effective adblock Chrome extension.

Pure Tuber: Pure Tuber is an adblock Chrome extension that is specifically designed for YouTube.

Video Ad Blocker for YouTube: Video Ad Blocker for YouTube is a simple and effective adblock Chrome extension.

AdBlock Plus: AdBlock Plus is another popular adblock Chrome extension.

Ad Muncher: Ad Muncher is an adblock Chrome extension that is focused on privacy.

Which adblock Chrome extension should you choose?

The best adblock Chrome extension for you will depend on your individual needs and preferences. No matter which adblock Chrome extension you choose, you are sure to see a significant reduction in the number of ads that you see on YouTube. This will make for a more enjoyable and uninterrupted viewing experience.

Additional tips for choosing an adblock Chrome extension

Consider the features that are important to you.

Read reviews of different adblock Chrome extensions to see what other users have to say.

Make sure that the adblock Chrome extension that you choose is compatible with your browser.

How to Install and Use a YouTube Adblock Chrome Extension

To install a YouTube Adblock Chrome extension, simply visit the Chrome Web Store and search for the extension you want to install. Once you have found the extension, click the "Add to Chrome" button.

Once the extension is installed, you will need to enable it. To do this, click the Chrome extension icon in the top right corner of the browser window and select the extension you want to enable.

Troubleshooting Common Problems with YouTube Adblock Chrome Extensions

If you are experiencing problems with your YouTube Adblock Chrome extension, there are a few things you can try:

Make sure the extension is enabled.

Clear your browser cache and cookies.

Update your extension to the latest version.

Try a different adblocker.

If you are still having problems, you can contact the developer of the extension for further assistance.

[tainghekhongdaycomvn]

How Much Data Is Missing from Analytics? And Other Analytics Black Holes

How Much Data Is Missing from Analytics? And Other Analytics Black Holes

Posted by Tom.Capper

If you’ve ever compared two analytics implementations on the same site, or compared your analytics with what your business is reporting in sales, you’ve probably noticed that things don’t always match up. In this post, I’ll explain why data is missing from your web analytics platforms and how large the impact could be. Some of the issues I cover are actually quite easily addressed, and have a decent impact on traffic — there’s never been an easier way to hit your quarterly targets. ;)

I’m going to focus on GA (Google Analytics), as it's the most commonly used provider, but most on-page analytics platforms have the same issues. Platforms that rely on server logs do avoid some issues but are fairly rare, so I won’t cover them in any depth.

Side note: Our test setup (multiple trackers & customized GA)

On Distilled.net, we have a standard Google Analytics property running from an HTML tag in GTM (Google Tag Manager). In addition, for the last two years, I’ve been running three extra concurrent Google Analytics implementations, designed to measure discrepancies between different configurations.

(If you’re just interested in my findings, you can skip this section, but if you want to hear more about the methodology, continue reading. Similarly, don’t worry if you don’t understand some of the detail here — the results are easier to follow.)

Two of these extra implementations — one in Google Tag Manager and one on page — run locally hosted, renamed copies of the Google Analytics JavaScript file (e.g. www.distilled.net/static/js/au3.js, instead of www.google-analytics.com/analytics.js) to make them harder to spot for ad blockers. I also used renamed JavaScript functions (“tcap” and “Buffoon,” rather than the standard “ga”) and renamed trackers (“FredTheUnblockable” and “AlbertTheImmutable”) to avoid having duplicate trackers (which can often cause issues).

This was originally inspired by 2016-era best practice on how to get your Google Analytics setup past ad blockers. I can’t find the original article now, but you can see a very similar one from 2017 here.

Lastly, we have (“DianaTheIndefatigable”), which just has a renamed tracker, but uses the standard code otherwise and is implemented on-page. This is to complete the set of all combinations of modified and unmodified GTM and on-page trackers.

Two of Distilled’s modified on-page trackers, as seen on https://www.distilled.net/

Overall, this table summarizes our setups:

Tracker

Renamed function?

GTM or on-page?

Locally hosted JavaScript file?

Default

No

GTM HTML tag

No

FredTheUnblockable

Yes - “tcap”

GTM HTML tag

Yes

AlbertTheImmutable

Yes - “buffoon”

On page

Yes

DianaTheIndefatigable

No

On page

No

I tested their functionality in various browser/ad-block environments by watching for the pageviews appearing in browser developer tools:

Reason 1: Ad Blockers

Ad blockers, primarily as browser extensions, have been growing in popularity for some time now. Primarily this has been to do with users looking for better performance and UX on ad-laden sites, but in recent years an increased emphasis on privacy has also crept in, hence the possibility of analytics blocking.

Effect of ad blockers

Some ad blockers block web analytics platforms by default, others can be configured to do so. I tested Distilled’s site with Adblock Plus and uBlock Origin, two of the most popular ad-blocking desktop browser addons, but it’s worth noting that ad blockers are increasingly prevalent on smartphones, too.

Here’s how Distilled’s setups fared:

(All numbers shown are from April 2018)

Setup

Vs. Adblock

Vs. Adblock with “EasyPrivacy” enabled

Vs. uBlock Origin

GTM

Pass

Fail

Fail

On page

Pass

Fail

Fail

GTM + renamed script & function

Pass

Fail

Fail

On page + renamed script & function

Pass

Fail

Fail

Seems like those tweaked setups didn’t do much!

Lost data due to ad blockers: ~10%

Ad blocker usage can be in the 15–25% range depending on region, but many of these installs will be default setups of AdBlock Plus, which as we’ve seen above, does not block tracking. Estimates of AdBlock Plus’s market share among ad blockers vary from 50–70%, with more recent reports tending more towards the former. So, if we assume that at most 50% of installed ad blockers block analytics, that leaves your exposure at around 10%.

Reason 2: Browser “do not track”

This is another privacy motivated feature, this time of browsers themselves. You can enable it in the settings of most current browsers. It’s not compulsory for sites or platforms to obey the “do not track” request, but Firefox offers a stronger feature under the same set of options, which I decided to test as well.

Effect of “do not track”

Most browsers now offer the option to send a “Do not track” message. I tested the latest releases of Firefox & Chrome for Windows 10.

Setup

Chrome “do not track”

Firefox “do not track”

Firefox “tracking protection”

GTM

Pass

Pass

Fail

On page

Pass

Pass

Fail

GTM + renamed script & function

Pass

Pass

Fail

On page + renamed script & function

Pass

Pass

Fail

Again, it doesn’t seem that the tweaked setups are doing much work for us here.

Lost data due to “do not track”: <1%

Only Firefox Quantum’s “Tracking Protection,” introduced in February, had any effect on our trackers. Firefox has a 5% market share, but Tracking Protection is not enabled by default. The launch of this feature had no effect on the trend for Firefox traffic on Distilled.net.

Reason 3: Filters

It’s a bit of an obvious one, but filters you’ve set up in your analytics might intentionally or unintentionally reduce your reported traffic levels.

For example, a filter excluding certain niche screen resolutions that you believe to be mostly bots, or internal traffic, will obviously cause your setup to underreport slightly.

Lost data due to filters: ???

Impact is hard to estimate, as setup will obviously vary on a site-by site-basis. I do recommend having a duplicate, unfiltered “master” view in case you realize too late you’ve lost something you didn’t intend to.

Reason 4: GTM vs. on-page vs. misplaced on-page

Google Tag Manager has become an increasingly popular way of implementing analytics in recent years, due to its increased flexibility and the ease of making changes. However, I’ve long noticed that it can tend to underreport vs. on-page setups.

I was also curious about what would happen if you didn’t follow Google’s guidelines in setting up on-page code.

By combining my numbers with numbers from my colleague Dom Woodman’s site (you’re welcome for the link, Dom), which happens to use a Drupal analytics add-on as well as GTM, I was able to see the difference between Google Tag Manager and misplaced on-page code (right at the bottom of the <body> tag) I then weighted this against my own Google Tag Manager data to get an overall picture of all 5 setups.

Effect of GTM and misplaced on-page code

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Chrome

100.00%

98.75%

100.77%

99.80%

94.75%

Safari

100.00%

99.42%

100.55%

102.08%

82.69%

Firefox

100.00%

99.71%

101.16%

101.45%

90.68%

Internet Explorer

100.00%

80.06%

112.31%

113.37%

77.18%

There are a few main takeaways here:

On-page code generally reports more traffic than GTM

Modified code is generally within a margin of error, apart from modified GTM code on Internet Explorer (see note below)

Misplaced analytics code will cost you up to a third of your traffic vs. properly implemented on-page code, depending on browser (!)

The customized setups, which are designed to get more traffic by evading ad blockers, are doing nothing of the sort.

It’s worth noting also that the customized implementations actually got less traffic than the standard ones. For the on-page code, this is within the margin of error, but for Google Tag Manager, there’s another reason — because I used unfiltered profiles for the comparison, there’s a lot of bot spam in the main profile, which primarily masquerades as Internet Explorer. Our main profile is by far the most spammed, and also acting as the baseline here, so the difference between on-page code and Google Tag Manager is probably somewhat larger than what I’m reporting.

I also split the data by mobile, out of curiosity:

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Desktop

100.00%

98.31%

100.97%

100.89%

93.47%

Mobile

100.00%

97.00%

103.78%

100.42%

89.87%

Tablet

100.00%

97.68%

104.20%

102.43%

88.13%

The further takeaway here seems to be that mobile browsers, like Internet Explorer, can struggle with Google Tag Manager.

Lost data due to GTM: 1–5%

Google Tag Manager seems to cost you a varying amount depending on what make-up of browsers and devices use your site. On Distilled.net, the difference is around 1.7%; however, we have an unusually desktop-heavy and tech-savvy audience (not much Internet Explorer!). Depending on vertical, this could easily swell to the 5% range.

Lost data due to misplaced on-page code: ~10%

On Teflsearch.com, the impact of misplaced on-page code was around 7.5%, vs Google Tag Manager. Keeping in mind that Google Tag Manager itself underreports, the total loss could easily be in the 10% range.

Bonus round: Missing data from channels

I’ve focused above on areas where you might be missing data altogether. However, there are also lots of ways in which data can be misrepresented, or detail can be missing. I’ll cover these more briefly, but the main issues are dark traffic and attribution.

Dark traffic

Dark traffic is direct traffic that didn’t really come via direct — which is generally becoming more and more common. Typical causes are:

Untagged campaigns in email

Untagged campaigns in apps (especially Facebook, Twitter, etc.)

Misrepresented organic

Data sent from botched tracking implementations (which can also appear as self-referrals)

It’s also worth noting the trend towards genuinely direct traffic that would historically have been organic. For example, due to increasingly sophisticated browser autocompletes, cross-device history, and so on, people end up “typing” a URL that they’d have searched for historically.

Attribution

I’ve written about this in more detail here, but in general, a session in Google Analytics (and any other platform) is a fairly arbitrary construct — you might think it’s obvious how a group of hits should be grouped into one or more sessions, but in fact, the process relies on a number of fairly questionable assumptions. In particular, it’s worth noting that Google Analytics generally attributes direct traffic (including dark traffic) to the previous non-direct source, if one exists.

Discussion

I was quite surprised by some of my own findings when researching this post, but I’m sure I didn’t get everything. Can you think of any other ways in which data can end up missing from analytics?

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[isearchgoood]

How Much Data Is Missing from Analytics? And Other Analytics Black Holes

Posted by Tom.Capper

If you’ve ever compared two analytics implementations on the same site, or compared your analytics with what your business is reporting in sales, you’ve probably noticed that things don’t always match up. In this post, I’ll explain why data is missing from your web analytics platforms and how large the impact could be. Some of the issues I cover are actually quite easily addressed, and have a decent impact on traffic — there’s never been an easier way to hit your quarterly targets. ;)

I’m going to focus on GA (Google Analytics), as it's the most commonly used provider, but most on-page analytics platforms have the same issues. Platforms that rely on server logs do avoid some issues but are fairly rare, so I won’t cover them in any depth.

Side note: Our test setup (multiple trackers & customized GA)

On Distilled.net, we have a standard Google Analytics property running from an HTML tag in GTM (Google Tag Manager). In addition, for the last two years, I’ve been running three extra concurrent Google Analytics implementations, designed to measure discrepancies between different configurations.

(If you’re just interested in my findings, you can skip this section, but if you want to hear more about the methodology, continue reading. Similarly, don’t worry if you don’t understand some of the detail here — the results are easier to follow.)

Two of these extra implementations — one in Google Tag Manager and one on page — run locally hosted, renamed copies of the Google Analytics JavaScript file (e.g. www.distilled.net/static/js/au3.js, instead of www.google-analytics.com/analytics.js) to make them harder to spot for ad blockers. I also used renamed JavaScript functions (“tcap” and “Buffoon,” rather than the standard “ga”) and renamed trackers (“FredTheUnblockable” and “AlbertTheImmutable”) to avoid having duplicate trackers (which can often cause issues).

This was originally inspired by 2016-era best practice on how to get your Google Analytics setup past ad blockers. I can’t find the original article now, but you can see a very similar one from 2017 here.

Lastly, we have (“DianaTheIndefatigable”), which just has a renamed tracker, but uses the standard code otherwise and is implemented on-page. This is to complete the set of all combinations of modified and unmodified GTM and on-page trackers.

Two of Distilled’s modified on-page trackers, as seen on https://www.distilled.net/

Overall, this table summarizes our setups:

Tracker

Renamed function?

GTM or on-page?

Locally hosted JavaScript file?

Default

No

GTM HTML tag

No

FredTheUnblockable

Yes - “tcap”

GTM HTML tag

Yes

AlbertTheImmutable

Yes - “buffoon”

On page

Yes

DianaTheIndefatigable

No

On page

No

I tested their functionality in various browser/ad-block environments by watching for the pageviews appearing in browser developer tools:

Reason 1: Ad Blockers

Ad blockers, primarily as browser extensions, have been growing in popularity for some time now. Primarily this has been to do with users looking for better performance and UX on ad-laden sites, but in recent years an increased emphasis on privacy has also crept in, hence the possibility of analytics blocking.

Effect of ad blockers

Some ad blockers block web analytics platforms by default, others can be configured to do so. I tested Distilled’s site with Adblock Plus and uBlock Origin, two of the most popular ad-blocking desktop browser addons, but it’s worth noting that ad blockers are increasingly prevalent on smartphones, too.

Here’s how Distilled’s setups fared:

(All numbers shown are from April 2018)

Setup

Vs. Adblock

Vs. Adblock with “EasyPrivacy” enabled

Vs. uBlock Origin

GTM

Pass

Fail

Fail

On page

Pass

Fail

Fail

GTM + renamed script & function

Pass

Fail

Fail

On page + renamed script & function

Pass

Fail

Fail

Seems like those tweaked setups didn’t do much!

Lost data due to ad blockers: ~10%

Ad blocker usage can be in the 15–25% range depending on region, but many of these installs will be default setups of AdBlock Plus, which as we’ve seen above, does not block tracking. Estimates of AdBlock Plus’s market share among ad blockers vary from 50–70%, with more recent reports tending more towards the former. So, if we assume that at most 50% of installed ad blockers block analytics, that leaves your exposure at around 10%.

Reason 2: Browser “do not track”

This is another privacy motivated feature, this time of browsers themselves. You can enable it in the settings of most current browsers. It’s not compulsory for sites or platforms to obey the “do not track” request, but Firefox offers a stronger feature under the same set of options, which I decided to test as well.

Effect of “do not track”

Most browsers now offer the option to send a “Do not track” message. I tested the latest releases of Firefox & Chrome for Windows 10.

Setup

Chrome “do not track”

Firefox “do not track”

Firefox “tracking protection”

GTM

Pass

Pass

Fail

On page

Pass

Pass

Fail

GTM + renamed script & function

Pass

Pass

Fail

On page + renamed script & function

Pass

Pass

Fail

Again, it doesn’t seem that the tweaked setups are doing much work for us here.

Lost data due to “do not track”: <1%

Only Firefox Quantum’s “Tracking Protection,” introduced in February, had any effect on our trackers. Firefox has a 5% market share, but Tracking Protection is not enabled by default. The launch of this feature had no effect on the trend for Firefox traffic on Distilled.net.

Reason 3: Filters

It’s a bit of an obvious one, but filters you’ve set up in your analytics might intentionally or unintentionally reduce your reported traffic levels.

For example, a filter excluding certain niche screen resolutions that you believe to be mostly bots, or internal traffic, will obviously cause your setup to underreport slightly.

Lost data due to filters: ???

Impact is hard to estimate, as setup will obviously vary on a site-by site-basis. I do recommend having a duplicate, unfiltered “master” view in case you realize too late you’ve lost something you didn’t intend to.

Reason 4: GTM vs. on-page vs. misplaced on-page

Google Tag Manager has become an increasingly popular way of implementing analytics in recent years, due to its increased flexibility and the ease of making changes. However, I’ve long noticed that it can tend to underreport vs. on-page setups.

I was also curious about what would happen if you didn’t follow Google’s guidelines in setting up on-page code.

By combining my numbers with numbers from my colleague Dom Woodman’s site (you’re welcome for the link, Dom), which happens to use a Drupal analytics add-on as well as GTM, I was able to see the difference between Google Tag Manager and misplaced on-page code (right at the bottom of the <body> tag) I then weighted this against my own Google Tag Manager data to get an overall picture of all 5 setups.

Effect of GTM and misplaced on-page code

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Chrome

100.00%

98.75%

100.77%

99.80%

94.75%

Safari

100.00%

99.42%

100.55%

102.08%

82.69%

Firefox

100.00%

99.71%

101.16%

101.45%

90.68%

Internet Explorer

100.00%

80.06%

112.31%

113.37%

77.18%

There are a few main takeaways here:

On-page code generally reports more traffic than GTM

Modified code is generally within a margin of error, apart from modified GTM code on Internet Explorer (see note below)

Misplaced analytics code will cost you up to a third of your traffic vs. properly implemented on-page code, depending on browser (!)

The customized setups, which are designed to get more traffic by evading ad blockers, are doing nothing of the sort.

It’s worth noting also that the customized implementations actually got less traffic than the standard ones. For the on-page code, this is within the margin of error, but for Google Tag Manager, there’s another reason — because I used unfiltered profiles for the comparison, there’s a lot of bot spam in the main profile, which primarily masquerades as Internet Explorer. Our main profile is by far the most spammed, and also acting as the baseline here, so the difference between on-page code and Google Tag Manager is probably somewhat larger than what I’m reporting.

I also split the data by mobile, out of curiosity:

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Desktop

100.00%

98.31%

100.97%

100.89%

93.47%

Mobile

100.00%

97.00%

103.78%

100.42%

89.87%

Tablet

100.00%

97.68%

104.20%

102.43%

88.13%

The further takeaway here seems to be that mobile browsers, like Internet Explorer, can struggle with Google Tag Manager.

Lost data due to GTM: 1–5%

Google Tag Manager seems to cost you a varying amount depending on what make-up of browsers and devices use your site. On Distilled.net, the difference is around 1.7%; however, we have an unusually desktop-heavy and tech-savvy audience (not much Internet Explorer!). Depending on vertical, this could easily swell to the 5% range.

Lost data due to misplaced on-page code: ~10%

On Teflsearch.com, the impact of misplaced on-page code was around 7.5%, vs Google Tag Manager. Keeping in mind that Google Tag Manager itself underreports, the total loss could easily be in the 10% range.

Bonus round: Missing data from channels

I’ve focused above on areas where you might be missing data altogether. However, there are also lots of ways in which data can be misrepresented, or detail can be missing. I’ll cover these more briefly, but the main issues are dark traffic and attribution.

Dark traffic

Dark traffic is direct traffic that didn’t really come via direct — which is generally becoming more and more common. Typical causes are:

Untagged campaigns in email

Untagged campaigns in apps (especially Facebook, Twitter, etc.)

Misrepresented organic

Data sent from botched tracking implementations (which can also appear as self-referrals)

It’s also worth noting the trend towards genuinely direct traffic that would historically have been organic. For example, due to increasingly sophisticated browser autocompletes, cross-device history, and so on, people end up “typing” a URL that they’d have searched for historically.

Attribution

I’ve written about this in more detail here, but in general, a session in Google Analytics (and any other platform) is a fairly arbitrary construct — you might think it’s obvious how a group of hits should be grouped into one or more sessions, but in fact, the process relies on a number of fairly questionable assumptions. In particular, it’s worth noting that Google Analytics generally attributes direct traffic (including dark traffic) to the previous non-direct source, if one exists.

Discussion

I was quite surprised by some of my own findings when researching this post, but I’m sure I didn’t get everything. Can you think of any other ways in which data can end up missing from analytics?

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

via Blogger https://ift.tt/2kwAy68 #blogger #bloggingtips #bloggerlife #bloggersgetsocial #ontheblog #writersofinstagram #writingprompt #instapoetry #writerscommunity #writersofig #writersblock #writerlife #writtenword #instawriters #spilledink #wordgasm #creativewriting #poetsofinstagram #blackoutpoetry #poetsofig

[lawrenceseitz22]

How Much Data Is Missing from Analytics? And Other Analytics Black Holes

Posted by Tom.Capper

If you’ve ever compared two analytics implementations on the same site, or compared your analytics with what your business is reporting in sales, you’ve probably noticed that things don’t always match up. In this post, I’ll explain why data is missing from your web analytics platforms and how large the impact could be. Some of the issues I cover are actually quite easily addressed, and have a decent impact on traffic — there’s never been an easier way to hit your quarterly targets. ;)

I’m going to focus on GA (Google Analytics), as it's the most commonly used provider, but most on-page analytics platforms have the same issues. Platforms that rely on server logs do avoid some issues but are fairly rare, so I won’t cover them in any depth.

Side note: Our test setup (multiple trackers & customized GA)

On Distilled.net, we have a standard Google Analytics property running from an HTML tag in GTM (Google Tag Manager). In addition, for the last two years, I’ve been running three extra concurrent Google Analytics implementations, designed to measure discrepancies between different configurations.

(If you’re just interested in my findings, you can skip this section, but if you want to hear more about the methodology, continue reading. Similarly, don’t worry if you don’t understand some of the detail here — the results are easier to follow.)

Two of these extra implementations — one in Google Tag Manager and one on page — run locally hosted, renamed copies of the Google Analytics JavaScript file (e.g. www.distilled.net/static/js/au3.js, instead of www.google-analytics.com/analytics.js) to make them harder to spot for ad blockers. I also used renamed JavaScript functions (“tcap” and “Buffoon,” rather than the standard “ga”) and renamed trackers (“FredTheUnblockable” and “AlbertTheImmutable”) to avoid having duplicate trackers (which can often cause issues).

This was originally inspired by 2016-era best practice on how to get your Google Analytics setup past ad blockers. I can’t find the original article now, but you can see a very similar one from 2017 here.

Lastly, we have (“DianaTheIndefatigable”), which just has a renamed tracker, but uses the standard code otherwise and is implemented on-page. This is to complete the set of all combinations of modified and unmodified GTM and on-page trackers.

Two of Distilled’s modified on-page trackers, as seen on https://www.distilled.net/

Overall, this table summarizes our setups:

Tracker

Renamed function?

GTM or on-page?

Locally hosted JavaScript file?

Default

No

GTM HTML tag

No

FredTheUnblockable

Yes - “tcap”

GTM HTML tag

Yes

AlbertTheImmutable

Yes - “buffoon”

On page

Yes

DianaTheIndefatigable

No

On page

No

I tested their functionality in various browser/ad-block environments by watching for the pageviews appearing in browser developer tools:

Reason 1: Ad Blockers

Ad blockers, primarily as browser extensions, have been growing in popularity for some time now. Primarily this has been to do with users looking for better performance and UX on ad-laden sites, but in recent years an increased emphasis on privacy has also crept in, hence the possibility of analytics blocking.

Effect of ad blockers

Some ad blockers block web analytics platforms by default, others can be configured to do so. I tested Distilled’s site with Adblock Plus and uBlock Origin, two of the most popular ad-blocking desktop browser addons, but it’s worth noting that ad blockers are increasingly prevalent on smartphones, too.

Here’s how Distilled’s setups fared:

(All numbers shown are from April 2018)

Setup

Vs. Adblock

Vs. Adblock with “EasyPrivacy” enabled

Vs. uBlock Origin

GTM

Pass

Fail

Fail

On page

Pass

Fail

Fail

GTM + renamed script & function

Pass

Fail

Fail

On page + renamed script & function

Pass

Fail

Fail

Seems like those tweaked setups didn’t do much!

Lost data due to ad blockers: ~10%

Ad blocker usage can be in the 15–25% range depending on region, but many of these installs will be default setups of AdBlock Plus, which as we’ve seen above, does not block tracking. Estimates of AdBlock Plus’s market share among ad blockers vary from 50–70%, with more recent reports tending more towards the former. So, if we assume that at most 50% of installed ad blockers block analytics, that leaves your exposure at around 10%.

Reason 2: Browser “do not track”

This is another privacy motivated feature, this time of browsers themselves. You can enable it in the settings of most current browsers. It’s not compulsory for sites or platforms to obey the “do not track” request, but Firefox offers a stronger feature under the same set of options, which I decided to test as well.

Effect of “do not track”

Most browsers now offer the option to send a “Do not track” message. I tested the latest releases of Firefox & Chrome for Windows 10.

Setup

Chrome “do not track”

Firefox “do not track”

Firefox “tracking protection”

GTM

Pass

Pass

Fail

On page

Pass

Pass

Fail

GTM + renamed script & function

Pass

Pass

Fail

On page + renamed script & function

Pass

Pass

Fail

Again, it doesn’t seem that the tweaked setups are doing much work for us here.

Lost data due to “do not track”: <1%

Only Firefox Quantum’s “Tracking Protection,” introduced in February, had any effect on our trackers. Firefox has a 5% market share, but Tracking Protection is not enabled by default. The launch of this feature had no effect on the trend for Firefox traffic on Distilled.net.

Reason 3: Filters

It’s a bit of an obvious one, but filters you’ve set up in your analytics might intentionally or unintentionally reduce your reported traffic levels.

For example, a filter excluding certain niche screen resolutions that you believe to be mostly bots, or internal traffic, will obviously cause your setup to underreport slightly.

Lost data due to filters: ???

Impact is hard to estimate, as setup will obviously vary on a site-by site-basis. I do recommend having a duplicate, unfiltered “master” view in case you realize too late you’ve lost something you didn’t intend to.

Reason 4: GTM vs. on-page vs. misplaced on-page

Google Tag Manager has become an increasingly popular way of implementing analytics in recent years, due to its increased flexibility and the ease of making changes. However, I’ve long noticed that it can tend to underreport vs. on-page setups.

I was also curious about what would happen if you didn’t follow Google’s guidelines in setting up on-page code.

By combining my numbers with numbers from my colleague Dom Woodman’s site (you’re welcome for the link, Dom), which happens to use a Drupal analytics add-on as well as GTM, I was able to see the difference between Google Tag Manager and misplaced on-page code (right at the bottom of the <body> tag) I then weighted this against my own Google Tag Manager data to get an overall picture of all 5 setups.

Effect of GTM and misplaced on-page code

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Chrome

100.00%

98.75%

100.77%

99.80%

94.75%

Safari

100.00%

99.42%

100.55%

102.08%

82.69%

Firefox

100.00%

99.71%

101.16%

101.45%

90.68%

Internet Explorer

100.00%

80.06%

112.31%

113.37%

77.18%

There are a few main takeaways here:

On-page code generally reports more traffic than GTM

Modified code is generally within a margin of error, apart from modified GTM code on Internet Explorer (see note below)

Misplaced analytics code will cost you up to a third of your traffic vs. properly implemented on-page code, depending on browser (!)

The customized setups, which are designed to get more traffic by evading ad blockers, are doing nothing of the sort.

It’s worth noting also that the customized implementations actually got less traffic than the standard ones. For the on-page code, this is within the margin of error, but for Google Tag Manager, there’s another reason — because I used unfiltered profiles for the comparison, there’s a lot of bot spam in the main profile, which primarily masquerades as Internet Explorer. Our main profile is by far the most spammed, and also acting as the baseline here, so the difference between on-page code and Google Tag Manager is probably somewhat larger than what I’m reporting.

I also split the data by mobile, out of curiosity:

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Desktop

100.00%

98.31%

100.97%

100.89%

93.47%

Mobile

100.00%

97.00%

103.78%

100.42%

89.87%

Tablet

100.00%

97.68%

104.20%

102.43%

88.13%

The further takeaway here seems to be that mobile browsers, like Internet Explorer, can struggle with Google Tag Manager.

Lost data due to GTM: 1–5%

Google Tag Manager seems to cost you a varying amount depending on what make-up of browsers and devices use your site. On Distilled.net, the difference is around 1.7%; however, we have an unusually desktop-heavy and tech-savvy audience (not much Internet Explorer!). Depending on vertical, this could easily swell to the 5% range.

Lost data due to misplaced on-page code: ~10%

On Teflsearch.com, the impact of misplaced on-page code was around 7.5%, vs Google Tag Manager. Keeping in mind that Google Tag Manager itself underreports, the total loss could easily be in the 10% range.

Bonus round: Missing data from channels

I’ve focused above on areas where you might be missing data altogether. However, there are also lots of ways in which data can be misrepresented, or detail can be missing. I’ll cover these more briefly, but the main issues are dark traffic and attribution.

Dark traffic

Dark traffic is direct traffic that didn’t really come via direct — which is generally becoming more and more common. Typical causes are:

Untagged campaigns in email

Untagged campaigns in apps (especially Facebook, Twitter, etc.)

Misrepresented organic

Data sent from botched tracking implementations (which can also appear as self-referrals)

It’s also worth noting the trend towards genuinely direct traffic that would historically have been organic. For example, due to increasingly sophisticated browser autocompletes, cross-device history, and so on, people end up “typing” a URL that they’d have searched for historically.

Attribution

I’ve written about this in more detail here, but in general, a session in Google Analytics (and any other platform) is a fairly arbitrary construct — you might think it’s obvious how a group of hits should be grouped into one or more sessions, but in fact, the process relies on a number of fairly questionable assumptions. In particular, it’s worth noting that Google Analytics generally attributes direct traffic (including dark traffic) to the previous non-direct source, if one exists.

Discussion

I was quite surprised by some of my own findings when researching this post, but I’m sure I didn’t get everything. Can you think of any other ways in which data can end up missing from analytics?

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

from Blogger https://ift.tt/2KZaOKK via IFTTT

[swunlimitednj]

How Much Data Is Missing from Analytics? And Other Analytics Black Holes

Posted by Tom.Capper

If you’ve ever compared two analytics implementations on the same site, or compared your analytics with what your business is reporting in sales, you’ve probably noticed that things don’t always match up. In this post, I’ll explain why data is missing from your web analytics platforms and how large the impact could be. Some of the issues I cover are actually quite easily addressed, and have a decent impact on traffic — there’s never been an easier way to hit your quarterly targets. ;)

I’m going to focus on GA (Google Analytics), as it's the most commonly used provider, but most on-page analytics platforms have the same issues. Platforms that rely on server logs do avoid some issues but are fairly rare, so I won’t cover them in any depth.

Side note: Our test setup (multiple trackers & customized GA)

On Distilled.net, we have a standard Google Analytics property running from an HTML tag in GTM (Google Tag Manager). In addition, for the last two years, I’ve been running three extra concurrent Google Analytics implementations, designed to measure discrepancies between different configurations.

(If you’re just interested in my findings, you can skip this section, but if you want to hear more about the methodology, continue reading. Similarly, don’t worry if you don’t understand some of the detail here — the results are easier to follow.)

Two of these extra implementations — one in Google Tag Manager and one on page — run locally hosted, renamed copies of the Google Analytics JavaScript file (e.g. www.distilled.net/static/js/au3.js, instead of www.google-analytics.com/analytics.js) to make them harder to spot for ad blockers. I also used renamed JavaScript functions (“tcap” and “Buffoon,” rather than the standard “ga”) and renamed trackers (“FredTheUnblockable” and “AlbertTheImmutable”) to avoid having duplicate trackers (which can often cause issues).

This was originally inspired by 2016-era best practice on how to get your Google Analytics setup past ad blockers. I can’t find the original article now, but you can see a very similar one from 2017 here.

Lastly, we have (“DianaTheIndefatigable”), which just has a renamed tracker, but uses the standard code otherwise and is implemented on-page. This is to complete the set of all combinations of modified and unmodified GTM and on-page trackers.

Two of Distilled’s modified on-page trackers, as seen on https://www.distilled.net/

Overall, this table summarizes our setups:

Tracker

Renamed function?

GTM or on-page?

Locally hosted JavaScript file?

Default

No

GTM HTML tag

No

FredTheUnblockable

Yes - “tcap”

GTM HTML tag

Yes

AlbertTheImmutable

Yes - “buffoon”

On page

Yes

DianaTheIndefatigable

No

On page

No

I tested their functionality in various browser/ad-block environments by watching for the pageviews appearing in browser developer tools:

Reason 1: Ad Blockers

Ad blockers, primarily as browser extensions, have been growing in popularity for some time now. Primarily this has been to do with users looking for better performance and UX on ad-laden sites, but in recent years an increased emphasis on privacy has also crept in, hence the possibility of analytics blocking.

Effect of ad blockers

Some ad blockers block web analytics platforms by default, others can be configured to do so. I tested Distilled’s site with Adblock Plus and uBlock Origin, two of the most popular ad-blocking desktop browser addons, but it’s worth noting that ad blockers are increasingly prevalent on smartphones, too.

Here’s how Distilled’s setups fared:

(All numbers shown are from April 2018)

Setup

Vs. Adblock

Vs. Adblock with “EasyPrivacy” enabled

Vs. uBlock Origin

GTM

Pass

Fail

Fail

On page

Pass

Fail

Fail

GTM + renamed script & function

Pass

Fail

Fail

On page + renamed script & function

Pass

Fail

Fail

Seems like those tweaked setups didn’t do much!

Lost data due to ad blockers: ~10%

Ad blocker usage can be in the 15–25% range depending on region, but many of these installs will be default setups of AdBlock Plus, which as we’ve seen above, does not block tracking. Estimates of AdBlock Plus’s market share among ad blockers vary from 50–70%, with more recent reports tending more towards the former. So, if we assume that at most 50% of installed ad blockers block analytics, that leaves your exposure at around 10%.

Reason 2: Browser “do not track”

This is another privacy motivated feature, this time of browsers themselves. You can enable it in the settings of most current browsers. It’s not compulsory for sites or platforms to obey the “do not track” request, but Firefox offers a stronger feature under the same set of options, which I decided to test as well.

Effect of “do not track”

Most browsers now offer the option to send a “Do not track” message. I tested the latest releases of Firefox & Chrome for Windows 10.

Setup

Chrome “do not track”

Firefox “do not track”

Firefox “tracking protection”

GTM

Pass

Pass

Fail

On page

Pass

Pass

Fail

GTM + renamed script & function

Pass

Pass

Fail

On page + renamed script & function

Pass

Pass

Fail

Again, it doesn’t seem that the tweaked setups are doing much work for us here.

Lost data due to “do not track”: <1%

Only Firefox Quantum’s “Tracking Protection,” introduced in February, had any effect on our trackers. Firefox has a 5% market share, but Tracking Protection is not enabled by default. The launch of this feature had no effect on the trend for Firefox traffic on Distilled.net.

Reason 3: Filters

It’s a bit of an obvious one, but filters you’ve set up in your analytics might intentionally or unintentionally reduce your reported traffic levels.

For example, a filter excluding certain niche screen resolutions that you believe to be mostly bots, or internal traffic, will obviously cause your setup to underreport slightly.

Lost data due to filters: ???

Impact is hard to estimate, as setup will obviously vary on a site-by site-basis. I do recommend having a duplicate, unfiltered “master” view in case you realize too late you’ve lost something you didn’t intend to.

Reason 4: GTM vs. on-page vs. misplaced on-page

Google Tag Manager has become an increasingly popular way of implementing analytics in recent years, due to its increased flexibility and the ease of making changes. However, I’ve long noticed that it can tend to underreport vs. on-page setups.

I was also curious about what would happen if you didn’t follow Google’s guidelines in setting up on-page code.

By combining my numbers with numbers from my colleague Dom Woodman’s site (you’re welcome for the link, Dom), which happens to use a Drupal analytics add-on as well as GTM, I was able to see the difference between Google Tag Manager and misplaced on-page code (right at the bottom of the <body> tag) I then weighted this against my own Google Tag Manager data to get an overall picture of all 5 setups.

Effect of GTM and misplaced on-page code

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Chrome

100.00%

98.75%

100.77%

99.80%

94.75%

Safari

100.00%

99.42%

100.55%

102.08%

82.69%

Firefox

100.00%

99.71%

101.16%

101.45%

90.68%

Internet Explorer

100.00%

80.06%

112.31%

113.37%

77.18%

There are a few main takeaways here:

On-page code generally reports more traffic than GTM

Modified code is generally within a margin of error, apart from modified GTM code on Internet Explorer (see note below)

Misplaced analytics code will cost you up to a third of your traffic vs. properly implemented on-page code, depending on browser (!)

The customized setups, which are designed to get more traffic by evading ad blockers, are doing nothing of the sort.

It’s worth noting also that the customized implementations actually got less traffic than the standard ones. For the on-page code, this is within the margin of error, but for Google Tag Manager, there’s another reason — because I used unfiltered profiles for the comparison, there’s a lot of bot spam in the main profile, which primarily masquerades as Internet Explorer. Our main profile is by far the most spammed, and also acting as the baseline here, so the difference between on-page code and Google Tag Manager is probably somewhat larger than what I’m reporting.

I also split the data by mobile, out of curiosity:

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Desktop

100.00%

98.31%

100.97%

100.89%

93.47%

Mobile

100.00%

97.00%

103.78%

100.42%

89.87%

Tablet

100.00%

97.68%

104.20%

102.43%

88.13%

The further takeaway here seems to be that mobile browsers, like Internet Explorer, can struggle with Google Tag Manager.

Lost data due to GTM: 1–5%

Google Tag Manager seems to cost you a varying amount depending on what make-up of browsers and devices use your site. On Distilled.net, the difference is around 1.7%; however, we have an unusually desktop-heavy and tech-savvy audience (not much Internet Explorer!). Depending on vertical, this could easily swell to the 5% range.

Lost data due to misplaced on-page code: ~10%

On Teflsearch.com, the impact of misplaced on-page code was around 7.5%, vs Google Tag Manager. Keeping in mind that Google Tag Manager itself underreports, the total loss could easily be in the 10% range.

Bonus round: Missing data from channels

I’ve focused above on areas where you might be missing data altogether. However, there are also lots of ways in which data can be misrepresented, or detail can be missing. I’ll cover these more briefly, but the main issues are dark traffic and attribution.

Dark traffic

Dark traffic is direct traffic that didn’t really come via direct — which is generally becoming more and more common. Typical causes are:

Untagged campaigns in email

Untagged campaigns in apps (especially Facebook, Twitter, etc.)

Misrepresented organic

Data sent from botched tracking implementations (which can also appear as self-referrals)

It’s also worth noting the trend towards genuinely direct traffic that would historically have been organic. For example, due to increasingly sophisticated browser autocompletes, cross-device history, and so on, people end up “typing” a URL that they’d have searched for historically.

Attribution

I’ve written about this in more detail here, but in general, a session in Google Analytics (and any other platform) is a fairly arbitrary construct — you might think it’s obvious how a group of hits should be grouped into one or more sessions, but in fact, the process relies on a number of fairly questionable assumptions. In particular, it’s worth noting that Google Analytics generally attributes direct traffic (including dark traffic) to the previous non-direct source, if one exists.

Discussion

I was quite surprised by some of my own findings when researching this post, but I’m sure I didn’t get everything. Can you think of any other ways in which data can end up missing from analytics?

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

from Blogger https://ift.tt/2J9fNey via SW Unlimited

[rodneyevesuarywk]

How Much Data Is Missing from Analytics? And Other Analytics Black Holes

Posted by Tom.Capper

If you’ve ever compared two analytics implementations on the same site, or compared your analytics with what your business is reporting in sales, you’ve probably noticed that things don’t always match up. In this post, I’ll explain why data is missing from your web analytics platforms and how large the impact could be. Some of the issues I cover are actually quite easily addressed, and have a decent impact on traffic — there’s never been an easier way to hit your quarterly targets. ;)

I’m going to focus on GA (Google Analytics), as it's the most commonly used provider, but most on-page analytics platforms have the same issues. Platforms that rely on server logs do avoid some issues but are fairly rare, so I won’t cover them in any depth.

Side note: Our test setup (multiple trackers & customized GA)

On Distilled.net, we have a standard Google Analytics property running from an HTML tag in GTM (Google Tag Manager). In addition, for the last two years, I’ve been running three extra concurrent Google Analytics implementations, designed to measure discrepancies between different configurations.

(If you’re just interested in my findings, you can skip this section, but if you want to hear more about the methodology, continue reading. Similarly, don’t worry if you don’t understand some of the detail here — the results are easier to follow.)

Two of these extra implementations — one in Google Tag Manager and one on page — run locally hosted, renamed copies of the Google Analytics JavaScript file (e.g. www.distilled.net/static/js/au3.js, instead of www.google-analytics.com/analytics.js) to make them harder to spot for ad blockers. I also used renamed JavaScript functions (“tcap” and “Buffoon,” rather than the standard “ga”) and renamed trackers (“FredTheUnblockable” and “AlbertTheImmutable”) to avoid having duplicate trackers (which can often cause issues).

This was originally inspired by 2016-era best practice on how to get your Google Analytics setup past ad blockers. I can’t find the original article now, but you can see a very similar one from 2017 here.

Lastly, we have (“DianaTheIndefatigable”), which just has a renamed tracker, but uses the standard code otherwise and is implemented on-page. This is to complete the set of all combinations of modified and unmodified GTM and on-page trackers.

Two of Distilled’s modified on-page trackers, as seen on https://www.distilled.net/

Overall, this table summarizes our setups:

Tracker

Renamed function?

GTM or on-page?

Locally hosted JavaScript file?

Default

No

GTM HTML tag

No

FredTheUnblockable

Yes - “tcap”

GTM HTML tag

Yes

AlbertTheImmutable

Yes - “buffoon”

On page

Yes

DianaTheIndefatigable

No

On page

No

I tested their functionality in various browser/ad-block environments by watching for the pageviews appearing in browser developer tools:

Reason 1: Ad Blockers

Ad blockers, primarily as browser extensions, have been growing in popularity for some time now. Primarily this has been to do with users looking for better performance and UX on ad-laden sites, but in recent years an increased emphasis on privacy has also crept in, hence the possibility of analytics blocking.

Effect of ad blockers

Some ad blockers block web analytics platforms by default, others can be configured to do so. I tested Distilled’s site with Adblock Plus and uBlock Origin, two of the most popular ad-blocking desktop browser addons, but it’s worth noting that ad blockers are increasingly prevalent on smartphones, too.

Here’s how Distilled’s setups fared:

(All numbers shown are from April 2018)

Setup

Vs. Adblock

Vs. Adblock with “EasyPrivacy” enabled

Vs. uBlock Origin

GTM

Pass

Fail

Fail

On page

Pass

Fail

Fail

GTM + renamed script & function

Pass

Fail

Fail

On page + renamed script & function

Pass

Fail

Fail

Seems like those tweaked setups didn’t do much!

Lost data due to ad blockers: ~10%

Ad blocker usage can be in the 15–25% range depending on region, but many of these installs will be default setups of AdBlock Plus, which as we’ve seen above, does not block tracking. Estimates of AdBlock Plus’s market share among ad blockers vary from 50–70%, with more recent reports tending more towards the former. So, if we assume that at most 50% of installed ad blockers block analytics, that leaves your exposure at around 10%.

Reason 2: Browser “do not track”

This is another privacy motivated feature, this time of browsers themselves. You can enable it in the settings of most current browsers. It’s not compulsory for sites or platforms to obey the “do not track” request, but Firefox offers a stronger feature under the same set of options, which I decided to test as well.

Effect of “do not track”

Most browsers now offer the option to send a “Do not track” message. I tested the latest releases of Firefox & Chrome for Windows 10.

Setup

Chrome “do not track”

Firefox “do not track”

Firefox “tracking protection”

GTM

Pass

Pass

Fail

On page

Pass

Pass

Fail

GTM + renamed script & function

Pass

Pass

Fail

On page + renamed script & function

Pass

Pass

Fail

Again, it doesn’t seem that the tweaked setups are doing much work for us here.

Lost data due to “do not track”: <1%

Only Firefox Quantum’s “Tracking Protection,” introduced in February, had any effect on our trackers. Firefox has a 5% market share, but Tracking Protection is not enabled by default. The launch of this feature had no effect on the trend for Firefox traffic on Distilled.net.

Reason 3: Filters

It’s a bit of an obvious one, but filters you’ve set up in your analytics might intentionally or unintentionally reduce your reported traffic levels.

For example, a filter excluding certain niche screen resolutions that you believe to be mostly bots, or internal traffic, will obviously cause your setup to underreport slightly.

Lost data due to filters: ???

Impact is hard to estimate, as setup will obviously vary on a site-by site-basis. I do recommend having a duplicate, unfiltered “master” view in case you realize too late you’ve lost something you didn’t intend to.

Reason 4: GTM vs. on-page vs. misplaced on-page

Google Tag Manager has become an increasingly popular way of implementing analytics in recent years, due to its increased flexibility and the ease of making changes. However, I’ve long noticed that it can tend to underreport vs. on-page setups.

I was also curious about what would happen if you didn’t follow Google’s guidelines in setting up on-page code.

By combining my numbers with numbers from my colleague Dom Woodman’s site (you’re welcome for the link, Dom), which happens to use a Drupal analytics add-on as well as GTM, I was able to see the difference between Google Tag Manager and misplaced on-page code (right at the bottom of the <body> tag) I then weighted this against my own Google Tag Manager data to get an overall picture of all 5 setups.

Effect of GTM and misplaced on-page code

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Chrome

100.00%

98.75%

100.77%

99.80%

94.75%

Safari

100.00%

99.42%

100.55%

102.08%

82.69%

Firefox

100.00%

99.71%

101.16%

101.45%

90.68%

Internet Explorer

100.00%

80.06%

112.31%

113.37%

77.18%

There are a few main takeaways here:

On-page code generally reports more traffic than GTM

Modified code is generally within a margin of error, apart from modified GTM code on Internet Explorer (see note below)

Misplaced analytics code will cost you up to a third of your traffic vs. properly implemented on-page code, depending on browser (!)

The customized setups, which are designed to get more traffic by evading ad blockers, are doing nothing of the sort.

It’s worth noting also that the customized implementations actually got less traffic than the standard ones. For the on-page code, this is within the margin of error, but for Google Tag Manager, there’s another reason — because I used unfiltered profiles for the comparison, there’s a lot of bot spam in the main profile, which primarily masquerades as Internet Explorer. Our main profile is by far the most spammed, and also acting as the baseline here, so the difference between on-page code and Google Tag Manager is probably somewhat larger than what I’m reporting.

I also split the data by mobile, out of curiosity:

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Desktop

100.00%

98.31%

100.97%

100.89%

93.47%

Mobile

100.00%

97.00%

103.78%

100.42%

89.87%

Tablet

100.00%

97.68%

104.20%

102.43%

88.13%

The further takeaway here seems to be that mobile browsers, like Internet Explorer, can struggle with Google Tag Manager.

Lost data due to GTM: 1–5%

Google Tag Manager seems to cost you a varying amount depending on what make-up of browsers and devices use your site. On Distilled.net, the difference is around 1.7%; however, we have an unusually desktop-heavy and tech-savvy audience (not much Internet Explorer!). Depending on vertical, this could easily swell to the 5% range.

Lost data due to misplaced on-page code: ~10%

On Teflsearch.com, the impact of misplaced on-page code was around 7.5%, vs Google Tag Manager. Keeping in mind that Google Tag Manager itself underreports, the total loss could easily be in the 10% range.

Bonus round: Missing data from channels

I’ve focused above on areas where you might be missing data altogether. However, there are also lots of ways in which data can be misrepresented, or detail can be missing. I’ll cover these more briefly, but the main issues are dark traffic and attribution.

Dark traffic

Dark traffic is direct traffic that didn’t really come via direct — which is generally becoming more and more common. Typical causes are:

Untagged campaigns in email

Untagged campaigns in apps (especially Facebook, Twitter, etc.)

Misrepresented organic

Data sent from botched tracking implementations (which can also appear as self-referrals)

It’s also worth noting the trend towards genuinely direct traffic that would historically have been organic. For example, due to increasingly sophisticated browser autocompletes, cross-device history, and so on, people end up “typing” a URL that they’d have searched for historically.

Attribution

I’ve written about this in more detail here, but in general, a session in Google Analytics (and any other platform) is a fairly arbitrary construct — you might think it’s obvious how a group of hits should be grouped into one or more sessions, but in fact, the process relies on a number of fairly questionable assumptions. In particular, it’s worth noting that Google Analytics generally attributes direct traffic (including dark traffic) to the previous non-direct source, if one exists.

Discussion

I was quite surprised by some of my own findings when researching this post, but I’m sure I didn’t get everything. Can you think of any other ways in which data can end up missing from analytics?

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

https://ift.tt/2LCPWKo

[conniecogeie]

How Much Data Is Missing from Analytics? And Other Analytics Black Holes

Posted by Tom.Capper

If you’ve ever compared two analytics implementations on the same site, or compared your analytics with what your business is reporting in sales, you’ve probably noticed that things don’t always match up. In this post, I’ll explain why data is missing from your web analytics platforms and how large the impact could be. Some of the issues I cover are actually quite easily addressed, and have a decent impact on traffic — there’s never been an easier way to hit your quarterly targets. ;)

I’m going to focus on GA (Google Analytics), as it's the most commonly used provider, but most on-page analytics platforms have the same issues. Platforms that rely on server logs do avoid some issues but are fairly rare, so I won’t cover them in any depth.

Side note: Our test setup (multiple trackers & customized GA)

On Distilled.net, we have a standard Google Analytics property running from an HTML tag in GTM (Google Tag Manager). In addition, for the last two years, I’ve been running three extra concurrent Google Analytics implementations, designed to measure discrepancies between different configurations.

(If you’re just interested in my findings, you can skip this section, but if you want to hear more about the methodology, continue reading. Similarly, don’t worry if you don’t understand some of the detail here — the results are easier to follow.)

Two of these extra implementations — one in Google Tag Manager and one on page — run locally hosted, renamed copies of the Google Analytics JavaScript file (e.g. www.distilled.net/static/js/au3.js, instead of www.google-analytics.com/analytics.js) to make them harder to spot for ad blockers. I also used renamed JavaScript functions (“tcap” and “Buffoon,” rather than the standard “ga”) and renamed trackers (“FredTheUnblockable” and “AlbertTheImmutable”) to avoid having duplicate trackers (which can often cause issues).

This was originally inspired by 2016-era best practice on how to get your Google Analytics setup past ad blockers. I can’t find the original article now, but you can see a very similar one from 2017 here.

Lastly, we have (“DianaTheIndefatigable”), which just has a renamed tracker, but uses the standard code otherwise and is implemented on-page. This is to complete the set of all combinations of modified and unmodified GTM and on-page trackers.

Two of Distilled’s modified on-page trackers, as seen on https://www.distilled.net/

Overall, this table summarizes our setups:

Tracker

Renamed function?

GTM or on-page?

Locally hosted JavaScript file?

Default

No

GTM HTML tag

No

FredTheUnblockable

Yes - “tcap”

GTM HTML tag

Yes

AlbertTheImmutable

Yes - “buffoon”

On page

Yes

DianaTheIndefatigable

No

On page

No

I tested their functionality in various browser/ad-block environments by watching for the pageviews appearing in browser developer tools:

Reason 1: Ad Blockers

Ad blockers, primarily as browser extensions, have been growing in popularity for some time now. Primarily this has been to do with users looking for better performance and UX on ad-laden sites, but in recent years an increased emphasis on privacy has also crept in, hence the possibility of analytics blocking.

Effect of ad blockers

Some ad blockers block web analytics platforms by default, others can be configured to do so. I tested Distilled’s site with Adblock Plus and uBlock Origin, two of the most popular ad-blocking desktop browser addons, but it’s worth noting that ad blockers are increasingly prevalent on smartphones, too.

Here’s how Distilled’s setups fared:

(All numbers shown are from April 2018)

Setup

Vs. Adblock

Vs. Adblock with “EasyPrivacy” enabled

Vs. uBlock Origin

GTM

Pass

Fail

Fail

On page

Pass

Fail

Fail

GTM + renamed script & function

Pass

Fail

Fail

On page + renamed script & function

Pass

Fail

Fail

Seems like those tweaked setups didn’t do much!

Lost data due to ad blockers: ~10%

Ad blocker usage can be in the 15–25% range depending on region, but many of these installs will be default setups of AdBlock Plus, which as we’ve seen above, does not block tracking. Estimates of AdBlock Plus’s market share among ad blockers vary from 50–70%, with more recent reports tending more towards the former. So, if we assume that at most 50% of installed ad blockers block analytics, that leaves your exposure at around 10%.

Reason 2: Browser “do not track”

This is another privacy motivated feature, this time of browsers themselves. You can enable it in the settings of most current browsers. It’s not compulsory for sites or platforms to obey the “do not track” request, but Firefox offers a stronger feature under the same set of options, which I decided to test as well.

Effect of “do not track”

Most browsers now offer the option to send a “Do not track” message. I tested the latest releases of Firefox & Chrome for Windows 10.

Setup

Chrome “do not track”

Firefox “do not track”

Firefox “tracking protection”

GTM

Pass

Pass

Fail

On page

Pass

Pass

Fail

GTM + renamed script & function

Pass

Pass

Fail

On page + renamed script & function

Pass

Pass

Fail

Again, it doesn’t seem that the tweaked setups are doing much work for us here.

Lost data due to “do not track”: <1%

Only Firefox Quantum’s “Tracking Protection,” introduced in February, had any effect on our trackers. Firefox has a 5% market share, but Tracking Protection is not enabled by default. The launch of this feature had no effect on the trend for Firefox traffic on Distilled.net.

Reason 3: Filters

It’s a bit of an obvious one, but filters you’ve set up in your analytics might intentionally or unintentionally reduce your reported traffic levels.

For example, a filter excluding certain niche screen resolutions that you believe to be mostly bots, or internal traffic, will obviously cause your setup to underreport slightly.

Lost data due to filters: ???

Impact is hard to estimate, as setup will obviously vary on a site-by site-basis. I do recommend having a duplicate, unfiltered “master” view in case you realize too late you’ve lost something you didn’t intend to.

Reason 4: GTM vs. on-page vs. misplaced on-page

Google Tag Manager has become an increasingly popular way of implementing analytics in recent years, due to its increased flexibility and the ease of making changes. However, I’ve long noticed that it can tend to underreport vs. on-page setups.

I was also curious about what would happen if you didn’t follow Google’s guidelines in setting up on-page code.

By combining my numbers with numbers from my colleague Dom Woodman’s site (you’re welcome for the link, Dom), which happens to use a Drupal analytics add-on as well as GTM, I was able to see the difference between Google Tag Manager and misplaced on-page code (right at the bottom of the <body> tag) I then weighted this against my own Google Tag Manager data to get an overall picture of all 5 setups.

Effect of GTM and misplaced on-page code

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Chrome

100.00%

98.75%

100.77%

99.80%

94.75%

Safari

100.00%

99.42%

100.55%

102.08%

82.69%

Firefox

100.00%

99.71%

101.16%

101.45%

90.68%

Internet Explorer

100.00%

80.06%

112.31%

113.37%

77.18%

There are a few main takeaways here:

On-page code generally reports more traffic than GTM

Modified code is generally within a margin of error, apart from modified GTM code on Internet Explorer (see note below)

Misplaced analytics code will cost you up to a third of your traffic vs. properly implemented on-page code, depending on browser (!)

The customized setups, which are designed to get more traffic by evading ad blockers, are doing nothing of the sort.

It’s worth noting also that the customized implementations actually got less traffic than the standard ones. For the on-page code, this is within the margin of error, but for Google Tag Manager, there’s another reason — because I used unfiltered profiles for the comparison, there’s a lot of bot spam in the main profile, which primarily masquerades as Internet Explorer. Our main profile is by far the most spammed, and also acting as the baseline here, so the difference between on-page code and Google Tag Manager is probably somewhat larger than what I’m reporting.

I also split the data by mobile, out of curiosity:

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Desktop

100.00%

98.31%

100.97%

100.89%

93.47%

Mobile

100.00%

97.00%

103.78%

100.42%

89.87%

Tablet

100.00%

97.68%

104.20%

102.43%

88.13%

The further takeaway here seems to be that mobile browsers, like Internet Explorer, can struggle with Google Tag Manager.

Lost data due to GTM: 1–5%

Google Tag Manager seems to cost you a varying amount depending on what make-up of browsers and devices use your site. On Distilled.net, the difference is around 1.7%; however, we have an unusually desktop-heavy and tech-savvy audience (not much Internet Explorer!). Depending on vertical, this could easily swell to the 5% range.

Lost data due to misplaced on-page code: ~10%

On Teflsearch.com, the impact of misplaced on-page code was around 7.5%, vs Google Tag Manager. Keeping in mind that Google Tag Manager itself underreports, the total loss could easily be in the 10% range.

Bonus round: Missing data from channels

I’ve focused above on areas where you might be missing data altogether. However, there are also lots of ways in which data can be misrepresented, or detail can be missing. I’ll cover these more briefly, but the main issues are dark traffic and attribution.

Dark traffic

Dark traffic is direct traffic that didn’t really come via direct — which is generally becoming more and more common. Typical causes are:

Untagged campaigns in email

Untagged campaigns in apps (especially Facebook, Twitter, etc.)

Misrepresented organic

Data sent from botched tracking implementations (which can also appear as self-referrals)

It’s also worth noting the trend towards genuinely direct traffic that would historically have been organic. For example, due to increasingly sophisticated browser autocompletes, cross-device history, and so on, people end up “typing” a URL that they’d have searched for historically.

Attribution

I’ve written about this in more detail here, but in general, a session in Google Analytics (and any other platform) is a fairly arbitrary construct — you might think it’s obvious how a group of hits should be grouped into one or more sessions, but in fact, the process relies on a number of fairly questionable assumptions. In particular, it’s worth noting that Google Analytics generally attributes direct traffic (including dark traffic) to the previous non-direct source, if one exists.

Discussion

I was quite surprised by some of my own findings when researching this post, but I’m sure I didn’t get everything. Can you think of any other ways in which data can end up missing from analytics?

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

https://ift.tt/2LCPWKo

[christinesumpmg1]

How Much Data Is Missing from Analytics? And Other Analytics Black Holes

Posted by Tom.Capper

If you’ve ever compared two analytics implementations on the same site, or compared your analytics with what your business is reporting in sales, you’ve probably noticed that things don’t always match up. In this post, I’ll explain why data is missing from your web analytics platforms and how large the impact could be. Some of the issues I cover are actually quite easily addressed, and have a decent impact on traffic — there’s never been an easier way to hit your quarterly targets. ;)

I’m going to focus on GA (Google Analytics), as it's the most commonly used provider, but most on-page analytics platforms have the same issues. Platforms that rely on server logs do avoid some issues but are fairly rare, so I won’t cover them in any depth.

Side note: Our test setup (multiple trackers & customized GA)

On Distilled.net, we have a standard Google Analytics property running from an HTML tag in GTM (Google Tag Manager). In addition, for the last two years, I’ve been running three extra concurrent Google Analytics implementations, designed to measure discrepancies between different configurations.

(If you’re just interested in my findings, you can skip this section, but if you want to hear more about the methodology, continue reading. Similarly, don’t worry if you don’t understand some of the detail here — the results are easier to follow.)

Two of these extra implementations — one in Google Tag Manager and one on page — run locally hosted, renamed copies of the Google Analytics JavaScript file (e.g. www.distilled.net/static/js/au3.js, instead of www.google-analytics.com/analytics.js) to make them harder to spot for ad blockers. I also used renamed JavaScript functions (“tcap” and “Buffoon,” rather than the standard “ga”) and renamed trackers (“FredTheUnblockable” and “AlbertTheImmutable”) to avoid having duplicate trackers (which can often cause issues).

This was originally inspired by 2016-era best practice on how to get your Google Analytics setup past ad blockers. I can’t find the original article now, but you can see a very similar one from 2017 here.

Lastly, we have (“DianaTheIndefatigable”), which just has a renamed tracker, but uses the standard code otherwise and is implemented on-page. This is to complete the set of all combinations of modified and unmodified GTM and on-page trackers.

Two of Distilled’s modified on-page trackers, as seen on https://www.distilled.net/

Overall, this table summarizes our setups:

Tracker

Renamed function?

GTM or on-page?

Locally hosted JavaScript file?

Default

No

GTM HTML tag

No

FredTheUnblockable

Yes - “tcap”

GTM HTML tag

Yes

AlbertTheImmutable

Yes - “buffoon”

On page

Yes

DianaTheIndefatigable

No

On page

No

I tested their functionality in various browser/ad-block environments by watching for the pageviews appearing in browser developer tools:

Reason 1: Ad Blockers

Ad blockers, primarily as browser extensions, have been growing in popularity for some time now. Primarily this has been to do with users looking for better performance and UX on ad-laden sites, but in recent years an increased emphasis on privacy has also crept in, hence the possibility of analytics blocking.

Effect of ad blockers

Some ad blockers block web analytics platforms by default, others can be configured to do so. I tested Distilled’s site with Adblock Plus and uBlock Origin, two of the most popular ad-blocking desktop browser addons, but it’s worth noting that ad blockers are increasingly prevalent on smartphones, too.

Here’s how Distilled’s setups fared:

(All numbers shown are from April 2018)

Setup

Vs. Adblock

Vs. Adblock with “EasyPrivacy” enabled

Vs. uBlock Origin

GTM

Pass

Fail

Fail

On page

Pass

Fail

Fail

GTM + renamed script & function

Pass

Fail

Fail

On page + renamed script & function

Pass

Fail

Fail

Seems like those tweaked setups didn’t do much!

Lost data due to ad blockers: ~10%

Ad blocker usage can be in the 15–25% range depending on region, but many of these installs will be default setups of AdBlock Plus, which as we’ve seen above, does not block tracking. Estimates of AdBlock Plus’s market share among ad blockers vary from 50–70%, with more recent reports tending more towards the former. So, if we assume that at most 50% of installed ad blockers block analytics, that leaves your exposure at around 10%.

Reason 2: Browser “do not track”

This is another privacy motivated feature, this time of browsers themselves. You can enable it in the settings of most current browsers. It’s not compulsory for sites or platforms to obey the “do not track” request, but Firefox offers a stronger feature under the same set of options, which I decided to test as well.

Effect of “do not track”

Most browsers now offer the option to send a “Do not track” message. I tested the latest releases of Firefox & Chrome for Windows 10.

Setup

Chrome “do not track”

Firefox “do not track”

Firefox “tracking protection”

GTM

Pass

Pass

Fail

On page

Pass

Pass

Fail

GTM + renamed script & function

Pass

Pass

Fail

On page + renamed script & function

Pass

Pass

Fail

Again, it doesn’t seem that the tweaked setups are doing much work for us here.

Lost data due to “do not track”: <1%

Only Firefox Quantum’s “Tracking Protection,” introduced in February, had any effect on our trackers. Firefox has a 5% market share, but Tracking Protection is not enabled by default. The launch of this feature had no effect on the trend for Firefox traffic on Distilled.net.

Reason 3: Filters

It’s a bit of an obvious one, but filters you’ve set up in your analytics might intentionally or unintentionally reduce your reported traffic levels.

For example, a filter excluding certain niche screen resolutions that you believe to be mostly bots, or internal traffic, will obviously cause your setup to underreport slightly.

Lost data due to filters: ???

Impact is hard to estimate, as setup will obviously vary on a site-by site-basis. I do recommend having a duplicate, unfiltered “master” view in case you realize too late you’ve lost something you didn’t intend to.

Reason 4: GTM vs. on-page vs. misplaced on-page

Google Tag Manager has become an increasingly popular way of implementing analytics in recent years, due to its increased flexibility and the ease of making changes. However, I’ve long noticed that it can tend to underreport vs. on-page setups.

I was also curious about what would happen if you didn’t follow Google’s guidelines in setting up on-page code.

By combining my numbers with numbers from my colleague Dom Woodman’s site (you’re welcome for the link, Dom), which happens to use a Drupal analytics add-on as well as GTM, I was able to see the difference between Google Tag Manager and misplaced on-page code (right at the bottom of the <body> tag) I then weighted this against my own Google Tag Manager data to get an overall picture of all 5 setups.

Effect of GTM and misplaced on-page code

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Chrome

100.00%

98.75%

100.77%

99.80%

94.75%

Safari

100.00%

99.42%

100.55%

102.08%

82.69%

Firefox

100.00%

99.71%

101.16%

101.45%

90.68%

Internet Explorer

100.00%

80.06%

112.31%

113.37%

77.18%

There are a few main takeaways here:

On-page code generally reports more traffic than GTM

Modified code is generally within a margin of error, apart from modified GTM code on Internet Explorer (see note below)

Misplaced analytics code will cost you up to a third of your traffic vs. properly implemented on-page code, depending on browser (!)

The customized setups, which are designed to get more traffic by evading ad blockers, are doing nothing of the sort.

It’s worth noting also that the customized implementations actually got less traffic than the standard ones. For the on-page code, this is within the margin of error, but for Google Tag Manager, there’s another reason — because I used unfiltered profiles for the comparison, there’s a lot of bot spam in the main profile, which primarily masquerades as Internet Explorer. Our main profile is by far the most spammed, and also acting as the baseline here, so the difference between on-page code and Google Tag Manager is probably somewhat larger than what I’m reporting.

I also split the data by mobile, out of curiosity:

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Desktop

100.00%

98.31%

100.97%

100.89%

93.47%

Mobile

100.00%

97.00%

103.78%

100.42%

89.87%

Tablet

100.00%

97.68%

104.20%

102.43%

88.13%

The further takeaway here seems to be that mobile browsers, like Internet Explorer, can struggle with Google Tag Manager.

Lost data due to GTM: 1–5%

Google Tag Manager seems to cost you a varying amount depending on what make-up of browsers and devices use your site. On Distilled.net, the difference is around 1.7%; however, we have an unusually desktop-heavy and tech-savvy audience (not much Internet Explorer!). Depending on vertical, this could easily swell to the 5% range.

Lost data due to misplaced on-page code: ~10%

On Teflsearch.com, the impact of misplaced on-page code was around 7.5%, vs Google Tag Manager. Keeping in mind that Google Tag Manager itself underreports, the total loss could easily be in the 10% range.

Bonus round: Missing data from channels

I’ve focused above on areas where you might be missing data altogether. However, there are also lots of ways in which data can be misrepresented, or detail can be missing. I’ll cover these more briefly, but the main issues are dark traffic and attribution.

Dark traffic

Dark traffic is direct traffic that didn’t really come via direct — which is generally becoming more and more common. Typical causes are:

Untagged campaigns in email

Untagged campaigns in apps (especially Facebook, Twitter, etc.)

Misrepresented organic

Data sent from botched tracking implementations (which can also appear as self-referrals)

It’s also worth noting the trend towards genuinely direct traffic that would historically have been organic. For example, due to increasingly sophisticated browser autocompletes, cross-device history, and so on, people end up “typing” a URL that they’d have searched for historically.

Attribution

I’ve written about this in more detail here, but in general, a session in Google Analytics (and any other platform) is a fairly arbitrary construct — you might think it’s obvious how a group of hits should be grouped into one or more sessions, but in fact, the process relies on a number of fairly questionable assumptions. In particular, it’s worth noting that Google Analytics generally attributes direct traffic (including dark traffic) to the previous non-direct source, if one exists.

Discussion

I was quite surprised by some of my own findings when researching this post, but I’m sure I didn’t get everything. Can you think of any other ways in which data can end up missing from analytics?

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[maryhare96]

How Much Data Is Missing from Analytics? And Other Analytics Black Holes

Posted by Tom.Capper

If you’ve ever compared two analytics implementations on the same site, or compared your analytics with what your business is reporting in sales, you’ve probably noticed that things don’t always match up. In this post, I’ll explain why data is missing from your web analytics platforms and how large the impact could be. Some of the issues I cover are actually quite easily addressed, and have a decent impact on traffic — there’s never been an easier way to hit your quarterly targets. ;)

I’m going to focus on GA (Google Analytics), as it's the most commonly used provider, but most on-page analytics platforms have the same issues. Platforms that rely on server logs do avoid some issues but are fairly rare, so I won’t cover them in any depth.

Side note: Our test setup (multiple trackers & customized GA)

On Distilled.net, we have a standard Google Analytics property running from an HTML tag in GTM (Google Tag Manager). In addition, for the last two years, I’ve been running three extra concurrent Google Analytics implementations, designed to measure discrepancies between different configurations.

(If you’re just interested in my findings, you can skip this section, but if you want to hear more about the methodology, continue reading. Similarly, don’t worry if you don’t understand some of the detail here — the results are easier to follow.)

Two of these extra implementations — one in Google Tag Manager and one on page — run locally hosted, renamed copies of the Google Analytics JavaScript file (e.g. www.distilled.net/static/js/au3.js, instead of www.google-analytics.com/analytics.js) to make them harder to spot for ad blockers. I also used renamed JavaScript functions (“tcap” and “Buffoon,” rather than the standard “ga”) and renamed trackers (“FredTheUnblockable” and “AlbertTheImmutable”) to avoid having duplicate trackers (which can often cause issues).

This was originally inspired by 2016-era best practice on how to get your Google Analytics setup past ad blockers. I can’t find the original article now, but you can see a very similar one from 2017 here.

Lastly, we have (“DianaTheIndefatigable”), which just has a renamed tracker, but uses the standard code otherwise and is implemented on-page. This is to complete the set of all combinations of modified and unmodified GTM and on-page trackers.

Two of Distilled’s modified on-page trackers, as seen on https://www.distilled.net/

Overall, this table summarizes our setups:

Tracker

Renamed function?

GTM or on-page?

Locally hosted JavaScript file?

Default

No

GTM HTML tag

No

FredTheUnblockable

Yes - “tcap”

GTM HTML tag

Yes

AlbertTheImmutable

Yes - “buffoon”

On page

Yes

DianaTheIndefatigable

No

On page

No

I tested their functionality in various browser/ad-block environments by watching for the pageviews appearing in browser developer tools:

Reason 1: Ad Blockers

Ad blockers, primarily as browser extensions, have been growing in popularity for some time now. Primarily this has been to do with users looking for better performance and UX on ad-laden sites, but in recent years an increased emphasis on privacy has also crept in, hence the possibility of analytics blocking.

Effect of ad blockers

Some ad blockers block web analytics platforms by default, others can be configured to do so. I tested Distilled’s site with Adblock Plus and uBlock Origin, two of the most popular ad-blocking desktop browser addons, but it’s worth noting that ad blockers are increasingly prevalent on smartphones, too.

Here’s how Distilled’s setups fared:

(All numbers shown are from April 2018)

Setup

Vs. Adblock

Vs. Adblock with “EasyPrivacy” enabled

Vs. uBlock Origin

GTM

Pass

Fail

Fail

On page

Pass

Fail

Fail

GTM + renamed script & function

Pass

Fail

Fail

On page + renamed script & function

Pass

Fail

Fail

Seems like those tweaked setups didn’t do much!

Lost data due to ad blockers: ~10%

Ad blocker usage can be in the 15–25% range depending on region, but many of these installs will be default setups of AdBlock Plus, which as we’ve seen above, does not block tracking. Estimates of AdBlock Plus’s market share among ad blockers vary from 50–70%, with more recent reports tending more towards the former. So, if we assume that at most 50% of installed ad blockers block analytics, that leaves your exposure at around 10%.

Reason 2: Browser “do not track”

This is another privacy motivated feature, this time of browsers themselves. You can enable it in the settings of most current browsers. It’s not compulsory for sites or platforms to obey the “do not track” request, but Firefox offers a stronger feature under the same set of options, which I decided to test as well.

Effect of “do not track”

Most browsers now offer the option to send a “Do not track” message. I tested the latest releases of Firefox & Chrome for Windows 10.

Setup

Chrome “do not track”

Firefox “do not track”

Firefox “tracking protection”

GTM

Pass

Pass

Fail

On page

Pass

Pass

Fail

GTM + renamed script & function

Pass

Pass

Fail

On page + renamed script & function

Pass

Pass

Fail

Again, it doesn’t seem that the tweaked setups are doing much work for us here.

Lost data due to “do not track”: <1%

Only Firefox Quantum’s “Tracking Protection,” introduced in February, had any effect on our trackers. Firefox has a 5% market share, but Tracking Protection is not enabled by default. The launch of this feature had no effect on the trend for Firefox traffic on Distilled.net.

Reason 3: Filters

It’s a bit of an obvious one, but filters you’ve set up in your analytics might intentionally or unintentionally reduce your reported traffic levels.

For example, a filter excluding certain niche screen resolutions that you believe to be mostly bots, or internal traffic, will obviously cause your setup to underreport slightly.

Lost data due to filters: ???

Impact is hard to estimate, as setup will obviously vary on a site-by site-basis. I do recommend having a duplicate, unfiltered “master” view in case you realize too late you’ve lost something you didn’t intend to.

Reason 4: GTM vs. on-page vs. misplaced on-page

Google Tag Manager has become an increasingly popular way of implementing analytics in recent years, due to its increased flexibility and the ease of making changes. However, I’ve long noticed that it can tend to underreport vs. on-page setups.

I was also curious about what would happen if you didn’t follow Google’s guidelines in setting up on-page code.

By combining my numbers with numbers from my colleague Dom Woodman’s site (you’re welcome for the link, Dom), which happens to use a Drupal analytics add-on as well as GTM, I was able to see the difference between Google Tag Manager and misplaced on-page code (right at the bottom of the <body> tag) I then weighted this against my own Google Tag Manager data to get an overall picture of all 5 setups.

Effect of GTM and misplaced on-page code

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Chrome

100.00%

98.75%

100.77%

99.80%

94.75%

Safari

100.00%

99.42%

100.55%

102.08%

82.69%

Firefox

100.00%

99.71%

101.16%

101.45%

90.68%

Internet Explorer

100.00%

80.06%

112.31%

113.37%

77.18%

There are a few main takeaways here:

On-page code generally reports more traffic than GTM

Modified code is generally within a margin of error, apart from modified GTM code on Internet Explorer (see note below)

Misplaced analytics code will cost you up to a third of your traffic vs. properly implemented on-page code, depending on browser (!)

The customized setups, which are designed to get more traffic by evading ad blockers, are doing nothing of the sort.

It’s worth noting also that the customized implementations actually got less traffic than the standard ones. For the on-page code, this is within the margin of error, but for Google Tag Manager, there’s another reason — because I used unfiltered profiles for the comparison, there’s a lot of bot spam in the main profile, which primarily masquerades as Internet Explorer. Our main profile is by far the most spammed, and also acting as the baseline here, so the difference between on-page code and Google Tag Manager is probably somewhat larger than what I’m reporting.

I also split the data by mobile, out of curiosity:

Traffic as a percentage of baseline (standard Google Tag Manager implementation):

Google Tag Manager

Modified & Google Tag Manager

On-Page Code In <head>

Modified & On-Page Code In <head>

On-Page Code Misplaced In <Body>

Desktop

100.00%

98.31%

100.97%

100.89%

93.47%

Mobile

100.00%

97.00%

103.78%

100.42%

89.87%

Tablet

100.00%

97.68%

104.20%

102.43%

88.13%

The further takeaway here seems to be that mobile browsers, like Internet Explorer, can struggle with Google Tag Manager.

Lost data due to GTM: 1–5%

Google Tag Manager seems to cost you a varying amount depending on what make-up of browsers and devices use your site. On Distilled.net, the difference is around 1.7%; however, we have an unusually desktop-heavy and tech-savvy audience (not much Internet Explorer!). Depending on vertical, this could easily swell to the 5% range.

Lost data due to misplaced on-page code: ~10%

On Teflsearch.com, the impact of misplaced on-page code was around 7.5%, vs Google Tag Manager. Keeping in mind that Google Tag Manager itself underreports, the total loss could easily be in the 10% range.

Bonus round: Missing data from channels

I’ve focused above on areas where you might be missing data altogether. However, there are also lots of ways in which data can be misrepresented, or detail can be missing. I’ll cover these more briefly, but the main issues are dark traffic and attribution.

Dark traffic

Dark traffic is direct traffic that didn’t really come via direct — which is generally becoming more and more common. Typical causes are:

Untagged campaigns in email

Untagged campaigns in apps (especially Facebook, Twitter, etc.)

Misrepresented organic

Data sent from botched tracking implementations (which can also appear as self-referrals)

It’s also worth noting the trend towards genuinely direct traffic that would historically have been organic. For example, due to increasingly sophisticated browser autocompletes, cross-device history, and so on, people end up “typing” a URL that they’d have searched for historically.

Attribution

I’ve written about this in more detail here, but in general, a session in Google Analytics (and any other platform) is a fairly arbitrary construct — you might think it’s obvious how a group of hits should be grouped into one or more sessions, but in fact, the process relies on a number of fairly questionable assumptions. In particular, it’s worth noting that Google Analytics generally attributes direct traffic (including dark traffic) to the previous non-direct source, if one exists.

Discussion

I was quite surprised by some of my own findings when researching this post, but I’m sure I didn’t get everything. Can you think of any other ways in which data can end up missing from analytics?

Sign up for The Moz Top 10, a semimonthly mailer updating you on the top ten hottest pieces of SEO news, tips, and rad links uncovered by the Moz team. Think of it as your exclusive digest of stuff you don't have time to hunt down but want to read!

https://ift.tt/2LCPWKo