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Learn How to Boost 10X Conversion Rate with Master's AB Split Testing Tutorial

Learn How to Boost Conversion Rate with Master's AB Split Testing Tutorial

Marketing campaigns are expensive and time consuming, so if you start a marketing campaign you should be sure that it will definitely bring you results. This is why many companies spend days and even months in testing before they roll out any campaigns.

PPC ads in general are effective for driving highly targeted traffic to a particular landing page where most conversion efforts occur. However, not all landing pages are created equal. A particular landing page variation may generate higher conversion rates than another page promoting the same product or service. Changes in certain page elements can be a big factor in the effectiveness of the page for generating conversions and it’s up to the business owner or the digital marketer to select which elements to use.

To validate which of these variations prove effective, A/B split testing can be conducted as part of the overall optimization process to improve the performance of your PPC campaign.

WHAT IS A/B TESTING

A/B testing (also known as split testing or bucket testing) is a method of comparing two versions of a webpage or app against each other to determine which one performs better. AB testing is essentially an experiment where two or more variants of a page are shown to users at random, and statistical analysis is used to determine which variation performs better for a given conversion goal.

Running an AB test that directly compares a variation against a current experience lets you ask focused questions about changes to your website or app, and then collect data about the impact of that change. Testing takes the guesswork out of website optimization and enables data-informed decisions that shift business conversations from "we think" to "we know." By measuring the impact that changes have on your metrics, you can ensure that every change produces positive results.

HOW A/B TESTING WORKS

In an A/B test, you take a webpage or app screen and modify it to create a second version of the same page. This change can be as simple as a single headline or button, or be a complete redesign of the page. Then, half of your traffic is shown the original version of the page (known as the control) and half are shown the modified version of the page (the variation).

As visitors are served either the control or variation, their engagement with each experience is measured and collected in an analytics dashboard and analyzed through a statistical engine. You can then determine whether changing the experience had a positive, negative, or no effect on visitor behavior. MAIN USES OF A/B SPLIT TESTING ?

Many digital marketers believe that A/B split testing is basically just a tool for optimization, which in this particular case involves PPC ads and landing pages. Contrary to this belief, A/B split testing can be used not only for optimization but also for validation, which is important during the initial stages of a particular PPC campaign.

⦁ Using A/B testing for Optimization

A/B split testing is primarily used for the optimization of an ongoing PPC campaign, particularly in testing which particular variation in page element likes the headlines, image, layout, form, call-to-action and other factors that will affect conversion rates. This tool is intended to increase known conversion rates of a PPC campaign after it has already been rolled out for a particular length of time.

⦁ Using A/B testing for Validation

A/B testing is good for optimizing an already ongoing PPC campaign. However, it is not the only use where you can apply A/B split testing. You can also use it to validate which particular variation will be the best one to use for your campaign before you even roll out. A good example is when you want to roll out an ebook or a whitepaper as part of your PPC campaign. You can test different variations of these materials and validate which one will generate the best results – and use it for the main campaign.

A/B TESTING PROCESS

The following is an A/B testing framework you can use to start running tests:

⦁ Collect Data: Your analytics will often provide insight into where you can begin optimizing. It helps to begin with high traffic areas of your site or app, as that will allow you to gather data faster. Look for pages with low conversion rates or high drop-off rates that can be improved.

⦁ Identify Goals: Your conversion goals are the metrics that you are using to determine whether or not the variation is more successful than the original version. Goals can be anything from clicking a button or link to product purchases and e-mail signups.

⦁ Generate Hypothesis: Once you've identified a goal you can begin generating A/B testing ideas and hypotheses for why you think they will be better than the current version. Once you have a list of ideas, prioritize them in terms of expected impact and difficulty of implementation.

⦁ Create Variations: Using your A/B testing software (like Optimize), make the desired changes to an element of your website or mobile app experience. This might be changing the color of a button, swapping the order of elements on the page, hiding navigation elements, or something entirely custom. Many leading A/B testing tools have a visual editor that will make these changes easy. Make sure to QA your experiment to make sure it works as expected.

⦁ Run Experiment: Kick off your experiment and wait for visitors to participate! At this point, visitors to your site or app will be randomly assigned to either the control or variation of your experience. Their interaction with each experience is measured, counted, and compared to determine how each performs.

⦁ Analyze Results: Once your experiment is complete, it's time to analyze the results. Your A/B testing software will present the data from the experiment and show you the difference between how the two versions of your page performed, and whether there is a statistically significant difference.

IMPACT OF A/B SPLIT TESTING ON SEO

A/B split testing is important if you want to validate which particular PPC campaign to use and optimize it to get the best results in terms of higher conversion. However, many digital marketers are afraid of the negative implications A/B split testing may have on the main website’s SEO. The fear emanated from the speculations that A/B testing may affect rankings because of the variants in content.

“We’ve gotten several questions recently about whether website testing—such as A/B or multivariate testing—affects a site’s performance in search results. We’re glad you’re asking, because we’re glad you’re testing! A/B and multivariate testing are great ways of making sure that what you’re offering really appeals to your users.”

– Google Webmaster Central Blog

The statement about is Google’s clarifications that they actually welcome A/B and other testing methods as long as the processes follow the guidelines they’ve outlined in their central blog. These guidelines are outlined and explained in brief below:

⦁ Do Not Perform Content CloakingIt is against Google’s guidelines if your website shows a different content to their crawling Googlebots than what humans may actually see from the site. Original content should always be shown to the user-agent “Googlebot” as manipulating this may result in your penalization and removal from search results

⦁ Use the link attribute rel=“canonical”

This is applicable when you are running A/B split testing experiments using multiple URLs. This link attribute will tell the search engines that the preferred version of a particular page is the original and not the alternate URL used for testing. The attribute will tell the search engine that variations should be grouped together as merely duplicates, with the original page marked as the canonical URL. This is different and better than using a noindex meta tag as you would of course want Googlebots to crawl and index your home page.

⦁ Set only a specific duration for you’re A/B split testing

Gather only enough data for you’re A/B split testing and specify the length of time you will need to run the experiment. Once you’ve identified how you can optimize your website and landing pages, it would be best to conclude your test and remove alternate URLs, markups, scripts and other elements you have used during the experiment

So Split testing is one of the fastest growing methods of boosting the value of your marketing campaign, as well learning the more effective ways of marketing your products. So, what if we tell you that we can save you years of testing and acquiring experience, but instead provide you with the hacks to actually boost your marketing skills right now?

We have done the work for you, we have toiled through thousands of different split tests across different segments and have actually created this

Split Testing Marketing Course

that can help you skip ahead directly to learning exactly how you can design and deploy the most efficient Split Tests and boost your conversions.

This course has distilled one hundred tweeks and hacks that can help you immediately boost your conversion rates. In a series of 6 training videos, you will learn not only how to work with sales copies but also sales videos, webinars and even Facebook advertising.

No more guesswork or even multiple testing practices, we'll tell you exactly what works and what doesn't. We've got the formula for marketing success in our hands and we want to share it with you.

What you'll find in this course:

⦁ How to apply our research into your marketing campaigns and sales materials for maximum results ⦁ Simple tweaks to score higher conversions and EPCs (earnings per click) ⦁ Little known tweaks and 'hacks' to make your sales video pull in the numbers on engagement and conversions ⦁ High engagement formula included as well (how long to run a webinar ideally, the structure, etc.) ⦁ How to get more opens and clicks ⦁ How to get more views and shares for your Facebook ads

So, what are you waiting for? Enroll now and learn the secrets of taking your marketing strategies to the next level!

#digitalmarketing #ab testing #google marketing #ppc marketing #sem #seo #adwords remarketing

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