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#i think it's a lot more useful for predictions than fixating on random details
ineffably-human · 1 year
Text
I don't think the Shadows writers forget about major-ass plot points like the Van Helsing thing or the entire season's worth of Baby Colin. (or the djinn, for that matter.) these things just come up when it's useful to the story for them to come up.
for instance: Baby Colin's been something they never even mentioned all season. episode 8, we need reasons every single character thinks that Laszlo might be upset that are actually about their own self-absorbed vibes (because that's how everyone in the house is). so Nadja thinks it's because of the hex that's consumed her life (while visibly doing nothing to her because it doesn't exist), Nandor thinks it's because of what a great place he's in emotionally (while constantly, obsessively thinking about Guillermo), Guillermo thinks it's about the failed experiments.
and because we don't have anything for Colin, who tries to stay out of everyone's craziness, he starts remembering the years he spent as a baby - and that's so we, as the audience, will wonder if that's why Laszlo is upset.
and in the end, Laszlo isn't upset about any of those things! he's just having a huge hyperfixation moment, because that's a much funnier joke. but now we've brought Baby Colin back up and maybe we can play with that for any future episodes, because now was the organic time to mention it again, without forcing Laszlo to be paralyzed with depression the whole season.
What We Do In The Shadows: Sometimes It Really Is That Deep
but also What We Do In The Shadows: Sometimes It's Just That Stupid
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blysse-and-blunder · 2 years
Text
 in lieu of a commonplace book
10pm sunday, jan 29, 2023
your gentle blogger has entered her next decade of life, thank you to @dying-suffering-french-stalkers and @redstar-winterorbit for the good birthday wishes last week!
reading not a ton if i'm honest, i've been deluged with gift books and library loans while at the same time crashing back into the semester, and the overall effect has been, uh, to freeze my recreational reading a bit. stuck trying to finish things like my audiobook of through the whispering door and ebook of maybe you should talk to somebody (have i talked about this one? it's a memoir of a therapist and reading it is like reading an episode of the gossip podcast, but i can also tell it's giving me occasional useful ideas and perspective on things to think about or ask for in therapy. but i can only take so much of it at once). the gift book i'm most into right now it lindsey ellis' axiom's end, which is a first-contact, aliens are real and the government has been hiding them scifi-- it's quick and readable, lindsey does a great job for a first novel, and i'm loving the alternate-history flavor of it being set in the Bush era and the southern california details i actually appreciate now. also the way the aliens are described, i love the design of them. beautiful and terrifying. but i haven't made progress in a few days.
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through the whispering door is perplexing me right now, in that the gentle romance has developed pleasingly (predictably), but there's been a lot of talk about the main character 'having changed' and 'not being the same as he was when he arrived' and i can't actually. point to why or where that happened. this is part of the problem with me and audiobooks, i think, because i don't care enough to go back and re-listen to the parts where i tuned out.... there's been a new heightening of the stakes now that there's a time-limit, and i always like the flavor of an eldritch stag character.
EDIT: finished the monster baru cormorant, still recovering, immediately checked the third one out of the library though the psychic damage this series does to me without warning (dear seth: i'm taking away the word 'clotted' from your lexicon for a bit. also ‘lobotomy’.) is hard to rectify with how smart and good some of the new narrative details are. the introduction of ‘trim’ and its associated reliance on / trust in other people, to a story where the main character's stated weakness is thinking about things from others' perspectives? or anticipating others' reactions? chef's kiss. and the navy full of rugged, determined, salt-weathered women is just very good to me, personally. aminata my incredibly violent beloved. the end of this book was- devastating. not in the same way as the last one: this time i have the kind of fascinated-horrified-sickened-fixated feeling that i get about horror stuff sometimes, and i’d say body horror is what i expect from book three.
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watching i got unlucky with weather-based flight cancellations last week, and spending a night in a random detroit hotel room created a great opportunity to check out my university's criterion collection access. for some reason i decided that this was the right moment to experience wong kar wai's in the mood for love (2000), which i have since finished in slightly calmer circumstances. despite knowing that tony leung and maggie cheung were both active in the 90s i somehow totally thought that this movie was like. actually a historic film and not a period piece? probably because of how much the visuals / how it’s shot and colored / the overall design feels so classic, feels like old school film in the best possible way. having now read the wikipedia page for this film i can tell i missed a lot of the actual plot, or rather, thought that there was more experimental / nonlinear story-telling going on than there might actually have been-- but that’s okay, it just means i’ll have to watch it again.
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listening i don’t remember when this song first popped up in my spot ify, possibly on a discover weekly playlist a while ago? but it landed for me last week, somehow brand new and meaningful as i was contemplating the musical direction of my next playlist. listening to it with better headphones revealed lots of nice layers, depth and harmony, i like that bass throb under the chorus, it’s produced well and rewards paying attention to the extra stuff-- the contrary motion of the background vocal line in the opening to the chorus is nice.
something something i will get up regardless. currently repeating to myself, all you gotta do now is walk.
playing had the pleasure of hanging out with my Dnd friends on my birthday last week and playing a whole new style of game with them! Y introduced us to gloom, which is very Edward Gorey-core and therefore was delightful, and got our game-design nerds all excited about the cards themselves, and then K skunked us all at anomia. the adrenaline in this one is addictive? it is somehow so fun and yet so infuriating, and I have yet to regret suggesting it to a group or party.
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making cleaned my room finally (somewhat) and have a stack of mail to send and cards to answer, now with the help of the beautiful fountain pen my roommates gave me for my birthday! It’s one of these, and while I can try to promise not to become a fountain pen nerd, time will tell…
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working on this award letter for a prof is somehow the hardest thing to just fucking finish. I think because I want it to be better than just okay, and am worried that it’ll counteract its own message if it’s not? But also—I have palaeography homework now! and the abstract of a talk to finish, and that talk + associated chapter to outline! not to mention finishing reading and commenting on a friend’s chapters! taking it slow last week was nice and probably needed, but fuck.
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wearingmywings · 6 years
Text
Destiel Meta - an outsider’s perspective
I’ve been reading meta for about a year, but now I wanted to add my own post regarding it.
I don’t really see things when I first watch episodes, I don’t get mirrors or parallels or pay attention to background details like wallpaper or neon signs or anything like that. I’m not good at analyzing things or interpreting it, not in literature nor film, I don’t do something in this area professionally or studied it. 
However, there are some things that jumped out so much that even I thought “Hey, that’s something!”.
Part 1: Mirrors
Seriously, mirrors? You’re telling me that it’s a known method to present mirrors to characters, that they can be used in subtle or totally obvious forms, and they can tell you a lot about the character that’s being mirrored just by existing? Wow that’s so cool!
14x300: In the first scenes when my friend yelled “Look! they look like Dean and Cas!”, I wasn’t 100% sure if that’s what was going on, but oh boi at the end of the episode it was crystal fucking clear. Three people next to each other, the one on the right taller than the others, one is wearing a jacket resembling a trench coat, one is wearing plaid. Trenchcoatjacket and Plaid are holding hands.
We noticed Plaid’s crush on Trenchcoatjacket the whole episode, it was so obvious! Hm, what else was there in resemblance? I remember the taller kid was pretty nerdy, and Plaid stole the Impala at one point, so it’s pretty clear we have Sam and Dean here, which leaves Cas for the last person, and it fits so well! Thats awesome!!
Apart from “Lebanon”, the episode ‘Mint Condition’ basically taught me how they use mirrors and that I should pay attention to them right now. They pointed out who was Sam and Dean, then resumed with the plot and I sat there thinking “Oh!”.
My friend explained to me how the ghost of that episode relates to John Winchester, and honestly if you follow the train of thought about mirrors that the episode presented to you, it’s pretty easy to get there.
Dreamhunter: The confirmed ship with two girls, ah yes! Again, I don‘t really pick up on visual cues or background stuff, but when Kaia said to Claire “I’ll go with you,” I had flashbacks to the season 11 finale immediately. I mean, using the exact same dilagoue? But alright, maybe they’re gonna keep playing it as a cute subtextual crush or how you call it, because neither of them says “You’re my crush”, so-
Oh, wait, Kaia was also stabbed in front of Claire who screamed “Noo!!”, that’s another striking resemblance. Hm.
Oh, Dreamhunter is confirmed to be a couple thing? Neat! So does that mean all the DeanCas stuff is romantic? Because y’all used the same dialogue and plot.
Part 2: Dean’s pining (season 11)
To be fully honest here, I didn’t understand season 11. At all. I didn’t get the whole Amara thing, why was everyone talking about pining? Dean told us that it wasn’t about desire with him and Amara, just a weird fixation, but still, the lady in the senior home told Dean that he “was pining for somebody else”. That makes no sense!
Unless it’s true? Dean didn’t pine for Amara, he tells us that, but everyone’s still talking about pining, therefore the topic of pining is important. Dean x Amara wasn’t romantic, that’s clear from what Dean told us and how he behaved, so no pining.
The only person left he could pine for is Cas. The dude who let in Lucifer, who Dean’s worried about, who Amara touches and she knows where Dean is? That’s..interesting. I’m still kinda confused, but some things are clearer now. No romance between Dean & Amara, but pining is still a theme, and only Cas makes sense. Got it.
Part 3: Cas’ endgame as being human
I wanted to include this because I’ve had this headcanon for years, then saw the meta community talk about it, and honestly there’s one scene to watch and it’d be clear that Cas wants to be human.
“We need grace-” “He can have mine”. 14x08
Alright dude, you’re so eager and ready to throw away your grace? Okidoki.
To go back in time, everyone always had these TED talks about how Cas loves humanity and loves humans and human things, that he feels stuff (season 4 yall, it’s been a while), that he compliments Hannah with things that “are human”. He doesn’t get along with other angels because they’re different than him, or they don’t understand his love and devotion for humans. He spends pretty much all his time on earth, around humans, because he loves them, and one in particular.
To quote Metatron, “He’s in love with humanity”. Do I need to add more? No? Fantastic, because this post is long enough already.
Part 4: Random things in no particular order
Episode 12x12, because come on. Some people took the gifs of Cas’ deathbed confession and connected them to the shots before, showing you where everyone’s standing, who Cas is looking at, and it’s so bloody clear. Don’t get me started on the singular vs plural “i love you” because I literally don’t have to, it’s right there.
“I could go with you”- season 11 finale. Cas, ready to die to accompany Dean on the suicide mission to save the world. He wants to ease Dean’s fear and be there for him until the very end, without hesitation. Castiel really fucking loves Dean Winchester. Wow.
That’s it I think? Those are the top things that jumped into my face when I watch the show, things I didn’t have to read other people’s thoughts on to understand what’s happening. :)
To finish this up I want to say something about meta writers. I didn’t start out reading meta, I didn’t really care for details and background stuff and took the show as I saw it, which is why I shipped Destiel immediately because there were enough things so blatantly obvious to me that I just had to. Then I found @tinkdw, then @bluestar86, @dotthings, @occamshipper, @postmodernmulticoloredcloak and all the other bloody amazing meta writers, and boom! A whole new world!
I started a series rewatch, read the posts for the episodes or seasons, paid more attention and there was so much to see and notice! It gave me joy in watching SPN in a time where I was kind of burned out because I had just discovered the bad side of the fandom and was a bit hopeless, for my OTP and the show itself. It gave me friends, and interesting conversations, but more importantly: These people helped me be realistic about episodes, upcoming episodes and PR stuff. “PR is not showrunning” was a strange concept to me before they showed me what it meant, and I vividly remember being in tears before all this after some PR material promised amazing things but failed to deliver.
These people are so good at predicting what’s going to happen because they read the fine print and understand it, pack it up and show it to us who either can’t read the fine print or dont notice it. They help fans to control (?) their expectations, to soften blind excitement over promo shots or interviews with people who have either no clue what they’re talking about (Jensen bby, i love you but what are you even saying?) or are purposefully exaggerating things.
They saved me from so much disappointment, they improved my fandom experience and changed my feelings for the show and how I watch it. There are so many interesting things to discover, things that confirm theories and explain plot points. I haven’t been disappointed in a new episode because of PR or rumors since I’ve met them, except ep 300 but that’s...a whole other thing. They were right about that too, though, and I didn’t listen. Catch me crying at four am because of it.
I love those people immensely, and I’m so thankful for them. They take the time to write all these essays about the show, all you have to do is read them.
A toast to meta writers! Consider this your personal love letter.
Kisses,
Jana
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tradevendors · 7 years
Text
The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
Posted by willcritchlow
Digital marketing is measurable.
It’s probably the single most common claim everyone hears about digital, and I can’t count the number of times I’ve seen conference speakers talk about it (heck, I’ve even done it myself).
I mean, look at those offline dinosaurs, the argument goes. They all know that half their spend is wasted — they just don’t know which half.
Maybe the joke’s on us digital marketers though, who garnered only 41% of global ad spend even in 2017 after years of strong growth.
Unfortunately, while we were geeking out about attribution models and cross-device tracking, we were accidentally triggering a common human cognitive bias that kept us anchored on small amounts, leaving buckets of money on the table and fundamentally reducing our impact and access to the C-suite.
And what’s worse is that we have convinced ourselves that it’s a critical part of what makes digital marketing great. The simplest way to see this is to realize that, for most of us, I very much doubt that if you removed all our measurement ability we’d reduce our digital marketing investment to nothing.
In truth, of course, we’re nowhere close to measuring all the benefits of most of the things we do. We certainly track the last clicks, and we’re not bad at tracking any clicks on the path to conversion on the same device, but we generally suck at capturing:
Anything that happens on a different device
Brand awareness impacts that lead to much later improvements in conversion rate, average order value, or lifetime value
Benefits of visibility or impressions that aren’t clicked
Brand affinity generally
The cognitive bias that leads us astray
All of this means that the returns we report on tend to be just the most direct returns. This should be fine — it’s just a floor on the true value (“this activity has generated at least this much value for the brand”) — but the “anchoring” cognitive bias means that it messes with our minds and our clients’ minds. Anchoring is the process whereby we fixate on the first number we hear and subsequently estimate unknowns closer to the anchoring number than we should. Famous experiments have shown that even showing people a totally random number can drag their subsequent estimates up or down.
So even if the true value of our activity was 10x the measured value, we’d be stuck on estimating the true value as very close to the single concrete, exact number we heard along the way.
This tends to result in the measured value being seen as a ceiling on the true value. Other biases like the availability heuristic (which results in us overstating the likelihood of things that are easy to remember) tend to mean that we tend to want to factor in obvious ways that the direct value measurement could be overstating things, and leave to one side all the unmeasured extra value.
The mistake became a really big one because fortunately/unfortunately, the measured return in digital has often been enough to justify at least a reasonable level of the activity. If it hadn’t been (think the vanishingly small number of people who see a billboard and immediately buy a car within the next week when they weren’t otherwise going to do so) we’d have been forced to talk more about the other benefits. But we weren’t. So we lazily talked about the measured value, and about the measurability as a benefit and a differentiator.
The threats of relying on exact measurement
Not only do we leave a whole load of credit (read: cash) on the table, but it also leads to threats to measurability being seen as existential threats to digital marketing activity as a whole. We know that there are growing threats to measuring accurately, including regulatory, technological, and user-behavior shifts:
GDPR and other privacy regulations are limiting what we are allowed to do (and, as platforms catch up, what we can do)
Privacy features are being included in more products, added on by savvy consumers, or simply being set to be on by default more often, with even the biggest company in the world touting privacy as a core differentiator
Users continue to increase the extent to which they research and buy across multiple devices
Compared to early in Google’s rise, the lack of keyword-level analytics data and the rise of (not provided) means that we have far less visibility into the details than we used to when the narrative of measurability was being written
Now, imagine that the combination of these trends meant that you lost 100% of your analytics and data. Would it mean that your leads stopped? Would you immediately turn your website off? Stop marketing?
I suggest that the answer to all of that is “no.” There’s a ton of value to digital marketing beyond the ability to track specific interactions.
We’re obviously not going to see our measurable insights disappear to zero, but for all the reasons I outlined above, it’s worth thinking about all the ways that our activities add value, how that value manifests, and some ways of proving it exists even if you can’t measure it.
How should we talk about value?
There are two pieces to the brand value puzzle:
Figuring out the value of increasing brand awareness or affinity
Understanding how our digital activities are changing said awareness or affinity
There’s obviously a lot of research into brand valuations generally, and while it’s outside the scope of this piece to think about total brand value, it’s worth noting that some methodologies place as much as 75% of the enterprise value of even some large companies in the value of their brands:
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My colleague Tom Capper has written about a variety of ways to measure changes in brand awareness, which attacks a good chunk of the second challenge. But challenge #1 remains: how do we figure out what it’s worth to carry out some marketing activity that changes brand awareness or affinity?
In a recent post, I discussed different ways of building marketing models and one of the methodologies I described might be useful for this – namely so-called “top-down” modelling which I defined as being about percentages and trends (as opposed to raw numbers and units of production).
The top-down approach
I’ve come up with two possible ways of modelling brand value in a transactional sense:
1. The Sherlock approach
“When you have eliminated the impossible, whatever remains, however improbable, must be the truth.“ – Sherlock Holmes
The outline would be to take the total new revenue acquired in a period. Subtract from this any elements that can be attributed to specific acquisition channels; whatever remains must be brand. If this is in any way stable or predictable over multiple periods, you can use it as a baseline value from which to apply the methodologies outlined above for measuring changes in brand awareness and affinity.
2. Aggressive attribution
If you run normal first-touch attribution reports, the limitations of measurement (clearing cookies, multiple devices etc) mean that you will show first-touch revenue that seems somewhat implausible (e.g. email; email surely can’t be a first-touch source — how did they get on your email list in the first place?):
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Click for a larger version
In this screenshot we see that although first-touch dramatically reduces the influence of direct, for instance, it still accounts for more than 15% of new revenue.
The aggressive attribution model takes total revenue and splits it between the acquisition channels (unbranded search, paid social, referral). A first pass on this would simply split it in the relative proportion to the size of each of those channels, effectively normalizing them, though you could build more sophisticated models.
Note that there is no way of perfectly identifying branded/unbranded organic search since (not provided) and so you’ll have to use a proxy like homepage search vs. non-homepage search.
But fundamentally, the argument here would be that any revenue coming from a “first touch” of:
Branded search
Direct
Organic social
Email
…was actually acquired previously via one of the acquisition channels and so we attempt to attribute it to those channels.
Even this under-represents brand value
Both of those methodologies are pretty aggressive — but they might still under-represent brand value. Here are two additional mechanics where brand drives organic search volume in ways I haven’t figured out how to measure yet:
Trusting Amazon to rank
I like reading on the Kindle. If I hear of a book I’d like to read, I’ll often Google the name of the book on its own and trust that Amazon will rank first or second so I can get to the Kindle page to buy it. This is effectively a branded search for Amazon (and if it doesn’t rank, I’ll likely follow up with a [book name amazon] search or head on over to Amazon to search there directly).
But because all I’ve appeared to do is search [book name] on Google and then click through to Amazon, there is nothing to differentiate this from an unbranded search.
Spotting brands you trust in the SERPs
I imagine we all have anecdotal experience of doing this: you do a search and you spot a website you know and trust (or where you have an account) ranking somewhere other than #1 and click on it regardless of position.
One time that I can specifically recall noticing this tendency growing in myself was when I started doing tons more baby-related searches after my first child was born. Up until that point, I had effectively zero brand affinity with anyone in the space, but I quickly grew to rate the content put out by babycentre (babycenter in the US) and I found myself often clicking on their result in position 3 or 4 even when I hadn’t set out to look for them, e.g. in results like this one:
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It was fascinating to me to observe this behavior in myself because I had no real interaction with babycentre outside of search, and yet, by consistently ranking well across tons of long-tail queries and providing consistently good content and user experience I came to know and trust them and click on them even when they were outranked. I find this to be a great example because it is entirely self-contained within organic search. They built a brand effect through organic search and reaped the reward in increased organic search.
I have essentially no ideas on how to measure either of these effects. If you have any bright ideas, do let me know in the comments.
Budgets will come under pressure
My belief is that total digital budgets will continue to grow (especially as TV continues to fragment), but I also believe that individual budgets are going to come under scrutiny and pressure making this kind of thinking increasingly important.
We know that there is going to be pressure on referral traffic from Facebook following the recent news feed announcements, but there is also pressure on trust in Google:
Before the recent news feed changes, slightly misleading stories had implied that Google had lost the top spot as the largest referrer of traffic (whereas in fact this was only briefly true in media)
The growth of the mobile-first card view and richer and richer SERPs has led to declines in outbound CTR in some areas
The increasingly black-box nature of Google’s algorithm and an increasing use of ML make the algorithm increasingly impenetrable and mean that we are having to do more testing on individual sites to understand what works
While I believe that the opportunity is large and still growing (see, for example, this slide showing Google growing as a referrer of traffic even as CTR has declined in some areas), it’s clear that the narrative is going to lead to more challenging conversations and budgets under increased scrutiny.
Can you justify your SEO investment?
What do you say when your CMO asks what you’re getting for your SEO investment?
What do you say when she asks whether the organic search opportunity is tapped out?
I’ll probably explore the answers to both these questions more in another post, but suffice it to say that I do a lot of thinking about these kinds of questions.
The first is why we have built our split-testing platform to make organic SEO investments measurable, quantifiable and accountable.
The second is why I think it’s super important to remember the big picture while the media is running around with hair on fire. Media companies saw Facebook overtake Google as a traffic channel (and then are likely seeing that reverse right now), but most of the web has Google as the largest and growing source of traffic and value.
The reality (from clickstream data) is that it’s really easy to forget how long the long-tail is and how sparse search features and ads are on the extreme long-tail:
Only 3–4% of all searches result in a click on an ad, for example. Google’s incredible (and still growing) business is based on a small subset of commercial searches
Google’s share of all outbound referral traffic across the web is growing (and Facebook’s is shrinking as they increasingly wall off their garden)
The opportunity is for smart brands to capitalize on a growing opportunity while their competitors sink time and money into a social space that is increasingly all about Facebook, and increasingly pay-to-play.
What do you think? Are you having these hard conversations with leadership? How are you measuring your digital brand’s value?
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Text
The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
Posted by willcritchlow
Digital marketing is measurable.
It’s probably the single most common claim everyone hears about digital, and I can’t count the number of times I’ve seen conference speakers talk about it (heck, I’ve even done it myself).
I mean, look at those offline dinosaurs, the argument goes. They all know that half their spend is wasted — they just don’t know which half.
Maybe the joke’s on us digital marketers though, who garnered only 41% of global ad spend even in 2017 after years of strong growth.
Unfortunately, while we were geeking out about attribution models and cross-device tracking, we were accidentally triggering a common human cognitive bias that kept us anchored on small amounts, leaving buckets of money on the table and fundamentally reducing our impact and access to the C-suite.
And what’s worse is that we have convinced ourselves that it’s a critical part of what makes digital marketing great. The simplest way to see this is to realize that, for most of us, I very much doubt that if you removed all our measurement ability we’d reduce our digital marketing investment to nothing.
In truth, of course, we’re nowhere close to measuring all the benefits of most of the things we do. We certainly track the last clicks, and we’re not bad at tracking any clicks on the path to conversion on the same device, but we generally suck at capturing:
Anything that happens on a different device
Brand awareness impacts that lead to much later improvements in conversion rate, average order value, or lifetime value
Benefits of visibility or impressions that aren’t clicked
Brand affinity generally
The cognitive bias that leads us astray
All of this means that the returns we report on tend to be just the most direct returns. This should be fine — it’s just a floor on the true value (“this activity has generated at least this much value for the brand”) — but the “anchoring” cognitive bias means that it messes with our minds and our clients’ minds. Anchoring is the process whereby we fixate on the first number we hear and subsequently estimate unknowns closer to the anchoring number than we should. Famous experiments have shown that even showing people a totally random number can drag their subsequent estimates up or down.
So even if the true value of our activity was 10x the measured value, we’d be stuck on estimating the true value as very close to the single concrete, exact number we heard along the way.
This tends to result in the measured value being seen as a ceiling on the true value. Other biases like the availability heuristic (which results in us overstating the likelihood of things that are easy to remember) tend to mean that we tend to want to factor in obvious ways that the direct value measurement could be overstating things, and leave to one side all the unmeasured extra value.
The mistake became a really big one because fortunately/unfortunately, the measured return in digital has often been enough to justify at least a reasonable level of the activity. If it hadn’t been (think the vanishingly small number of people who see a billboard and immediately buy a car within the next week when they weren’t otherwise going to do so) we’d have been forced to talk more about the other benefits. But we weren’t. So we lazily talked about the measured value, and about the measurability as a benefit and a differentiator.
The threats of relying on exact measurement
Not only do we leave a whole load of credit (read: cash) on the table, but it also leads to threats to measurability being seen as existential threats to digital marketing activity as a whole. We know that there are growing threats to measuring accurately, including regulatory, technological, and user-behavior shifts:
GDPR and other privacy regulations are limiting what we are allowed to do (and, as platforms catch up, what we can do)
Privacy features are being included in more products, added on by savvy consumers, or simply being set to be on by default more often, with even the biggest company in the world touting privacy as a core differentiator
Users continue to increase the extent to which they research and buy across multiple devices
Compared to early in Google’s rise, the lack of keyword-level analytics data and the rise of (not provided) means that we have far less visibility into the details than we used to when the narrative of measurability was being written
Now, imagine that the combination of these trends meant that you lost 100% of your analytics and data. Would it mean that your leads stopped? Would you immediately turn your website off? Stop marketing?
I suggest that the answer to all of that is “no.” There's a ton of value to digital marketing beyond the ability to track specific interactions.
We’re obviously not going to see our measurable insights disappear to zero, but for all the reasons I outlined above, it’s worth thinking about all the ways that our activities add value, how that value manifests, and some ways of proving it exists even if you can’t measure it.
How should we talk about value?
There are two pieces to the brand value puzzle:
Figuring out the value of increasing brand awareness or affinity
Understanding how our digital activities are changing said awareness or affinity
There's obviously a lot of research into brand valuations generally, and while it’s outside the scope of this piece to think about total brand value, it’s worth noting that some methodologies place as much as 75% of the enterprise value of even some large companies in the value of their brands:
Image source
My colleague Tom Capper has written about a variety of ways to measure changes in brand awareness, which attacks a good chunk of the second challenge. But challenge #1 remains: how do we figure out what it’s worth to carry out some marketing activity that changes brand awareness or affinity?
In a recent post, I discussed different ways of building marketing models and one of the methodologies I described might be useful for this - namely so-called “top-down” modelling which I defined as being about percentages and trends (as opposed to raw numbers and units of production).
The top-down approach
I’ve come up with two possible ways of modelling brand value in a transactional sense:
1. The Sherlock approach
“When you have eliminated the impossible, whatever remains, however improbable, must be the truth." - Sherlock Holmes
The outline would be to take the total new revenue acquired in a period. Subtract from this any elements that can be attributed to specific acquisition channels; whatever remains must be brand. If this is in any way stable or predictable over multiple periods, you can use it as a baseline value from which to apply the methodologies outlined above for measuring changes in brand awareness and affinity.
2. Aggressive attribution
If you run normal first-touch attribution reports, the limitations of measurement (clearing cookies, multiple devices etc) mean that you will show first-touch revenue that seems somewhat implausible (e.g. email; email surely can’t be a first-touch source — how did they get on your email list in the first place?):
Click for a larger version
In this screenshot we see that although first-touch dramatically reduces the influence of direct, for instance, it still accounts for more than 15% of new revenue.
The aggressive attribution model takes total revenue and splits it between the acquisition channels (unbranded search, paid social, referral). A first pass on this would simply split it in the relative proportion to the size of each of those channels, effectively normalizing them, though you could build more sophisticated models.
Note that there is no way of perfectly identifying branded/unbranded organic search since (not provided) and so you’ll have to use a proxy like homepage search vs. non-homepage search.
But fundamentally, the argument here would be that any revenue coming from a “first touch” of:
Branded search
Direct
Organic social
Email
...was actually acquired previously via one of the acquisition channels and so we attempt to attribute it to those channels.
Even this under-represents brand value
Both of those methodologies are pretty aggressive — but they might still under-represent brand value. Here are two additional mechanics where brand drives organic search volume in ways I haven’t figured out how to measure yet:
Trusting Amazon to rank
I like reading on the Kindle. If I hear of a book I’d like to read, I’ll often Google the name of the book on its own and trust that Amazon will rank first or second so I can get to the Kindle page to buy it. This is effectively a branded search for Amazon (and if it doesn’t rank, I’ll likely follow up with a [book name amazon] search or head on over to Amazon to search there directly).
But because all I’ve appeared to do is search [book name] on Google and then click through to Amazon, there is nothing to differentiate this from an unbranded search.
Spotting brands you trust in the SERPs
I imagine we all have anecdotal experience of doing this: you do a search and you spot a website you know and trust (or where you have an account) ranking somewhere other than #1 and click on it regardless of position.
One time that I can specifically recall noticing this tendency growing in myself was when I started doing tons more baby-related searches after my first child was born. Up until that point, I had effectively zero brand affinity with anyone in the space, but I quickly grew to rate the content put out by babycentre (babycenter in the US) and I found myself often clicking on their result in position 3 or 4 even when I hadn’t set out to look for them, e.g. in results like this one:
It was fascinating to me to observe this behavior in myself because I had no real interaction with babycentre outside of search, and yet, by consistently ranking well across tons of long-tail queries and providing consistently good content and user experience I came to know and trust them and click on them even when they were outranked. I find this to be a great example because it is entirely self-contained within organic search. They built a brand effect through organic search and reaped the reward in increased organic search.
I have essentially no ideas on how to measure either of these effects. If you have any bright ideas, do let me know in the comments.
Budgets will come under pressure
My belief is that total digital budgets will continue to grow (especially as TV continues to fragment), but I also believe that individual budgets are going to come under scrutiny and pressure making this kind of thinking increasingly important.
We know that there is going to be pressure on referral traffic from Facebook following the recent news feed announcements, but there is also pressure on trust in Google:
Before the recent news feed changes, slightly misleading stories had implied that Google had lost the top spot as the largest referrer of traffic (whereas in fact this was only briefly true in media)
The growth of the mobile-first card view and richer and richer SERPs has led to declines in outbound CTR in some areas
The increasingly black-box nature of Google’s algorithm and an increasing use of ML make the algorithm increasingly impenetrable and mean that we are having to do more testing on individual sites to understand what works
While I believe that the opportunity is large and still growing (see, for example, this slide showing Google growing as a referrer of traffic even as CTR has declined in some areas), it’s clear that the narrative is going to lead to more challenging conversations and budgets under increased scrutiny.
Can you justify your SEO investment?
What do you say when your CMO asks what you’re getting for your SEO investment?
What do you say when she asks whether the organic search opportunity is tapped out?
I’ll probably explore the answers to both these questions more in another post, but suffice it to say that I do a lot of thinking about these kinds of questions.
The first is why we have built our split-testing platform to make organic SEO investments measurable, quantifiable and accountable.
The second is why I think it’s super important to remember the big picture while the media is running around with hair on fire. Media companies saw Facebook overtake Google as a traffic channel (and then are likely seeing that reverse right now), but most of the web has Google as the largest and growing source of traffic and value.
The reality (from clickstream data) is that it's really easy to forget how long the long-tail is and how sparse search features and ads are on the extreme long-tail:
Only 3–4% of all searches result in a click on an ad, for example. Google's incredible (and still growing) business is based on a small subset of commercial searches
Google's share of all outbound referral traffic across the web is growing (and Facebook's is shrinking as they increasingly wall off their garden)
The opportunity is for smart brands to capitalize on a growing opportunity while their competitors sink time and money into a social space that is increasingly all about Facebook, and increasingly pay-to-play.
What do you think? Are you having these hard conversations with leadership? How are you measuring your digital brand’s value?
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isearchgoood · 7 years
Text
The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
Posted by willcritchlow
Digital marketing is measurable.
It’s probably the single most common claim everyone hears about digital, and I can’t count the number of times I’ve seen conference speakers talk about it (heck, I’ve even done it myself).
I mean, look at those offline dinosaurs, the argument goes. They all know that half their spend is wasted — they just don’t know which half.
Maybe the joke’s on us digital marketers though, who garnered only 41% of global ad spend even in 2017 after years of strong growth.
Unfortunately, while we were geeking out about attribution models and cross-device tracking, we were accidentally triggering a common human cognitive bias that kept us anchored on small amounts, leaving buckets of money on the table and fundamentally reducing our impact and access to the C-suite.
And what’s worse is that we have convinced ourselves that it’s a critical part of what makes digital marketing great. The simplest way to see this is to realize that, for most of us, I very much doubt that if you removed all our measurement ability we’d reduce our digital marketing investment to nothing.
In truth, of course, we’re nowhere close to measuring all the benefits of most of the things we do. We certainly track the last clicks, and we’re not bad at tracking any clicks on the path to conversion on the same device, but we generally suck at capturing:
Anything that happens on a different device
Brand awareness impacts that lead to much later improvements in conversion rate, average order value, or lifetime value
Benefits of visibility or impressions that aren’t clicked
Brand affinity generally
The cognitive bias that leads us astray
All of this means that the returns we report on tend to be just the most direct returns. This should be fine — it’s just a floor on the true value (“this activity has generated at least this much value for the brand”) — but the “anchoring” cognitive bias means that it messes with our minds and our clients’ minds. Anchoring is the process whereby we fixate on the first number we hear and subsequently estimate unknowns closer to the anchoring number than we should. Famous experiments have shown that even showing people a totally random number can drag their subsequent estimates up or down.
So even if the true value of our activity was 10x the measured value, we’d be stuck on estimating the true value as very close to the single concrete, exact number we heard along the way.
This tends to result in the measured value being seen as a ceiling on the true value. Other biases like the availability heuristic (which results in us overstating the likelihood of things that are easy to remember) tend to mean that we tend to want to factor in obvious ways that the direct value measurement could be overstating things, and leave to one side all the unmeasured extra value.
The mistake became a really big one because fortunately/unfortunately, the measured return in digital has often been enough to justify at least a reasonable level of the activity. If it hadn’t been (think the vanishingly small number of people who see a billboard and immediately buy a car within the next week when they weren’t otherwise going to do so) we’d have been forced to talk more about the other benefits. But we weren’t. So we lazily talked about the measured value, and about the measurability as a benefit and a differentiator.
The threats of relying on exact measurement
Not only do we leave a whole load of credit (read: cash) on the table, but it also leads to threats to measurability being seen as existential threats to digital marketing activity as a whole. We know that there are growing threats to measuring accurately, including regulatory, technological, and user-behavior shifts:
GDPR and other privacy regulations are limiting what we are allowed to do (and, as platforms catch up, what we can do)
Privacy features are being included in more products, added on by savvy consumers, or simply being set to be on by default more often, with even the biggest company in the world touting privacy as a core differentiator
Users continue to increase the extent to which they research and buy across multiple devices
Compared to early in Google’s rise, the lack of keyword-level analytics data and the rise of (not provided) means that we have far less visibility into the details than we used to when the narrative of measurability was being written
Now, imagine that the combination of these trends meant that you lost 100% of your analytics and data. Would it mean that your leads stopped? Would you immediately turn your website off? Stop marketing?
I suggest that the answer to all of that is “no.” There's a ton of value to digital marketing beyond the ability to track specific interactions.
We’re obviously not going to see our measurable insights disappear to zero, but for all the reasons I outlined above, it’s worth thinking about all the ways that our activities add value, how that value manifests, and some ways of proving it exists even if you can’t measure it.
How should we talk about value?
There are two pieces to the brand value puzzle:
Figuring out the value of increasing brand awareness or affinity
Understanding how our digital activities are changing said awareness or affinity
There's obviously a lot of research into brand valuations generally, and while it’s outside the scope of this piece to think about total brand value, it’s worth noting that some methodologies place as much as 75% of the enterprise value of even some large companies in the value of their brands:
Image source
My colleague Tom Capper has written about a variety of ways to measure changes in brand awareness, which attacks a good chunk of the second challenge. But challenge #1 remains: how do we figure out what it’s worth to carry out some marketing activity that changes brand awareness or affinity?
In a recent post, I discussed different ways of building marketing models and one of the methodologies I described might be useful for this - namely so-called “top-down” modelling which I defined as being about percentages and trends (as opposed to raw numbers and units of production).
The top-down approach
I’ve come up with two possible ways of modelling brand value in a transactional sense:
1. The Sherlock approach
“When you have eliminated the impossible, whatever remains, however improbable, must be the truth." - Sherlock Holmes
The outline would be to take the total new revenue acquired in a period. Subtract from this any elements that can be attributed to specific acquisition channels; whatever remains must be brand. If this is in any way stable or predictable over multiple periods, you can use it as a baseline value from which to apply the methodologies outlined above for measuring changes in brand awareness and affinity.
2. Aggressive attribution
If you run normal first-touch attribution reports, the limitations of measurement (clearing cookies, multiple devices etc) mean that you will show first-touch revenue that seems somewhat implausible (e.g. email; email surely can’t be a first-touch source — how did they get on your email list in the first place?):
Click for a larger version
In this screenshot we see that although first-touch dramatically reduces the influence of direct, for instance, it still accounts for more than 15% of new revenue.
The aggressive attribution model takes total revenue and splits it between the acquisition channels (unbranded search, paid social, referral). A first pass on this would simply split it in the relative proportion to the size of each of those channels, effectively normalizing them, though you could build more sophisticated models.
Note that there is no way of perfectly identifying branded/unbranded organic search since (not provided) and so you’ll have to use a proxy like homepage search vs. non-homepage search.
But fundamentally, the argument here would be that any revenue coming from a “first touch” of:
Branded search
Direct
Organic social
Email
...was actually acquired previously via one of the acquisition channels and so we attempt to attribute it to those channels.
Even this under-represents brand value
Both of those methodologies are pretty aggressive — but they might still under-represent brand value. Here are two additional mechanics where brand drives organic search volume in ways I haven’t figured out how to measure yet:
Trusting Amazon to rank
I like reading on the Kindle. If I hear of a book I’d like to read, I’ll often Google the name of the book on its own and trust that Amazon will rank first or second so I can get to the Kindle page to buy it. This is effectively a branded search for Amazon (and if it doesn’t rank, I’ll likely follow up with a [book name amazon] search or head on over to Amazon to search there directly).
But because all I’ve appeared to do is search [book name] on Google and then click through to Amazon, there is nothing to differentiate this from an unbranded search.
Spotting brands you trust in the SERPs
I imagine we all have anecdotal experience of doing this: you do a search and you spot a website you know and trust (or where you have an account) ranking somewhere other than #1 and click on it regardless of position.
One time that I can specifically recall noticing this tendency growing in myself was when I started doing tons more baby-related searches after my first child was born. Up until that point, I had effectively zero brand affinity with anyone in the space, but I quickly grew to rate the content put out by babycentre (babycenter in the US) and I found myself often clicking on their result in position 3 or 4 even when I hadn’t set out to look for them, e.g. in results like this one:
It was fascinating to me to observe this behavior in myself because I had no real interaction with babycentre outside of search, and yet, by consistently ranking well across tons of long-tail queries and providing consistently good content and user experience I came to know and trust them and click on them even when they were outranked. I find this to be a great example because it is entirely self-contained within organic search. They built a brand effect through organic search and reaped the reward in increased organic search.
I have essentially no ideas on how to measure either of these effects. If you have any bright ideas, do let me know in the comments.
Budgets will come under pressure
My belief is that total digital budgets will continue to grow (especially as TV continues to fragment), but I also believe that individual budgets are going to come under scrutiny and pressure making this kind of thinking increasingly important.
We know that there is going to be pressure on referral traffic from Facebook following the recent news feed announcements, but there is also pressure on trust in Google:
Before the recent news feed changes, slightly misleading stories had implied that Google had lost the top spot as the largest referrer of traffic (whereas in fact this was only briefly true in media)
The growth of the mobile-first card view and richer and richer SERPs has led to declines in outbound CTR in some areas
The increasingly black-box nature of Google’s algorithm and an increasing use of ML make the algorithm increasingly impenetrable and mean that we are having to do more testing on individual sites to understand what works
While I believe that the opportunity is large and still growing (see, for example, this slide showing Google growing as a referrer of traffic even as CTR has declined in some areas), it’s clear that the narrative is going to lead to more challenging conversations and budgets under increased scrutiny.
Can you justify your SEO investment?
What do you say when your CMO asks what you’re getting for your SEO investment?
What do you say when she asks whether the organic search opportunity is tapped out?
I’ll probably explore the answers to both these questions more in another post, but suffice it to say that I do a lot of thinking about these kinds of questions.
The first is why we have built our split-testing platform to make organic SEO investments measurable, quantifiable and accountable.
The second is why I think it’s super important to remember the big picture while the media is running around with hair on fire. Media companies saw Facebook overtake Google as a traffic channel (and then are likely seeing that reverse right now), but most of the web has Google as the largest and growing source of traffic and value.
The reality (from clickstream data) is that it's really easy to forget how long the long-tail is and how sparse search features and ads are on the extreme long-tail:
Only 3–4% of all searches result in a click on an ad, for example. Google's incredible (and still growing) business is based on a small subset of commercial searches
Google's share of all outbound referral traffic across the web is growing (and Facebook's is shrinking as they increasingly wall off their garden)
The opportunity is for smart brands to capitalize on a growing opportunity while their competitors sink time and money into a social space that is increasingly all about Facebook, and increasingly pay-to-play.
What do you think? Are you having these hard conversations with leadership? How are you measuring your digital brand’s value?
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0 notes
mercedessharonwo1 · 7 years
Text
The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
Posted by willcritchlow
Digital marketing is measurable.
It’s probably the single most common claim everyone hears about digital, and I can’t count the number of times I’ve seen conference speakers talk about it (heck, I’ve even done it myself).
I mean, look at those offline dinosaurs, the argument goes. They all know that half their spend is wasted — they just don’t know which half.
Maybe the joke’s on us digital marketers though, who garnered only 41% of global ad spend even in 2017 after years of strong growth.
Unfortunately, while we were geeking out about attribution models and cross-device tracking, we were accidentally triggering a common human cognitive bias that kept us anchored on small amounts, leaving buckets of money on the table and fundamentally reducing our impact and access to the C-suite.
And what’s worse is that we have convinced ourselves that it’s a critical part of what makes digital marketing great. The simplest way to see this is to realize that, for most of us, I very much doubt that if you removed all our measurement ability we’d reduce our digital marketing investment to nothing.
In truth, of course, we’re nowhere close to measuring all the benefits of most of the things we do. We certainly track the last clicks, and we’re not bad at tracking any clicks on the path to conversion on the same device, but we generally suck at capturing:
Anything that happens on a different device
Brand awareness impacts that lead to much later improvements in conversion rate, average order value, or lifetime value
Benefits of visibility or impressions that aren’t clicked
Brand affinity generally
The cognitive bias that leads us astray
All of this means that the returns we report on tend to be just the most direct returns. This should be fine — it’s just a floor on the true value (“this activity has generated at least this much value for the brand”) — but the “anchoring” cognitive bias means that it messes with our minds and our clients’ minds. Anchoring is the process whereby we fixate on the first number we hear and subsequently estimate unknowns closer to the anchoring number than we should. Famous experiments have shown that even showing people a totally random number can drag their subsequent estimates up or down.
So even if the true value of our activity was 10x the measured value, we’d be stuck on estimating the true value as very close to the single concrete, exact number we heard along the way.
This tends to result in the measured value being seen as a ceiling on the true value. Other biases like the availability heuristic (which results in us overstating the likelihood of things that are easy to remember) tend to mean that we tend to want to factor in obvious ways that the direct value measurement could be overstating things, and leave to one side all the unmeasured extra value.
The mistake became a really big one because fortunately/unfortunately, the measured return in digital has often been enough to justify at least a reasonable level of the activity. If it hadn’t been (think the vanishingly small number of people who see a billboard and immediately buy a car within the next week when they weren’t otherwise going to do so) we’d have been forced to talk more about the other benefits. But we weren’t. So we lazily talked about the measured value, and about the measurability as a benefit and a differentiator.
The threats of relying on exact measurement
Not only do we leave a whole load of credit (read: cash) on the table, but it also leads to threats to measurability being seen as existential threats to digital marketing activity as a whole. We know that there are growing threats to measuring accurately, including regulatory, technological, and user-behavior shifts:
GDPR and other privacy regulations are limiting what we are allowed to do (and, as platforms catch up, what we can do)
Privacy features are being included in more products, added on by savvy consumers, or simply being set to be on by default more often, with even the biggest company in the world touting privacy as a core differentiator
Users continue to increase the extent to which they research and buy across multiple devices
Compared to early in Google’s rise, the lack of keyword-level analytics data and the rise of (not provided) means that we have far less visibility into the details than we used to when the narrative of measurability was being written
Now, imagine that the combination of these trends meant that you lost 100% of your analytics and data. Would it mean that your leads stopped? Would you immediately turn your website off? Stop marketing?
I suggest that the answer to all of that is “no.” There's a ton of value to digital marketing beyond the ability to track specific interactions.
We’re obviously not going to see our measurable insights disappear to zero, but for all the reasons I outlined above, it’s worth thinking about all the ways that our activities add value, how that value manifests, and some ways of proving it exists even if you can’t measure it.
How should we talk about value?
There are two pieces to the brand value puzzle:
Figuring out the value of increasing brand awareness or affinity
Understanding how our digital activities are changing said awareness or affinity
There's obviously a lot of research into brand valuations generally, and while it’s outside the scope of this piece to think about total brand value, it’s worth noting that some methodologies place as much as 75% of the enterprise value of even some large companies in the value of their brands:
Image source
My colleague Tom Capper has written about a variety of ways to measure changes in brand awareness, which attacks a good chunk of the second challenge. But challenge #1 remains: how do we figure out what it’s worth to carry out some marketing activity that changes brand awareness or affinity?
In a recent post, I discussed different ways of building marketing models and one of the methodologies I described might be useful for this - namely so-called “top-down” modelling which I defined as being about percentages and trends (as opposed to raw numbers and units of production).
The top-down approach
I’ve come up with two possible ways of modelling brand value in a transactional sense:
1. The Sherlock approach
“When you have eliminated the impossible, whatever remains, however improbable, must be the truth." - Sherlock Holmes
The outline would be to take the total new revenue acquired in a period. Subtract from this any elements that can be attributed to specific acquisition channels; whatever remains must be brand. If this is in any way stable or predictable over multiple periods, you can use it as a baseline value from which to apply the methodologies outlined above for measuring changes in brand awareness and affinity.
2. Aggressive attribution
If you run normal first-touch attribution reports, the limitations of measurement (clearing cookies, multiple devices etc) mean that you will show first-touch revenue that seems somewhat implausible (e.g. email; email surely can’t be a first-touch source — how did they get on your email list in the first place?):
http://ift.tt/2EBZMw3
0 notes
dainiaolivahm · 7 years
Text
The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
Posted by willcritchlow
Digital marketing is measurable.
It’s probably the single most common claim everyone hears about digital, and I can’t count the number of times I’ve seen conference speakers talk about it (heck, I’ve even done it myself).
I mean, look at those offline dinosaurs, the argument goes. They all know that half their spend is wasted — they just don’t know which half.
Maybe the joke’s on us digital marketers though, who garnered only 41% of global ad spend even in 2017 after years of strong growth.
Unfortunately, while we were geeking out about attribution models and cross-device tracking, we were accidentally triggering a common human cognitive bias that kept us anchored on small amounts, leaving buckets of money on the table and fundamentally reducing our impact and access to the C-suite.
And what’s worse is that we have convinced ourselves that it’s a critical part of what makes digital marketing great. The simplest way to see this is to realize that, for most of us, I very much doubt that if you removed all our measurement ability we’d reduce our digital marketing investment to nothing.
In truth, of course, we’re nowhere close to measuring all the benefits of most of the things we do. We certainly track the last clicks, and we’re not bad at tracking any clicks on the path to conversion on the same device, but we generally suck at capturing:
Anything that happens on a different device
Brand awareness impacts that lead to much later improvements in conversion rate, average order value, or lifetime value
Benefits of visibility or impressions that aren’t clicked
Brand affinity generally
The cognitive bias that leads us astray
All of this means that the returns we report on tend to be just the most direct returns. This should be fine — it’s just a floor on the true value (“this activity has generated at least this much value for the brand”) — but the “anchoring” cognitive bias means that it messes with our minds and our clients’ minds. Anchoring is the process whereby we fixate on the first number we hear and subsequently estimate unknowns closer to the anchoring number than we should. Famous experiments have shown that even showing people a totally random number can drag their subsequent estimates up or down.
So even if the true value of our activity was 10x the measured value, we’d be stuck on estimating the true value as very close to the single concrete, exact number we heard along the way.
This tends to result in the measured value being seen as a ceiling on the true value. Other biases like the availability heuristic (which results in us overstating the likelihood of things that are easy to remember) tend to mean that we tend to want to factor in obvious ways that the direct value measurement could be overstating things, and leave to one side all the unmeasured extra value.
The mistake became a really big one because fortunately/unfortunately, the measured return in digital has often been enough to justify at least a reasonable level of the activity. If it hadn’t been (think the vanishingly small number of people who see a billboard and immediately buy a car within the next week when they weren’t otherwise going to do so) we’d have been forced to talk more about the other benefits. But we weren’t. So we lazily talked about the measured value, and about the measurability as a benefit and a differentiator.
The threats of relying on exact measurement
Not only do we leave a whole load of credit (read: cash) on the table, but it also leads to threats to measurability being seen as existential threats to digital marketing activity as a whole. We know that there are growing threats to measuring accurately, including regulatory, technological, and user-behavior shifts:
GDPR and other privacy regulations are limiting what we are allowed to do (and, as platforms catch up, what we can do)
Privacy features are being included in more products, added on by savvy consumers, or simply being set to be on by default more often, with even the biggest company in the world touting privacy as a core differentiator
Users continue to increase the extent to which they research and buy across multiple devices
Compared to early in Google’s rise, the lack of keyword-level analytics data and the rise of (not provided) means that we have far less visibility into the details than we used to when the narrative of measurability was being written
Now, imagine that the combination of these trends meant that you lost 100% of your analytics and data. Would it mean that your leads stopped? Would you immediately turn your website off? Stop marketing?
I suggest that the answer to all of that is “no.” There's a ton of value to digital marketing beyond the ability to track specific interactions.
We’re obviously not going to see our measurable insights disappear to zero, but for all the reasons I outlined above, it’s worth thinking about all the ways that our activities add value, how that value manifests, and some ways of proving it exists even if you can’t measure it.
How should we talk about value?
There are two pieces to the brand value puzzle:
Figuring out the value of increasing brand awareness or affinity
Understanding how our digital activities are changing said awareness or affinity
There's obviously a lot of research into brand valuations generally, and while it’s outside the scope of this piece to think about total brand value, it’s worth noting that some methodologies place as much as 75% of the enterprise value of even some large companies in the value of their brands:
Image source
My colleague Tom Capper has written about a variety of ways to measure changes in brand awareness, which attacks a good chunk of the second challenge. But challenge #1 remains: how do we figure out what it’s worth to carry out some marketing activity that changes brand awareness or affinity?
In a recent post, I discussed different ways of building marketing models and one of the methodologies I described might be useful for this - namely so-called “top-down” modelling which I defined as being about percentages and trends (as opposed to raw numbers and units of production).
The top-down approach
I’ve come up with two possible ways of modelling brand value in a transactional sense:
1. The Sherlock approach
“When you have eliminated the impossible, whatever remains, however improbable, must be the truth." - Sherlock Holmes
The outline would be to take the total new revenue acquired in a period. Subtract from this any elements that can be attributed to specific acquisition channels; whatever remains must be brand. If this is in any way stable or predictable over multiple periods, you can use it as a baseline value from which to apply the methodologies outlined above for measuring changes in brand awareness and affinity.
2. Aggressive attribution
If you run normal first-touch attribution reports, the limitations of measurement (clearing cookies, multiple devices etc) mean that you will show first-touch revenue that seems somewhat implausible (e.g. email; email surely can’t be a first-touch source — how did they get on your email list in the first place?):
http://ift.tt/2EBZMw3
0 notes
mariasolemarionqi · 7 years
Text
The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
Posted by willcritchlow
Digital marketing is measurable.
It’s probably the single most common claim everyone hears about digital, and I can’t count the number of times I’ve seen conference speakers talk about it (heck, I’ve even done it myself).
I mean, look at those offline dinosaurs, the argument goes. They all know that half their spend is wasted — they just don’t know which half.
Maybe the joke’s on us digital marketers though, who garnered only 41% of global ad spend even in 2017 after years of strong growth.
Unfortunately, while we were geeking out about attribution models and cross-device tracking, we were accidentally triggering a common human cognitive bias that kept us anchored on small amounts, leaving buckets of money on the table and fundamentally reducing our impact and access to the C-suite.
And what’s worse is that we have convinced ourselves that it’s a critical part of what makes digital marketing great. The simplest way to see this is to realize that, for most of us, I very much doubt that if you removed all our measurement ability we’d reduce our digital marketing investment to nothing.
In truth, of course, we’re nowhere close to measuring all the benefits of most of the things we do. We certainly track the last clicks, and we’re not bad at tracking any clicks on the path to conversion on the same device, but we generally suck at capturing:
Anything that happens on a different device
Brand awareness impacts that lead to much later improvements in conversion rate, average order value, or lifetime value
Benefits of visibility or impressions that aren’t clicked
Brand affinity generally
The cognitive bias that leads us astray
All of this means that the returns we report on tend to be just the most direct returns. This should be fine — it’s just a floor on the true value (“this activity has generated at least this much value for the brand”) — but the “anchoring” cognitive bias means that it messes with our minds and our clients’ minds. Anchoring is the process whereby we fixate on the first number we hear and subsequently estimate unknowns closer to the anchoring number than we should. Famous experiments have shown that even showing people a totally random number can drag their subsequent estimates up or down.
So even if the true value of our activity was 10x the measured value, we’d be stuck on estimating the true value as very close to the single concrete, exact number we heard along the way.
This tends to result in the measured value being seen as a ceiling on the true value. Other biases like the availability heuristic (which results in us overstating the likelihood of things that are easy to remember) tend to mean that we tend to want to factor in obvious ways that the direct value measurement could be overstating things, and leave to one side all the unmeasured extra value.
The mistake became a really big one because fortunately/unfortunately, the measured return in digital has often been enough to justify at least a reasonable level of the activity. If it hadn’t been (think the vanishingly small number of people who see a billboard and immediately buy a car within the next week when they weren’t otherwise going to do so) we’d have been forced to talk more about the other benefits. But we weren’t. So we lazily talked about the measured value, and about the measurability as a benefit and a differentiator.
The threats of relying on exact measurement
Not only do we leave a whole load of credit (read: cash) on the table, but it also leads to threats to measurability being seen as existential threats to digital marketing activity as a whole. We know that there are growing threats to measuring accurately, including regulatory, technological, and user-behavior shifts:
GDPR and other privacy regulations are limiting what we are allowed to do (and, as platforms catch up, what we can do)
Privacy features are being included in more products, added on by savvy consumers, or simply being set to be on by default more often, with even the biggest company in the world touting privacy as a core differentiator
Users continue to increase the extent to which they research and buy across multiple devices
Compared to early in Google’s rise, the lack of keyword-level analytics data and the rise of (not provided) means that we have far less visibility into the details than we used to when the narrative of measurability was being written
Now, imagine that the combination of these trends meant that you lost 100% of your analytics and data. Would it mean that your leads stopped? Would you immediately turn your website off? Stop marketing?
I suggest that the answer to all of that is “no.” There's a ton of value to digital marketing beyond the ability to track specific interactions.
We’re obviously not going to see our measurable insights disappear to zero, but for all the reasons I outlined above, it’s worth thinking about all the ways that our activities add value, how that value manifests, and some ways of proving it exists even if you can’t measure it.
How should we talk about value?
There are two pieces to the brand value puzzle:
Figuring out the value of increasing brand awareness or affinity
Understanding how our digital activities are changing said awareness or affinity
There's obviously a lot of research into brand valuations generally, and while it’s outside the scope of this piece to think about total brand value, it’s worth noting that some methodologies place as much as 75% of the enterprise value of even some large companies in the value of their brands:
Image source
My colleague Tom Capper has written about a variety of ways to measure changes in brand awareness, which attacks a good chunk of the second challenge. But challenge #1 remains: how do we figure out what it’s worth to carry out some marketing activity that changes brand awareness or affinity?
In a recent post, I discussed different ways of building marketing models and one of the methodologies I described might be useful for this - namely so-called “top-down” modelling which I defined as being about percentages and trends (as opposed to raw numbers and units of production).
The top-down approach
I’ve come up with two possible ways of modelling brand value in a transactional sense:
1. The Sherlock approach
“When you have eliminated the impossible, whatever remains, however improbable, must be the truth." - Sherlock Holmes
The outline would be to take the total new revenue acquired in a period. Subtract from this any elements that can be attributed to specific acquisition channels; whatever remains must be brand. If this is in any way stable or predictable over multiple periods, you can use it as a baseline value from which to apply the methodologies outlined above for measuring changes in brand awareness and affinity.
2. Aggressive attribution
If you run normal first-touch attribution reports, the limitations of measurement (clearing cookies, multiple devices etc) mean that you will show first-touch revenue that seems somewhat implausible (e.g. email; email surely can’t be a first-touch source — how did they get on your email list in the first place?):
http://ift.tt/2EBZMw3
0 notes
fairchildlingpo1 · 7 years
Text
The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
Posted by willcritchlow
Digital marketing is measurable.
It’s probably the single most common claim everyone hears about digital, and I can’t count the number of times I’ve seen conference speakers talk about it (heck, I’ve even done it myself).
I mean, look at those offline dinosaurs, the argument goes. They all know that half their spend is wasted — they just don’t know which half.
Maybe the joke’s on us digital marketers though, who garnered only 41% of global ad spend even in 2017 after years of strong growth.
Unfortunately, while we were geeking out about attribution models and cross-device tracking, we were accidentally triggering a common human cognitive bias that kept us anchored on small amounts, leaving buckets of money on the table and fundamentally reducing our impact and access to the C-suite.
And what’s worse is that we have convinced ourselves that it’s a critical part of what makes digital marketing great. The simplest way to see this is to realize that, for most of us, I very much doubt that if you removed all our measurement ability we’d reduce our digital marketing investment to nothing.
In truth, of course, we’re nowhere close to measuring all the benefits of most of the things we do. We certainly track the last clicks, and we’re not bad at tracking any clicks on the path to conversion on the same device, but we generally suck at capturing:
Anything that happens on a different device
Brand awareness impacts that lead to much later improvements in conversion rate, average order value, or lifetime value
Benefits of visibility or impressions that aren’t clicked
Brand affinity generally
The cognitive bias that leads us astray
All of this means that the returns we report on tend to be just the most direct returns. This should be fine — it’s just a floor on the true value (“this activity has generated at least this much value for the brand”) — but the “anchoring” cognitive bias means that it messes with our minds and our clients’ minds. Anchoring is the process whereby we fixate on the first number we hear and subsequently estimate unknowns closer to the anchoring number than we should. Famous experiments have shown that even showing people a totally random number can drag their subsequent estimates up or down.
So even if the true value of our activity was 10x the measured value, we’d be stuck on estimating the true value as very close to the single concrete, exact number we heard along the way.
This tends to result in the measured value being seen as a ceiling on the true value. Other biases like the availability heuristic (which results in us overstating the likelihood of things that are easy to remember) tend to mean that we tend to want to factor in obvious ways that the direct value measurement could be overstating things, and leave to one side all the unmeasured extra value.
The mistake became a really big one because fortunately/unfortunately, the measured return in digital has often been enough to justify at least a reasonable level of the activity. If it hadn’t been (think the vanishingly small number of people who see a billboard and immediately buy a car within the next week when they weren’t otherwise going to do so) we’d have been forced to talk more about the other benefits. But we weren’t. So we lazily talked about the measured value, and about the measurability as a benefit and a differentiator.
The threats of relying on exact measurement
Not only do we leave a whole load of credit (read: cash) on the table, but it also leads to threats to measurability being seen as existential threats to digital marketing activity as a whole. We know that there are growing threats to measuring accurately, including regulatory, technological, and user-behavior shifts:
GDPR and other privacy regulations are limiting what we are allowed to do (and, as platforms catch up, what we can do)
Privacy features are being included in more products, added on by savvy consumers, or simply being set to be on by default more often, with even the biggest company in the world touting privacy as a core differentiator
Users continue to increase the extent to which they research and buy across multiple devices
Compared to early in Google’s rise, the lack of keyword-level analytics data and the rise of (not provided) means that we have far less visibility into the details than we used to when the narrative of measurability was being written
Now, imagine that the combination of these trends meant that you lost 100% of your analytics and data. Would it mean that your leads stopped? Would you immediately turn your website off? Stop marketing?
I suggest that the answer to all of that is “no.” There's a ton of value to digital marketing beyond the ability to track specific interactions.
We’re obviously not going to see our measurable insights disappear to zero, but for all the reasons I outlined above, it’s worth thinking about all the ways that our activities add value, how that value manifests, and some ways of proving it exists even if you can’t measure it.
How should we talk about value?
There are two pieces to the brand value puzzle:
Figuring out the value of increasing brand awareness or affinity
Understanding how our digital activities are changing said awareness or affinity
There's obviously a lot of research into brand valuations generally, and while it’s outside the scope of this piece to think about total brand value, it’s worth noting that some methodologies place as much as 75% of the enterprise value of even some large companies in the value of their brands:
Image source
My colleague Tom Capper has written about a variety of ways to measure changes in brand awareness, which attacks a good chunk of the second challenge. But challenge #1 remains: how do we figure out what it’s worth to carry out some marketing activity that changes brand awareness or affinity?
In a recent post, I discussed different ways of building marketing models and one of the methodologies I described might be useful for this - namely so-called “top-down” modelling which I defined as being about percentages and trends (as opposed to raw numbers and units of production).
The top-down approach
I’ve come up with two possible ways of modelling brand value in a transactional sense:
1. The Sherlock approach
“When you have eliminated the impossible, whatever remains, however improbable, must be the truth." - Sherlock Holmes
The outline would be to take the total new revenue acquired in a period. Subtract from this any elements that can be attributed to specific acquisition channels; whatever remains must be brand. If this is in any way stable or predictable over multiple periods, you can use it as a baseline value from which to apply the methodologies outlined above for measuring changes in brand awareness and affinity.
2. Aggressive attribution
If you run normal first-touch attribution reports, the limitations of measurement (clearing cookies, multiple devices etc) mean that you will show first-touch revenue that seems somewhat implausible (e.g. email; email surely can’t be a first-touch source — how did they get on your email list in the first place?):
http://ift.tt/2EBZMw3
0 notes
christinesumpmg1 · 7 years
Text
The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
Posted by willcritchlow
Digital marketing is measurable.
It’s probably the single most common claim everyone hears about digital, and I can’t count the number of times I’ve seen conference speakers talk about it (heck, I’ve even done it myself).
I mean, look at those offline dinosaurs, the argument goes. They all know that half their spend is wasted — they just don’t know which half.
Maybe the joke’s on us digital marketers though, who garnered only 41% of global ad spend even in 2017 after years of strong growth.
Unfortunately, while we were geeking out about attribution models and cross-device tracking, we were accidentally triggering a common human cognitive bias that kept us anchored on small amounts, leaving buckets of money on the table and fundamentally reducing our impact and access to the C-suite.
And what’s worse is that we have convinced ourselves that it’s a critical part of what makes digital marketing great. The simplest way to see this is to realize that, for most of us, I very much doubt that if you removed all our measurement ability we’d reduce our digital marketing investment to nothing.
In truth, of course, we’re nowhere close to measuring all the benefits of most of the things we do. We certainly track the last clicks, and we’re not bad at tracking any clicks on the path to conversion on the same device, but we generally suck at capturing:
Anything that happens on a different device
Brand awareness impacts that lead to much later improvements in conversion rate, average order value, or lifetime value
Benefits of visibility or impressions that aren’t clicked
Brand affinity generally
The cognitive bias that leads us astray
All of this means that the returns we report on tend to be just the most direct returns. This should be fine — it’s just a floor on the true value (“this activity has generated at least this much value for the brand”) — but the “anchoring” cognitive bias means that it messes with our minds and our clients’ minds. Anchoring is the process whereby we fixate on the first number we hear and subsequently estimate unknowns closer to the anchoring number than we should. Famous experiments have shown that even showing people a totally random number can drag their subsequent estimates up or down.
So even if the true value of our activity was 10x the measured value, we’d be stuck on estimating the true value as very close to the single concrete, exact number we heard along the way.
This tends to result in the measured value being seen as a ceiling on the true value. Other biases like the availability heuristic (which results in us overstating the likelihood of things that are easy to remember) tend to mean that we tend to want to factor in obvious ways that the direct value measurement could be overstating things, and leave to one side all the unmeasured extra value.
The mistake became a really big one because fortunately/unfortunately, the measured return in digital has often been enough to justify at least a reasonable level of the activity. If it hadn’t been (think the vanishingly small number of people who see a billboard and immediately buy a car within the next week when they weren’t otherwise going to do so) we’d have been forced to talk more about the other benefits. But we weren’t. So we lazily talked about the measured value, and about the measurability as a benefit and a differentiator.
The threats of relying on exact measurement
Not only do we leave a whole load of credit (read: cash) on the table, but it also leads to threats to measurability being seen as existential threats to digital marketing activity as a whole. We know that there are growing threats to measuring accurately, including regulatory, technological, and user-behavior shifts:
GDPR and other privacy regulations are limiting what we are allowed to do (and, as platforms catch up, what we can do)
Privacy features are being included in more products, added on by savvy consumers, or simply being set to be on by default more often, with even the biggest company in the world touting privacy as a core differentiator
Users continue to increase the extent to which they research and buy across multiple devices
Compared to early in Google’s rise, the lack of keyword-level analytics data and the rise of (not provided) means that we have far less visibility into the details than we used to when the narrative of measurability was being written
Now, imagine that the combination of these trends meant that you lost 100% of your analytics and data. Would it mean that your leads stopped? Would you immediately turn your website off? Stop marketing?
I suggest that the answer to all of that is “no.” There's a ton of value to digital marketing beyond the ability to track specific interactions.
We’re obviously not going to see our measurable insights disappear to zero, but for all the reasons I outlined above, it’s worth thinking about all the ways that our activities add value, how that value manifests, and some ways of proving it exists even if you can’t measure it.
How should we talk about value?
There are two pieces to the brand value puzzle:
Figuring out the value of increasing brand awareness or affinity
Understanding how our digital activities are changing said awareness or affinity
There's obviously a lot of research into brand valuations generally, and while it’s outside the scope of this piece to think about total brand value, it’s worth noting that some methodologies place as much as 75% of the enterprise value of even some large companies in the value of their brands:
Image source
My colleague Tom Capper has written about a variety of ways to measure changes in brand awareness, which attacks a good chunk of the second challenge. But challenge #1 remains: how do we figure out what it’s worth to carry out some marketing activity that changes brand awareness or affinity?
In a recent post, I discussed different ways of building marketing models and one of the methodologies I described might be useful for this - namely so-called “top-down” modelling which I defined as being about percentages and trends (as opposed to raw numbers and units of production).
The top-down approach
I’ve come up with two possible ways of modelling brand value in a transactional sense:
1. The Sherlock approach
“When you have eliminated the impossible, whatever remains, however improbable, must be the truth." - Sherlock Holmes
The outline would be to take the total new revenue acquired in a period. Subtract from this any elements that can be attributed to specific acquisition channels; whatever remains must be brand. If this is in any way stable or predictable over multiple periods, you can use it as a baseline value from which to apply the methodologies outlined above for measuring changes in brand awareness and affinity.
2. Aggressive attribution
If you run normal first-touch attribution reports, the limitations of measurement (clearing cookies, multiple devices etc) mean that you will show first-touch revenue that seems somewhat implausible (e.g. email; email surely can’t be a first-touch source — how did they get on your email list in the first place?):
http://ift.tt/2EBZMw3
0 notes
christinesumpmg · 7 years
Text
The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
Posted by willcritchlow
Digital marketing is measurable.
It’s probably the single most common claim everyone hears about digital, and I can’t count the number of times I’ve seen conference speakers talk about it (heck, I’ve even done it myself).
I mean, look at those offline dinosaurs, the argument goes. They all know that half their spend is wasted — they just don’t know which half.
Maybe the joke’s on us digital marketers though, who garnered only 41% of global ad spend even in 2017 after years of strong growth.
Unfortunately, while we were geeking out about attribution models and cross-device tracking, we were accidentally triggering a common human cognitive bias that kept us anchored on small amounts, leaving buckets of money on the table and fundamentally reducing our impact and access to the C-suite.
And what’s worse is that we have convinced ourselves that it’s a critical part of what makes digital marketing great. The simplest way to see this is to realize that, for most of us, I very much doubt that if you removed all our measurement ability we’d reduce our digital marketing investment to nothing.
In truth, of course, we’re nowhere close to measuring all the benefits of most of the things we do. We certainly track the last clicks, and we’re not bad at tracking any clicks on the path to conversion on the same device, but we generally suck at capturing:
Anything that happens on a different device
Brand awareness impacts that lead to much later improvements in conversion rate, average order value, or lifetime value
Benefits of visibility or impressions that aren’t clicked
Brand affinity generally
The cognitive bias that leads us astray
All of this means that the returns we report on tend to be just the most direct returns. This should be fine — it’s just a floor on the true value (“this activity has generated at least this much value for the brand”) — but the “anchoring” cognitive bias means that it messes with our minds and our clients’ minds. Anchoring is the process whereby we fixate on the first number we hear and subsequently estimate unknowns closer to the anchoring number than we should. Famous experiments have shown that even showing people a totally random number can drag their subsequent estimates up or down.
So even if the true value of our activity was 10x the measured value, we’d be stuck on estimating the true value as very close to the single concrete, exact number we heard along the way.
This tends to result in the measured value being seen as a ceiling on the true value. Other biases like the availability heuristic (which results in us overstating the likelihood of things that are easy to remember) tend to mean that we tend to want to factor in obvious ways that the direct value measurement could be overstating things, and leave to one side all the unmeasured extra value.
The mistake became a really big one because fortunately/unfortunately, the measured return in digital has often been enough to justify at least a reasonable level of the activity. If it hadn’t been (think the vanishingly small number of people who see a billboard and immediately buy a car within the next week when they weren’t otherwise going to do so) we’d have been forced to talk more about the other benefits. But we weren’t. So we lazily talked about the measured value, and about the measurability as a benefit and a differentiator.
The threats of relying on exact measurement
Not only do we leave a whole load of credit (read: cash) on the table, but it also leads to threats to measurability being seen as existential threats to digital marketing activity as a whole. We know that there are growing threats to measuring accurately, including regulatory, technological, and user-behavior shifts:
GDPR and other privacy regulations are limiting what we are allowed to do (and, as platforms catch up, what we can do)
Privacy features are being included in more products, added on by savvy consumers, or simply being set to be on by default more often, with even the biggest company in the world touting privacy as a core differentiator
Users continue to increase the extent to which they research and buy across multiple devices
Compared to early in Google’s rise, the lack of keyword-level analytics data and the rise of (not provided) means that we have far less visibility into the details than we used to when the narrative of measurability was being written
Now, imagine that the combination of these trends meant that you lost 100% of your analytics and data. Would it mean that your leads stopped? Would you immediately turn your website off? Stop marketing?
I suggest that the answer to all of that is “no.” There's a ton of value to digital marketing beyond the ability to track specific interactions.
We’re obviously not going to see our measurable insights disappear to zero, but for all the reasons I outlined above, it’s worth thinking about all the ways that our activities add value, how that value manifests, and some ways of proving it exists even if you can’t measure it.
How should we talk about value?
There are two pieces to the brand value puzzle:
Figuring out the value of increasing brand awareness or affinity
Understanding how our digital activities are changing said awareness or affinity
There's obviously a lot of research into brand valuations generally, and while it’s outside the scope of this piece to think about total brand value, it’s worth noting that some methodologies place as much as 75% of the enterprise value of even some large companies in the value of their brands:
Image source
My colleague Tom Capper has written about a variety of ways to measure changes in brand awareness, which attacks a good chunk of the second challenge. But challenge #1 remains: how do we figure out what it’s worth to carry out some marketing activity that changes brand awareness or affinity?
In a recent post, I discussed different ways of building marketing models and one of the methodologies I described might be useful for this - namely so-called “top-down” modelling which I defined as being about percentages and trends (as opposed to raw numbers and units of production).
The top-down approach
I’ve come up with two possible ways of modelling brand value in a transactional sense:
1. The Sherlock approach
“When you have eliminated the impossible, whatever remains, however improbable, must be the truth." - Sherlock Holmes
The outline would be to take the total new revenue acquired in a period. Subtract from this any elements that can be attributed to specific acquisition channels; whatever remains must be brand. If this is in any way stable or predictable over multiple periods, you can use it as a baseline value from which to apply the methodologies outlined above for measuring changes in brand awareness and affinity.
2. Aggressive attribution
If you run normal first-touch attribution reports, the limitations of measurement (clearing cookies, multiple devices etc) mean that you will show first-touch revenue that seems somewhat implausible (e.g. email; email surely can’t be a first-touch source — how did they get on your email list in the first place?):
http://ift.tt/2EBZMw3
0 notes
maryhare96 · 7 years
Text
The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
Posted by willcritchlow
Digital marketing is measurable.
It’s probably the single most common claim everyone hears about digital, and I can’t count the number of times I’ve seen conference speakers talk about it (heck, I’ve even done it myself).
I mean, look at those offline dinosaurs, the argument goes. They all know that half their spend is wasted — they just don’t know which half.
Maybe the joke’s on us digital marketers though, who garnered only 41% of global ad spend even in 2017 after years of strong growth.
Unfortunately, while we were geeking out about attribution models and cross-device tracking, we were accidentally triggering a common human cognitive bias that kept us anchored on small amounts, leaving buckets of money on the table and fundamentally reducing our impact and access to the C-suite.
And what’s worse is that we have convinced ourselves that it’s a critical part of what makes digital marketing great. The simplest way to see this is to realize that, for most of us, I very much doubt that if you removed all our measurement ability we’d reduce our digital marketing investment to nothing.
In truth, of course, we’re nowhere close to measuring all the benefits of most of the things we do. We certainly track the last clicks, and we’re not bad at tracking any clicks on the path to conversion on the same device, but we generally suck at capturing:
Anything that happens on a different device
Brand awareness impacts that lead to much later improvements in conversion rate, average order value, or lifetime value
Benefits of visibility or impressions that aren’t clicked
Brand affinity generally
The cognitive bias that leads us astray
All of this means that the returns we report on tend to be just the most direct returns. This should be fine — it’s just a floor on the true value (“this activity has generated at least this much value for the brand”) — but the “anchoring” cognitive bias means that it messes with our minds and our clients’ minds. Anchoring is the process whereby we fixate on the first number we hear and subsequently estimate unknowns closer to the anchoring number than we should. Famous experiments have shown that even showing people a totally random number can drag their subsequent estimates up or down.
So even if the true value of our activity was 10x the measured value, we’d be stuck on estimating the true value as very close to the single concrete, exact number we heard along the way.
This tends to result in the measured value being seen as a ceiling on the true value. Other biases like the availability heuristic (which results in us overstating the likelihood of things that are easy to remember) tend to mean that we tend to want to factor in obvious ways that the direct value measurement could be overstating things, and leave to one side all the unmeasured extra value.
The mistake became a really big one because fortunately/unfortunately, the measured return in digital has often been enough to justify at least a reasonable level of the activity. If it hadn’t been (think the vanishingly small number of people who see a billboard and immediately buy a car within the next week when they weren’t otherwise going to do so) we’d have been forced to talk more about the other benefits. But we weren’t. So we lazily talked about the measured value, and about the measurability as a benefit and a differentiator.
The threats of relying on exact measurement
Not only do we leave a whole load of credit (read: cash) on the table, but it also leads to threats to measurability being seen as existential threats to digital marketing activity as a whole. We know that there are growing threats to measuring accurately, including regulatory, technological, and user-behavior shifts:
GDPR and other privacy regulations are limiting what we are allowed to do (and, as platforms catch up, what we can do)
Privacy features are being included in more products, added on by savvy consumers, or simply being set to be on by default more often, with even the biggest company in the world touting privacy as a core differentiator
Users continue to increase the extent to which they research and buy across multiple devices
Compared to early in Google’s rise, the lack of keyword-level analytics data and the rise of (not provided) means that we have far less visibility into the details than we used to when the narrative of measurability was being written
Now, imagine that the combination of these trends meant that you lost 100% of your analytics and data. Would it mean that your leads stopped? Would you immediately turn your website off? Stop marketing?
I suggest that the answer to all of that is “no.” There's a ton of value to digital marketing beyond the ability to track specific interactions.
We’re obviously not going to see our measurable insights disappear to zero, but for all the reasons I outlined above, it’s worth thinking about all the ways that our activities add value, how that value manifests, and some ways of proving it exists even if you can’t measure it.
How should we talk about value?
There are two pieces to the brand value puzzle:
Figuring out the value of increasing brand awareness or affinity
Understanding how our digital activities are changing said awareness or affinity
There's obviously a lot of research into brand valuations generally, and while it’s outside the scope of this piece to think about total brand value, it’s worth noting that some methodologies place as much as 75% of the enterprise value of even some large companies in the value of their brands:
Image source
My colleague Tom Capper has written about a variety of ways to measure changes in brand awareness, which attacks a good chunk of the second challenge. But challenge #1 remains: how do we figure out what it’s worth to carry out some marketing activity that changes brand awareness or affinity?
In a recent post, I discussed different ways of building marketing models and one of the methodologies I described might be useful for this - namely so-called “top-down” modelling which I defined as being about percentages and trends (as opposed to raw numbers and units of production).
The top-down approach
I’ve come up with two possible ways of modelling brand value in a transactional sense:
1. The Sherlock approach
“When you have eliminated the impossible, whatever remains, however improbable, must be the truth." - Sherlock Holmes
The outline would be to take the total new revenue acquired in a period. Subtract from this any elements that can be attributed to specific acquisition channels; whatever remains must be brand. If this is in any way stable or predictable over multiple periods, you can use it as a baseline value from which to apply the methodologies outlined above for measuring changes in brand awareness and affinity.
2. Aggressive attribution
If you run normal first-touch attribution reports, the limitations of measurement (clearing cookies, multiple devices etc) mean that you will show first-touch revenue that seems somewhat implausible (e.g. email; email surely can’t be a first-touch source — how did they get on your email list in the first place?):
http://ift.tt/2EBZMw3
0 notes
kraussoutene · 7 years
Text
The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
Posted by willcritchlow
Digital marketing is measurable.
It’s probably the single most common claim everyone hears about digital, and I can’t count the number of times I’ve seen conference speakers talk about it (heck, I’ve even done it myself).
I mean, look at those offline dinosaurs, the argument goes. They all know that half their spend is wasted — they just don’t know which half.
Maybe the joke’s on us digital marketers though, who garnered only 41% of global ad spend even in 2017 after years of strong growth.
Unfortunately, while we were geeking out about attribution models and cross-device tracking, we were accidentally triggering a common human cognitive bias that kept us anchored on small amounts, leaving buckets of money on the table and fundamentally reducing our impact and access to the C-suite.
And what’s worse is that we have convinced ourselves that it’s a critical part of what makes digital marketing great. The simplest way to see this is to realize that, for most of us, I very much doubt that if you removed all our measurement ability we’d reduce our digital marketing investment to nothing.
In truth, of course, we’re nowhere close to measuring all the benefits of most of the things we do. We certainly track the last clicks, and we’re not bad at tracking any clicks on the path to conversion on the same device, but we generally suck at capturing:
Anything that happens on a different device
Brand awareness impacts that lead to much later improvements in conversion rate, average order value, or lifetime value
Benefits of visibility or impressions that aren’t clicked
Brand affinity generally
The cognitive bias that leads us astray
All of this means that the returns we report on tend to be just the most direct returns. This should be fine — it’s just a floor on the true value (“this activity has generated at least this much value for the brand”) — but the “anchoring” cognitive bias means that it messes with our minds and our clients’ minds. Anchoring is the process whereby we fixate on the first number we hear and subsequently estimate unknowns closer to the anchoring number than we should. Famous experiments have shown that even showing people a totally random number can drag their subsequent estimates up or down.
So even if the true value of our activity was 10x the measured value, we’d be stuck on estimating the true value as very close to the single concrete, exact number we heard along the way.
This tends to result in the measured value being seen as a ceiling on the true value. Other biases like the availability heuristic (which results in us overstating the likelihood of things that are easy to remember) tend to mean that we tend to want to factor in obvious ways that the direct value measurement could be overstating things, and leave to one side all the unmeasured extra value.
The mistake became a really big one because fortunately/unfortunately, the measured return in digital has often been enough to justify at least a reasonable level of the activity. If it hadn’t been (think the vanishingly small number of people who see a billboard and immediately buy a car within the next week when they weren’t otherwise going to do so) we’d have been forced to talk more about the other benefits. But we weren’t. So we lazily talked about the measured value, and about the measurability as a benefit and a differentiator.
The threats of relying on exact measurement
Not only do we leave a whole load of credit (read: cash) on the table, but it also leads to threats to measurability being seen as existential threats to digital marketing activity as a whole. We know that there are growing threats to measuring accurately, including regulatory, technological, and user-behavior shifts:
GDPR and other privacy regulations are limiting what we are allowed to do (and, as platforms catch up, what we can do)
Privacy features are being included in more products, added on by savvy consumers, or simply being set to be on by default more often, with even the biggest company in the world touting privacy as a core differentiator
Users continue to increase the extent to which they research and buy across multiple devices
Compared to early in Google’s rise, the lack of keyword-level analytics data and the rise of (not provided) means that we have far less visibility into the details than we used to when the narrative of measurability was being written
Now, imagine that the combination of these trends meant that you lost 100% of your analytics and data. Would it mean that your leads stopped? Would you immediately turn your website off? Stop marketing?
I suggest that the answer to all of that is “no.” There's a ton of value to digital marketing beyond the ability to track specific interactions.
We’re obviously not going to see our measurable insights disappear to zero, but for all the reasons I outlined above, it’s worth thinking about all the ways that our activities add value, how that value manifests, and some ways of proving it exists even if you can’t measure it.
How should we talk about value?
There are two pieces to the brand value puzzle:
Figuring out the value of increasing brand awareness or affinity
Understanding how our digital activities are changing said awareness or affinity
There's obviously a lot of research into brand valuations generally, and while it’s outside the scope of this piece to think about total brand value, it’s worth noting that some methodologies place as much as 75% of the enterprise value of even some large companies in the value of their brands:
Image source
My colleague Tom Capper has written about a variety of ways to measure changes in brand awareness, which attacks a good chunk of the second challenge. But challenge #1 remains: how do we figure out what it’s worth to carry out some marketing activity that changes brand awareness or affinity?
In a recent post, I discussed different ways of building marketing models and one of the methodologies I described might be useful for this - namely so-called “top-down” modelling which I defined as being about percentages and trends (as opposed to raw numbers and units of production).
The top-down approach
I’ve come up with two possible ways of modelling brand value in a transactional sense:
1. The Sherlock approach
“When you have eliminated the impossible, whatever remains, however improbable, must be the truth." - Sherlock Holmes
The outline would be to take the total new revenue acquired in a period. Subtract from this any elements that can be attributed to specific acquisition channels; whatever remains must be brand. If this is in any way stable or predictable over multiple periods, you can use it as a baseline value from which to apply the methodologies outlined above for measuring changes in brand awareness and affinity.
2. Aggressive attribution
If you run normal first-touch attribution reports, the limitations of measurement (clearing cookies, multiple devices etc) mean that you will show first-touch revenue that seems somewhat implausible (e.g. email; email surely can’t be a first-touch source — how did they get on your email list in the first place?):
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The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
Posted by willcritchlow
Digital marketing is measurable.
It’s probably the single most common claim everyone hears about digital, and I can’t count the number of times I’ve seen conference speakers talk about it (heck, I’ve even done it myself).
I mean, look at those offline dinosaurs, the argument goes. They all know that half their spend is wasted — they just don’t know which half.
Maybe the joke’s on us digital marketers though, who garnered only 41% of global ad spend even in 2017 after years of strong growth.
Unfortunately, while we were geeking out about attribution models and cross-device tracking, we were accidentally triggering a common human cognitive bias that kept us anchored on small amounts, leaving buckets of money on the table and fundamentally reducing our impact and access to the C-suite.
And what’s worse is that we have convinced ourselves that it’s a critical part of what makes digital marketing great. The simplest way to see this is to realize that, for most of us, I very much doubt that if you removed all our measurement ability we’d reduce our digital marketing investment to nothing.
In truth, of course, we’re nowhere close to measuring all the benefits of most of the things we do. We certainly track the last clicks, and we’re not bad at tracking any clicks on the path to conversion on the same device, but we generally suck at capturing:
Anything that happens on a different device
Brand awareness impacts that lead to much later improvements in conversion rate, average order value, or lifetime value
Benefits of visibility or impressions that aren’t clicked
Brand affinity generally
The cognitive bias that leads us astray
All of this means that the returns we report on tend to be just the most direct returns. This should be fine — it’s just a floor on the true value (“this activity has generated at least this much value for the brand”) — but the “anchoring” cognitive bias means that it messes with our minds and our clients’ minds. Anchoring is the process whereby we fixate on the first number we hear and subsequently estimate unknowns closer to the anchoring number than we should. Famous experiments have shown that even showing people a totally random number can drag their subsequent estimates up or down.
So even if the true value of our activity was 10x the measured value, we’d be stuck on estimating the true value as very close to the single concrete, exact number we heard along the way.
This tends to result in the measured value being seen as a ceiling on the true value. Other biases like the availability heuristic (which results in us overstating the likelihood of things that are easy to remember) tend to mean that we tend to want to factor in obvious ways that the direct value measurement could be overstating things, and leave to one side all the unmeasured extra value.
The mistake became a really big one because fortunately/unfortunately, the measured return in digital has often been enough to justify at least a reasonable level of the activity. If it hadn’t been (think the vanishingly small number of people who see a billboard and immediately buy a car within the next week when they weren’t otherwise going to do so) we’d have been forced to talk more about the other benefits. But we weren’t. So we lazily talked about the measured value, and about the measurability as a benefit and a differentiator.
The threats of relying on exact measurement
Not only do we leave a whole load of credit (read: cash) on the table, but it also leads to threats to measurability being seen as existential threats to digital marketing activity as a whole. We know that there are growing threats to measuring accurately, including regulatory, technological, and user-behavior shifts:
GDPR and other privacy regulations are limiting what we are allowed to do (and, as platforms catch up, what we can do)
Privacy features are being included in more products, added on by savvy consumers, or simply being set to be on by default more often, with even the biggest company in the world touting privacy as a core differentiator
Users continue to increase the extent to which they research and buy across multiple devices
Compared to early in Google’s rise, the lack of keyword-level analytics data and the rise of (not provided) means that we have far less visibility into the details than we used to when the narrative of measurability was being written
Now, imagine that the combination of these trends meant that you lost 100% of your analytics and data. Would it mean that your leads stopped? Would you immediately turn your website off? Stop marketing?
I suggest that the answer to all of that is “no.” There's a ton of value to digital marketing beyond the ability to track specific interactions.
We’re obviously not going to see our measurable insights disappear to zero, but for all the reasons I outlined above, it’s worth thinking about all the ways that our activities add value, how that value manifests, and some ways of proving it exists even if you can’t measure it.
How should we talk about value?
There are two pieces to the brand value puzzle:
Figuring out the value of increasing brand awareness or affinity
Understanding how our digital activities are changing said awareness or affinity
There's obviously a lot of research into brand valuations generally, and while it’s outside the scope of this piece to think about total brand value, it’s worth noting that some methodologies place as much as 75% of the enterprise value of even some large companies in the value of their brands:
Image source
My colleague Tom Capper has written about a variety of ways to measure changes in brand awareness, which attacks a good chunk of the second challenge. But challenge #1 remains: how do we figure out what it’s worth to carry out some marketing activity that changes brand awareness or affinity?
In a recent post, I discussed different ways of building marketing models and one of the methodologies I described might be useful for this - namely so-called “top-down” modelling which I defined as being about percentages and trends (as opposed to raw numbers and units of production).
The top-down approach
I’ve come up with two possible ways of modelling brand value in a transactional sense:
1. The Sherlock approach
“When you have eliminated the impossible, whatever remains, however improbable, must be the truth." - Sherlock Holmes
The outline would be to take the total new revenue acquired in a period. Subtract from this any elements that can be attributed to specific acquisition channels; whatever remains must be brand. If this is in any way stable or predictable over multiple periods, you can use it as a baseline value from which to apply the methodologies outlined above for measuring changes in brand awareness and affinity.
2. Aggressive attribution
If you run normal first-touch attribution reports, the limitations of measurement (clearing cookies, multiple devices etc) mean that you will show first-touch revenue that seems somewhat implausible (e.g. email; email surely can’t be a first-touch source — how did they get on your email list in the first place?):
Click for a larger version
In this screenshot we see that although first-touch dramatically reduces the influence of direct, for instance, it still accounts for more than 15% of new revenue.
The aggressive attribution model takes total revenue and splits it between the acquisition channels (unbranded search, paid social, referral). A first pass on this would simply split it in the relative proportion to the size of each of those channels, effectively normalizing them, though you could build more sophisticated models.
Note that there is no way of perfectly identifying branded/unbranded organic search since (not provided) and so you’ll have to use a proxy like homepage search vs. non-homepage search.
But fundamentally, the argument here would be that any revenue coming from a “first touch” of:
Branded search
Direct
Organic social
Email
...was actually acquired previously via one of the acquisition channels and so we attempt to attribute it to those channels.
Even this under-represents brand value
Both of those methodologies are pretty aggressive — but they might still under-represent brand value. Here are two additional mechanics where brand drives organic search volume in ways I haven’t figured out how to measure yet:
Trusting Amazon to rank
I like reading on the Kindle. If I hear of a book I’d like to read, I’ll often Google the name of the book on its own and trust that Amazon will rank first or second so I can get to the Kindle page to buy it. This is effectively a branded search for Amazon (and if it doesn’t rank, I’ll likely follow up with a [book name amazon] search or head on over to Amazon to search there directly).
But because all I’ve appeared to do is search [book name] on Google and then click through to Amazon, there is nothing to differentiate this from an unbranded search.
Spotting brands you trust in the SERPs
I imagine we all have anecdotal experience of doing this: you do a search and you spot a website you know and trust (or where you have an account) ranking somewhere other than #1 and click on it regardless of position.
One time that I can specifically recall noticing this tendency growing in myself was when I started doing tons more baby-related searches after my first child was born. Up until that point, I had effectively zero brand affinity with anyone in the space, but I quickly grew to rate the content put out by babycentre (babycenter in the US) and I found myself often clicking on their result in position 3 or 4 even when I hadn’t set out to look for them, e.g. in results like this one:
It was fascinating to me to observe this behavior in myself because I had no real interaction with babycentre outside of search, and yet, by consistently ranking well across tons of long-tail queries and providing consistently good content and user experience I came to know and trust them and click on them even when they were outranked. I find this to be a great example because it is entirely self-contained within organic search. They built a brand effect through organic search and reaped the reward in increased organic search.
I have essentially no ideas on how to measure either of these effects. If you have any bright ideas, do let me know in the comments.
Budgets will come under pressure
My belief is that total digital budgets will continue to grow (especially as TV continues to fragment), but I also believe that individual budgets are going to come under scrutiny and pressure making this kind of thinking increasingly important.
We know that there is going to be pressure on referral traffic from Facebook following the recent news feed announcements, but there is also pressure on trust in Google:
Before the recent news feed changes, slightly misleading stories had implied that Google had lost the top spot as the largest referrer of traffic (whereas in fact this was only briefly true in media)
The growth of the mobile-first card view and richer and richer SERPs has led to declines in outbound CTR in some areas
The increasingly black-box nature of Google’s algorithm and an increasing use of ML make the algorithm increasingly impenetrable and mean that we are having to do more testing on individual sites to understand what works
While I believe that the opportunity is large and still growing (see, for example, this slide showing Google growing as a referrer of traffic even as CTR has declined in some areas), it’s clear that the narrative is going to lead to more challenging conversations and budgets under increased scrutiny.
Can you justify your SEO investment?
What do you say when your CMO asks what you’re getting for your SEO investment?
What do you say when she asks whether the organic search opportunity is tapped out?
I’ll probably explore the answers to both these questions more in another post, but suffice it to say that I do a lot of thinking about these kinds of questions.
The first is why we have built our split-testing platform to make organic SEO investments measurable, quantifiable and accountable.
The second is why I think it’s super important to remember the big picture while the media is running around with hair on fire. Media companies saw Facebook overtake Google as a traffic channel (and then are likely seeing that reverse right now), but most of the web has Google as the largest and growing source of traffic and value.
The reality (from clickstream data) is that it's really easy to forget how long the long-tail is and how sparse search features and ads are on the extreme long-tail:
Only 3–4% of all searches result in a click on an ad, for example. Google's incredible (and still growing) business is based on a small subset of commercial searches
Google's share of all outbound referral traffic across the web is growing (and Facebook's is shrinking as they increasingly wall off their garden)
The opportunity is for smart brands to capitalize on a growing opportunity while their competitors sink time and money into a social space that is increasingly all about Facebook, and increasingly pay-to-play.
What do you think? Are you having these hard conversations with leadership? How are you measuring your digital brand’s value?
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lawrenceseitz22 · 7 years
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The Biggest Mistake Digital Marketers Ever Made: Claiming to Measure Everything
Posted by willcritchlow
Digital marketing is measurable.
It’s probably the single most common claim everyone hears about digital, and I can’t count the number of times I’ve seen conference speakers talk about it (heck, I’ve even done it myself).
I mean, look at those offline dinosaurs, the argument goes. They all know that half their spend is wasted — they just don’t know which half.
Maybe the joke’s on us digital marketers though, who garnered only 41% of global ad spend even in 2017 after years of strong growth.
Unfortunately, while we were geeking out about attribution models and cross-device tracking, we were accidentally triggering a common human cognitive bias that kept us anchored on small amounts, leaving buckets of money on the table and fundamentally reducing our impact and access to the C-suite.
And what’s worse is that we have convinced ourselves that it’s a critical part of what makes digital marketing great. The simplest way to see this is to realize that, for most of us, I very much doubt that if you removed all our measurement ability we’d reduce our digital marketing investment to nothing.
In truth, of course, we’re nowhere close to measuring all the benefits of most of the things we do. We certainly track the last clicks, and we’re not bad at tracking any clicks on the path to conversion on the same device, but we generally suck at capturing:
Anything that happens on a different device
Brand awareness impacts that lead to much later improvements in conversion rate, average order value, or lifetime value
Benefits of visibility or impressions that aren’t clicked
Brand affinity generally
The cognitive bias that leads us astray
All of this means that the returns we report on tend to be just the most direct returns. This should be fine — it’s just a floor on the true value (“this activity has generated at least this much value for the brand”) — but the “anchoring” cognitive bias means that it messes with our minds and our clients’ minds. Anchoring is the process whereby we fixate on the first number we hear and subsequently estimate unknowns closer to the anchoring number than we should. Famous experiments have shown that even showing people a totally random number can drag their subsequent estimates up or down.
So even if the true value of our activity was 10x the measured value, we’d be stuck on estimating the true value as very close to the single concrete, exact number we heard along the way.
This tends to result in the measured value being seen as a ceiling on the true value. Other biases like the availability heuristic (which results in us overstating the likelihood of things that are easy to remember) tend to mean that we tend to want to factor in obvious ways that the direct value measurement could be overstating things, and leave to one side all the unmeasured extra value.
The mistake became a really big one because fortunately/unfortunately, the measured return in digital has often been enough to justify at least a reasonable level of the activity. If it hadn’t been (think the vanishingly small number of people who see a billboard and immediately buy a car within the next week when they weren’t otherwise going to do so) we’d have been forced to talk more about the other benefits. But we weren’t. So we lazily talked about the measured value, and about the measurability as a benefit and a differentiator.
The threats of relying on exact measurement
Not only do we leave a whole load of credit (read: cash) on the table, but it also leads to threats to measurability being seen as existential threats to digital marketing activity as a whole. We know that there are growing threats to measuring accurately, including regulatory, technological, and user-behavior shifts:
GDPR and other privacy regulations are limiting what we are allowed to do (and, as platforms catch up, what we can do)
Privacy features are being included in more products, added on by savvy consumers, or simply being set to be on by default more often, with even the biggest company in the world touting privacy as a core differentiator
Users continue to increase the extent to which they research and buy across multiple devices
Compared to early in Google’s rise, the lack of keyword-level analytics data and the rise of (not provided) means that we have far less visibility into the details than we used to when the narrative of measurability was being written
Now, imagine that the combination of these trends meant that you lost 100% of your analytics and data. Would it mean that your leads stopped? Would you immediately turn your website off? Stop marketing?
I suggest that the answer to all of that is “no.” There's a ton of value to digital marketing beyond the ability to track specific interactions.
We’re obviously not going to see our measurable insights disappear to zero, but for all the reasons I outlined above, it’s worth thinking about all the ways that our activities add value, how that value manifests, and some ways of proving it exists even if you can’t measure it.
How should we talk about value?
There are two pieces to the brand value puzzle:
Figuring out the value of increasing brand awareness or affinity
Understanding how our digital activities are changing said awareness or affinity
There's obviously a lot of research into brand valuations generally, and while it’s outside the scope of this piece to think about total brand value, it’s worth noting that some methodologies place as much as 75% of the enterprise value of even some large companies in the value of their brands:
Image source
My colleague Tom Capper has written about a variety of ways to measure changes in brand awareness, which attacks a good chunk of the second challenge. But challenge #1 remains: how do we figure out what it’s worth to carry out some marketing activity that changes brand awareness or affinity?
In a recent post, I discussed different ways of building marketing models and one of the methodologies I described might be useful for this - namely so-called “top-down” modelling which I defined as being about percentages and trends (as opposed to raw numbers and units of production).
The top-down approach
I’ve come up with two possible ways of modelling brand value in a transactional sense:
1. The Sherlock approach
“When you have eliminated the impossible, whatever remains, however improbable, must be the truth." - Sherlock Holmes
The outline would be to take the total new revenue acquired in a period. Subtract from this any elements that can be attributed to specific acquisition channels; whatever remains must be brand. If this is in any way stable or predictable over multiple periods, you can use it as a baseline value from which to apply the methodologies outlined above for measuring changes in brand awareness and affinity.
2. Aggressive attribution
If you run normal first-touch attribution reports, the limitations of measurement (clearing cookies, multiple devices etc) mean that you will show first-touch revenue that seems somewhat implausible (e.g. email; email surely can’t be a first-touch source — how did they get on your email list in the first place?):
Click for a larger version
In this screenshot we see that although first-touch dramatically reduces the influence of direct, for instance, it still accounts for more than 15% of new revenue.
The aggressive attribution model takes total revenue and splits it between the acquisition channels (unbranded search, paid social, referral). A first pass on this would simply split it in the relative proportion to the size of each of those channels, effectively normalizing them, though you could build more sophisticated models.
Note that there is no way of perfectly identifying branded/unbranded organic search since (not provided) and so you’ll have to use a proxy like homepage search vs. non-homepage search.
But fundamentally, the argument here would be that any revenue coming from a “first touch” of:
Branded search
Direct
Organic social
Email
...was actually acquired previously via one of the acquisition channels and so we attempt to attribute it to those channels.
Even this under-represents brand value
Both of those methodologies are pretty aggressive — but they might still under-represent brand value. Here are two additional mechanics where brand drives organic search volume in ways I haven’t figured out how to measure yet:
Trusting Amazon to rank
I like reading on the Kindle. If I hear of a book I’d like to read, I’ll often Google the name of the book on its own and trust that Amazon will rank first or second so I can get to the Kindle page to buy it. This is effectively a branded search for Amazon (and if it doesn’t rank, I’ll likely follow up with a [book name amazon] search or head on over to Amazon to search there directly).
But because all I’ve appeared to do is search [book name] on Google and then click through to Amazon, there is nothing to differentiate this from an unbranded search.
Spotting brands you trust in the SERPs
I imagine we all have anecdotal experience of doing this: you do a search and you spot a website you know and trust (or where you have an account) ranking somewhere other than #1 and click on it regardless of position.
One time that I can specifically recall noticing this tendency growing in myself was when I started doing tons more baby-related searches after my first child was born. Up until that point, I had effectively zero brand affinity with anyone in the space, but I quickly grew to rate the content put out by babycentre (babycenter in the US) and I found myself often clicking on their result in position 3 or 4 even when I hadn’t set out to look for them, e.g. in results like this one:
It was fascinating to me to observe this behavior in myself because I had no real interaction with babycentre outside of search, and yet, by consistently ranking well across tons of long-tail queries and providing consistently good content and user experience I came to know and trust them and click on them even when they were outranked. I find this to be a great example because it is entirely self-contained within organic search. They built a brand effect through organic search and reaped the reward in increased organic search.
I have essentially no ideas on how to measure either of these effects. If you have any bright ideas, do let me know in the comments.
Budgets will come under pressure
My belief is that total digital budgets will continue to grow (especially as TV continues to fragment), but I also believe that individual budgets are going to come under scrutiny and pressure making this kind of thinking increasingly important.
We know that there is going to be pressure on referral traffic from Facebook following the recent news feed announcements, but there is also pressure on trust in Google:
Before the recent news feed changes, slightly misleading stories had implied that Google had lost the top spot as the largest referrer of traffic (whereas in fact this was only briefly true in media)
The growth of the mobile-first card view and richer and richer SERPs has led to declines in outbound CTR in some areas
The increasingly black-box nature of Google’s algorithm and an increasing use of ML make the algorithm increasingly impenetrable and mean that we are having to do more testing on individual sites to understand what works
While I believe that the opportunity is large and still growing (see, for example, this slide showing Google growing as a referrer of traffic even as CTR has declined in some areas), it’s clear that the narrative is going to lead to more challenging conversations and budgets under increased scrutiny.
Can you justify your SEO investment?
What do you say when your CMO asks what you’re getting for your SEO investment?
What do you say when she asks whether the organic search opportunity is tapped out?
I’ll probably explore the answers to both these questions more in another post, but suffice it to say that I do a lot of thinking about these kinds of questions.
The first is why we have built our split-testing platform to make organic SEO investments measurable, quantifiable and accountable.
The second is why I think it’s super important to remember the big picture while the media is running around with hair on fire. Media companies saw Facebook overtake Google as a traffic channel (and then are likely seeing that reverse right now), but most of the web has Google as the largest and growing source of traffic and value.
The reality (from clickstream data) is that it's really easy to forget how long the long-tail is and how sparse search features and ads are on the extreme long-tail:
Only 3–4% of all searches result in a click on an ad, for example. Google's incredible (and still growing) business is based on a small subset of commercial searches
Google's share of all outbound referral traffic across the web is growing (and Facebook's is shrinking as they increasingly wall off their garden)
The opportunity is for smart brands to capitalize on a growing opportunity while their competitors sink time and money into a social space that is increasingly all about Facebook, and increasingly pay-to-play.
What do you think? Are you having these hard conversations with leadership? How are you measuring your digital brand’s value?
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