If you didn’t know, for the past 18 months or so I’ve been hosting a podcast with the inimitable Jill Royce on the topic of ad-tech history. It’s called #PaleoAdTech and we’ve been blessed with a roster of ad-tech titans, from the pinballing pioneers of the dot-com days — now-forgotten blazers like AllAdvantage, AdAuction and FlyCast; and well-remembered disrupters like DoubleClick and Advertising.com — to the makers of a more recent past, like AppNexus and MediaMath.
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A version of this purr-fect article originally appeared in The Drum on Feb. 13, 2023, a few days after Super Bowl LVII aired. A picture of my photogenic muse Jerry appeared at the end (as it does below).
While some people say the Super Bowl was a close game, it really wasn’t. Dogs totally dominated cats in the USA Today AdMeter poll.
The Farmer’s Dog came in first with a time-travel tail – uh, tale – that showed just how good dogs are at nuzzling our emotions. Amazon’s bad-dog-turned-angel saga took third.
And where were all the spokescats? Not feline the love. One provided a whisker of comic relief in a Google Pixel ad, where a sour puss pointedly removes a dog from a photo with AI. Probably out of jealously.
It turns out, there’s a good reason for the double-standard. Cats and dogs evoke different emotions in people and can be used to inspire specific actions in marketing.
Dog actors actually inspire us to make connections, take risks, and share our personal space
Cat actors put us in mind to purr-chase more insurance, protect our homes and families, and prep for doomsday
So says a first-of-its-kind study which tries to quantify the impact of cat and dog talent on consumer behavior.
Dogs Say YOLO, Cats Say YOWL
Half of U.S. households have a dog and one-third have a cat – a number that continues to grow. One in five households even found a new furry friend to rescue them during lockdown.
And we are big spenders, not just on our pets. Pet owners tend to be more affluent, healthier, more confident, even better-looking (meow).
Pets appear often in entertainment, from Puss in Boots to every perfect-family-with-an-SUV TV spot, especially if it’s in the snow (cue adorable baby Bernese mountain dog). But the impact of our four-footed friends on our attitudes and behaviors hasn’t really been clawed over until recently.
The current study – a collaboration among universities in the U.S. and Hong Kong – wasn’t yet another meme about cat-people vs dog-people. It showed that dogs and cats actually evoke a chain of emotions in most consumers that is both different and predictable. They prime the message pump.
For decades now, many researchers have adopted an idea called regulatory focus theory, which claims there are two basic consumer mindsets:
Promotion – focusing on gains, success, YOLO, being all that we can be
Prevention – focusing on safety, preserving what we have, personal security, avoiding risks
Now we consumers aren’t all one or the other – except in the case of some fussy outliers – but have a mindset that can be shifted by social cues and marketing messages … which brings us to pets.
”This stream of research suggests that a promotion-oriented eagerness system better captures dogs’ temperaments and behavioral characteristics, whereas a prevention-focused cautious system better describes cats’ temperaments and behavioral characteristics.”
In fact, advertisers already intuited the study’s findings before it appeared. (And they exhibit a subtle anti-cat bias, which cats will remember when they take over the world.)
Cats are often used in dark and dyspeptic scenarios:
Wells Fargo demonstrating “suspicious activity” on cards, pushing alerts
Sainsbury’s (U.K.) Mog the Cat, disappointed by an empty dinner bowl at Christmas, warning us to shop early
That alarming All-State ad where Mayhem cat-thropomorphizes from human to feline while his home decomposes around him
Meanwhile, of course, dogs tag along with kids in the sunshine and spread nothing but golden light and joy:
Wells Fargo, this time with Regina King and a golden retriever promoting a cash-back rewards card
Subaru Ascent … which featured no fewer than seven adorable goldens outside a condo sign-posted “The Barkeleys” and … I rest my case.
Cats, Fight Plaque!
The researchers got their human test subjects primed with dog (or cat) questions and images, putting them into the promotion (or prevention) mindspace. Then they asked them if they would buy toothpaste that would “freshen breath” (or “fight plaque”).
Not surprisingly, the dog-primed promotion-focused pack preferred the fresh-breath feature. The cat-primed prevention-focused pride wanted to take a swipe at that plaque.
Other scenarios found that the dog-primed pack was significantly more likely to:
Participate in a lottery
Buy stocks (vs funds)
Buy vitamins that made wellness (vs prevention) claims
On the other paw, the cat-primed group was more likely to:
Stay away from high-flying but risky stocks
Put a higher value on preventative health services
Spend more for products with prevention claims
The experiments controlled for factors like personal pet ownership, preferences and even mood. So again, it’s not just more cat-people-are-shy propaganda. Rather, it’s evidence that there is some stereotypical behavior in animals that triggers semi-unconscious associations in people. These associations in turn nudge consumers into a particular general mindset, which can bolster certain messages.
So now we have some guidelines for our feline- and canine-themed campaigns. That’s something to howl (or meow) about.
We’re at the Rosewood Sand Hill, optimally close to Kleiner Perkins and the banks that whisper out our future like the oracles of air. No conspicuous consumption; in fact, we’ve moved beyond consumption into non-consumption, all electric and non-meat, so faithful are we to our own shared abundance.
And onto the stage comes a slightly seedy character, no longer young, ironic in the way of the 1990s, inhabiting a gestalt that’s gone. It’s me, in fact: about to argue yet again the importance of forgotten history to a room full of futurists. This is what you may have missed …
1. We Start with Netscape
The internet predates the browser, but the browser was the box on which we built the web. Before Mosaic and – more significantly – its virtual spin-out Netscape, launched in 1994, the internet consisted of academic cultists and gardens like AOL and CompuServe with walls so high they blocked out the sun; they weren’t the answer.
Mosaic was “achingly beautiful,” in the words of Vint Cerf, a project emerging from protocols developed by the British physicist Tim Berners-Lee (HTML, HTTP). Mosaic put images on the web, after a battle. It made hypertext easy. Developed by unpretentious hackers at the University of Illinois’ National Center for Supercomputing Applications (NCSA), it was profiled in the New York Times, which failed to mention its actual makers, Marc Andreessen and Eric Bina.
Thus stung by lab politics, Andreessen and then Bina and others agreed to join Silicon Graphics’ founder Jim Clark in the Bay Area to build a better Mosaic. It went public in 1995 and started the dot-com boom, through no fault of its own. Everybody was excited by Netscape; especially Microsoft, which promptly tried to bury it.
And while the academic internet was explicitly anti-commercial, Netscape was not. Nor were many of the publications that bravely stood up online, such as HotWired.com, the digital porting of the digiterati’s lifestyle manual: Wired magazine. Portals like Jerry Yang and David Filo’s link roster Yahoo! were initially anti-ad – as was Google at launch, five years later, — but ads got inevitable. From the beginning, nobody seemed to want to subscribe to bits on a screen or use a credit card online.
Ads were the only way to pay.
On the Netscape homepage was an early “live cam” (updated every few seconds) of a fishtank. It sat on the desk of a 24 year-old engineer named Lou Montulli. Now Lou was not part of the original NCSA cadre but was merited in due to his popular text browser Lynx, written while he worked the help desk part time in the Computer Lab at the University of Kansas, between racquetball games.
And Montulli of course – as everyone who has followed me since my Gartner days knows – invented the browser cookie. As he told me, it was to enable a shopping cart in the stateless-by-design internet, and immediate adoption by ad workers was not in the plan. Montulli decided to enable third-party cookies by default not because he wanted to invade anyone’s privacy but quite the opposite: he wanted the whole thing to be unobtrusive and transparent.
In other words, he made the engineer’s mistake of assuming that because a feature exists (we have always had the power to turn off our cookies), it actually exists. In fact, nobody bothered to look.
Lesson #1: Whoever owns the browser software, controls the Internet (i.e., Apple, Google).
2. The Dot-Com Ad Network Boom
In the 1990s, everything was an ad network. There was no real-time bidding on anything, and even big publishers didn’t have a big online ad business. Scaled large websites like NYTimes.com and WSJ.com weren’t scaled enough to attract TV money, at first, and smaller websites (i.e., everyone else) had neither staff nor knowledge, buyers nor technology, to extract rents from the web on their own.
So we have the ad networks, which do the work of signing up lots of publishers so they can go to ad buyers and offer them something they might actually want – millions of impressions across thousands of websites, never mind where. A natural extension of this middleperson model is the software that sits between publishers, ad buyers and agencies, deciding which ads to run, when, and counting what occurs.
This software is called an ad server, and many ad networks built their own ad servers, or tried, until the leaders emerged. This emergence happened quickly: by 1996, DoubleClick was dominant, and when it acquired on-premise rival NetGravity in 1999, it was super-dominant. People forget DoubleClick started as an ad network, and its ad server was a tool for the sellers. SaaS as a margin machine wasn’t real until the Y2K.
DoubleClick had the virtue of swagger; it was unapologetic in its quest for excess. Its hyper-charismatic, raven-haired co-founder Kevin O’Connor threw out business plans that were too cautious: “How does that lead to total domination?!” DoubleClickers loved him, and everyone in New York media wanted to work at DoubleClick in 1999. I tell you this from memory.
Silicon Alley – triangulated roughly around the Flatiron region, cheaper than midtown and convenient to the R and 6 – was a publicists’ pitch pushed by DoubleClick and the city of New York. The company’s logo was on just about every lamppost in lower Manhattan. Skywriters flew over beaches in the Hamptons telling ad buyers their campaigns were safe, the machines were on it.
And they were. Business was built – again, absolutely openly – on the compilation of a file against every DoubleClick cookie and I.P. address, appended with third-party data like location. With almost every premium publisher in its network, DoubleClick had a cookie on all our browsers, and so read much (not all) of our etheric adventures.
It was only when O’Connor acquired Abakus to insert real names and addresses into the pseudonymous cookie profile did USA Today, and then everyone else, raise a hand. But this was in 2000-01, when we all had other problems.
There was one outlier, a brave ad network that took a principled stand against dropping third-party cookies on browsers, for privacy reasons. It was a sortie that did not connect. In the 1990s, WebConnect was most definitely on the wrong side of history.
Lesson #2: Ad dollars flow to places with more information, not better ethics.
3. The Rise of Retargeting
Retargeting is the killer app for digital ads.
There is a very simple reason for this: it works.
In the 2000’s, ads targeted based on specific things we did in our browsers got at least 3X better engagement than non-retargeted ads, however we measured. Of course, many people claim to have invented this miracle-grow: Advertising.com, TACODA, MySpace, Criteo, BlueLithium/Yahoo. But it seems to have been invented quite naturally by DoubleClick, sometime around the dot-com crash.
Retargeting works, but it has a signal flaw. It is very easy to notice. In fact, we might say most civilians did not even suspect the persistence of cookies and targeted ads until retargeting gave them a clue.
Slowly at first, and then with more persistent vigor and rage, the ad-that-followed-me combined with a generalized uptick in paranoia to create a climate of conspiracy around the ad business. We went from being Mad Men to madmen with malodorous intent.
We have the spectacle, in the later 2000’s, of otherwise circumspect journalists reporting their businesses closer to the grave with richly-researched deep dives under ominous titles such as “The Privacy Project” (“I Visited 47 Sites. Hundreds of Trackers Followed Me” – New York Times) and “What They Know” (“They Know What You’re Shopping For” – Wall Street Journal).
Web surfing for the cultural elite assumed the soundtrack of a horror film. Yes, they probably do know what you did last summer.
Looking at Google Trends data over the past two decades, interest in ‘tracking’ has indeed swelled – even as interest in a randomly-selected fad (in this case: ‘Bieber,’ in red) has fallen off the cyber-cliff.
Lesson #3: In the long run, it is more profitable to be gentle with your superpowers.
4. The Epochal Moment Called 2018
Everything changed in 2018. Certainly Snowden had an impact, five years earlier, but his concerns were largely abstract, existential and political. He and his outraged adherents had much more important things on their minds than mere ads.
Which brings us to Mark Zuckerberg. He appeared in front of two Senate committees two years after the 2016 presidential election and some time after a German magazine revealed Facebook had given unredacted network data to a Cambridge researcher, who’d sold it to a conservative consulting firm called Cambridge Analytica. (Meta settled this case only last month, by the way.)
Nothing happened out of the senators’ naive posturing, but an estimated 80 million people saw part of the hearings – and everyone knew they were on. This was a yellow-card moment in digital; another ping at the populus. This time, for the first time, we started to look at our phones with suspicion. Our apps were watching us too.
By no coincidence, 2018 was also the year that digital ad spend overtook offline – that is, digital won – and the share of the triopoly (Google, Meta, Amazon) exceeded 80/20, including search. Digital became the dominant dimension in ads, and a handful of mastodons maneuvered for control.
Zuckerberg’s appearance in 2018 almost forced Apple to do what it did, two years later.
Intelligent Tracking Prevention (ITP) and the App Tracking Transparency framework (ATT) flexed the power of the browser and OS owner. We noted this with Netscape, and we see it again. Google was peer-pressured into blog posts and a Privacy Sandbox of professorial interest, while Apple filled a vacuum left by our Congress, appointing itself Neighborhood Watch for the World Wide Web.
Two things to mention here:
One, Apple’s specific tactics aren’t as important as its heuristic decision to make data collection contingent on an explicit opt-in by the user. We need to say “Yes.” Which makes sense until we ask the logical question: “Yes to what?” And we’re caught in the sepulchral eddy of the Privacy Paradox, which states that it’s almost impossible to make an intelligent decision about whether we do or do not want to “opt in” to collection of … what? … for what purpose? … and by whom?
Most of us don’t care. We click yes or no depending on our prejudice. (I always click yes.) Also, whether we’ve heard of the brand. And we’re grandfathered into the big apps like Amazon, Instagram, Facebook, TikTok. In fact, we have no idea what they know, and they don’t really have to tell us.
Two, nobody wants untargeted ads. Trust me on this. We might romanticize an experience of anonymity, but I challenge you to live it – as I did, — disable your trackers, obscure your I.P., use a VPN, and just look at the ads you’re served up: a late-night-cable-TV hodgepodge of personal pizza, car caddies, weight loss lies and class-action lawsuits.
Irrelevance has never been so loud.
Lesson #4: Apple is taking the place of a well-ordered Government today.
5. What’s Coming Next
As much as we crave good direction, howling in despair, the ad market still obeys its formulas. We need addressability and accountability; targeting and measurement. We target based on real information, inferred information, at a person- or a cohort-level, and then there is context (time, publisher, page, device). Measurement is an art form in itself and has never been exactly precise.
Building a campaign, we start closest to the point of decision – if we can – and build out from there; again, starting with those places where we have the most control, or think we have. So many times we start with paid search because it’s (1) close to the point of decision, and (2) in our control. We’ll overpay to meet these criteria. And so on, out into the wild terrain of unknown ad networks and disconnected TV.
Given the principles of proximity to a sale and greater information, where do we look?
Until it perfects its in-app storefront, Facebook/Instagram is hampered by its distance from the end zone. That’s why it needed the mobile ad ID (MAID). So-called retail media – which is living its own wonder years right now – can place ads close to the point of purchase and record a sale. It’s an ideal environment limited only by immature tech (in most cases) and the narrow data sets.
And it seems very safe to me to say that we are in desperate need of new ad formats.
Paid search is the most successful, and it was entirely unpredicted. Banner ads feel like a retreat to the mean. McLuhan tells us the content of any medium is always another medium. Digital is growing up and out of that, at last.
Look at the #Influencer phenomenon, reaching perhaps $13 billion this year. Those are blatant product pushes, in our pockets, from figures not too proud to beg – and they work. That’s digital for you. What about product placement? Imagine tools that paint products into sets (and eventually dialogue) without a seam. They’re coming soon. I call these “non-ad ad formats.”
Soon we’ll all just call them ads-as-usual.
So where does that leave the hard-working brand? You know that you need first-party data, but it doesn’t have to be your own. If you have it, scale it; get a Customer Data Platform (CDP). If you don’t, you’ll just need to ride along with someone else’s, once Montulli’s cookie’s gone. Don’t worry, though: those ‘someone else’s’ (Amazon, Disney, NBCU, Uber) – they all know you’re coming.
They’ll be ready. There will always be a way to advertise.
Taylor Swift has a way of breaking things: records, superlatives, hearts, and even – when she committed the previously inconceivable magic of occupying all ten spots on the Billboard Top 10 with tracks from her 10th album Midnights – herself:
She also broke Ticketmaster, apparently startled by demand for the 2.5 million tickets available for her 52-city ‘The Eras’ tour, her first since 2018.
“It’s a function of Taylor Swift,” said the CEO of the largest shareholder in Live Nation/Ticketmaster’s on CNBC. “We had 14 million people hit the site, including bots….” Even non-humans love Swift.
What’s her secret? After Midnight dropped at, of course, midnight on October 21st, Swift became the most-streamed artist with the most-streamed album in a day on Spotify, breaking records set by her own Red (Taylor’s Version) and 2020’s folklore.
By now, it’s clear Taylor Swift’s only rival is herself.
“Taylor Swift is nearly unimpeachable as a human, role model and brand,” Aaron Kwittken, Chief Executive of the PRophet, told The Drum recently.
As a brand – setting aside her artistry for a moment – Taylor Swift is a global phenomenon. Capital One, Target, Starbucks, Keds, CoverGirl, Diet Coke, Apple, Comcast, American Greetings – just a partial list of partners who have contributed to her estimated $400 million net worth in recent years.
Make no mistake; she’s a marketing engine. And it turns out brand Taylor Swift has a definite playbook, refined over her fifteen-year career. She still has a lot to teach marketers.
1. Be an Anti-Brand
The first single from the 13-song Midnights was called “Anti-Hero,” which Swift claims is about her “insecurities.” (Remember that number 13: it’s important.) In many ways, Taylor Swift is an Anti-Brand.
Traditional branding calls for a definite identity, promise and voice. It requires research-driven lines in the “brand space.” But Taylor Swift doesn’t have these things – she’s more of a “Blank Space” on which any of us, no matter how different, can see anything we need to see, especially ourselves.
Earlier this month, Midnights sponsor Capital One revealed two spots for the World Series called “Multiple Taylors,” featuring versions of Swift from 1989, Speak Now and others. It recalled the cryptic video for her song “Look What You Made Me Do,” from Reputation, unleashed at the 2017 MTV Video Music Awards, which featured fifteen versions of Swift, from the Red ringmaster to the stunned victim of Kanye’s notorious trophy-snatching.
She dared to ask us: “Who is the real Taylor Swift?” And the answer: We all are, pick the one you want.
She’s an oddly malleable brand, ideally suited to an age of creators, remixes and memes. It makes sense that there are multiple versions of two of her albums, with at least four more to come. Another celebrity, Ryan Adams, famously rerecorded her entire 1989 himself.
And then there are the lookalikes: it’s possible to become TikTok famous just for looking a little bit like Swift. And the oddly Teflonish quality: famous people who seem to want to feud with Swift somehow end up fading away (like Katy Perry) or on stage at one of her shows singing a duet (like Hayley Kiyoko), best friends forever.
Sociologist Emile Durkheim talked about totems as supernatural objects within which tribes can see themselves. Brands like Taylor Swift are totems for the age of TikTok.
2. Make Your Fans Do Work
It’s not easy being a fan of Taylor Swift; just ask us. Between buying $75 pajamas at her Official Store, waiting on virtual lines that break, and pre-ordering 13 copies of the expanded 20-song Midnights (3am Edition), there’s barely time to decipher all the clues she’s left in her TikToks, lyrics and Insta captions.
Mainstream fans might not know it, but Swift has long embedded Baroque ciphers into her marketing materials. She does this to encourage social media action, conversation, digital engagement – and of course to repay our attention.
Swift’s code-work started early. Her first album, Taylor Swift, released in 2006 when she was 16, featured liner notes with random capital letters, embedding messages like “Date Nice Boys.” She told the Washington Post: “That’s how it started, and my fans and I have since descended into color coding, numerology, word searches, elaborate hints, and Easter eggs.”
Examples abound – so many, in fact, that at least one commentator has ranted that “people treat Taylor Swift’s albums like they’re the damn Da Vinci code!”
Many of these Easter eggs are simply rewards for the faithful, references to outfits and props from previous albums. In the video for “Anti-Hero,” a stand-in breaks a guitar from the Speak Now tour, and a character wears a dress from Fearless. Others are aimed at completists: there are four versions of the vinyl album cover for Midnights that can be tiled to build a clock.
In her more Gothic Reputation phase, Swift packed the video for her first single with references to Mean Girls, her “Out of the Woods” video, a dollar bill she won in a notorious lawsuit, snakes and tea referring to various Kardashians, and so on.
It’s all harmless fun but can get hyperbolic in an overwired age. Swift’s fans often work harder than required, locating clues that aren’t actually there. Last September, the NFL made the mistake of issuing an announcement at midnight. Immediately, Swift’s conspiracy-minded cadre built a widely-reported rumor that Swift herself was going to be the half-time show at the Super Bowl because – well, of course – Taylor Swift owns midnight.
The announcement had nothing to do with Swift. Sometimes midnight is just midnight. (Rhianna is doing the half-time show.)
There’s a sociological theory that the successful cults are those that make their adherents work harder. Brand Taylor Swift is annealed by all the work we put into it.
3. Master the Art of Suspense
On October 7, thirteen days before Midnight‘s release, Swift started posting videos on TikTok under the title “Midnights mayhem with me.” The singer pulled titles from a bingo cage at random, announcing them and providing backstories. At the same time, Spotify co-branded billboards appeared in New York City and London with enigmatic snippets of song lyrics.
As the Drum’s Audrey Kemp wrote recently, these tactics were part of the masterful rollout of Midnights.
Swift has always made the most of withholding and releasing facts most prized by fans: release dates, album and song titles, co-stars. Last year, for Fearless (Taylor’s Version), she combined suspense with her penchant for puzzles, tweeting a video of a vault filled with scrambled letters. These were unscrambled by the intrepid to reveal the names of collaborators Phoebe Bridgers, Chris Stapleton and Ed Sheeran, and song titles such as “All Too Well.”
For 2019’s Lover, Swift provided both a Monday and a Saturday version of the mystery. She admitted the video for “ME!” contained the (unknown) title of her next album, but fans rejected “Lover” because it was too obvious, appearing in huge pink neon letters on the top of a building. The album was called Lover.
Then some sharp-eyed owners of her official calendar noticed a butterfly stamp on April 13 (there’s 13 again), and thirteen days later, Lover‘s first single debuted.
This kind of suspense makes her releases more poignant. Combined with a sense of scarcity, carefully cultivated through the ticket-buying (or not-buying) process, it puts Swiftys into a state of near-continual brandemonium around these key launch windows.
So brands, be like Taylor: malleable and flexible, demanding in a way that rewards close attention, and above all unpredictable. Taylor Swift is in show business, of course, but now so is every brand.
Elon Musk does not have a love-hate attitude toward advertising: he hates it. At least, that’s what he said – on Twitter, of course – back in 2019: “I hate advertising.”
This may be a curious attitude for a new media mogul whose most recent acquisition – that same Twitter – is almost entirely ad-supported.
But it turns out that Musk is not alone. The history of major ad platforms is littered with righteous founders who did not like the business they now own. In fact, it’s difficult to find a founder who expressed any fondness for ads, let alone ad tech.
But when revenues are required, attitudes change; call it a pivot to reality.
Here – in alphabetical order – are the origin attitudes of the great modern ad businesses. What’s the lesson? We change as we grow? Maybe. Or maybe, like Musk, we all need to learn a little respect.
Amazon
“Advertising is the price you pay for having an unremarkable product or service.”
“If a business [i.e., advertising] is built on misleading users, on data exploitation, on choices that are no choices at all, then it does not deserve our praise. It deserves reform.”
“We want to be the safe respite where you can explore, get stimulated, have fun, enjoy, relax — and have none of the controversy around exploiting users with advertising.”
“We are probably the last people in the world that want to do this [i.e., advertising], but it will be tastefully done, and that will keep it free to the users, like TV.”
– Jerry Yang, co-founder (1995), quoted in Inside Yahoo by Karen Angel
Advertisers only wish we knew as much as people seem to think we do. “Surveillance” is a mysterious term and surely overstates the case. But it is undeniable that the rules are changing, perception is a mounting problem, and it’s time to think ahead. How?
One company leads the field with its provident tactics. Already a significant — if not yet dominant — media player, it is assembling the components of a powerful offering and has much to teach us all.
(1) Start with Your Brand
This won’t be easy. The ad business has long had trust issues, which did not start with GDPR and CPRA. Celebrations last year that advertising was now merely the second least-trusted profession (after politics) were just sad.
But there is an exception: a $400 billion-earning company that has managed to persuade most of us that it’s not part of a menacing “data-industrial complex.” Apple is the world’s most valuable brand, according to Interbrand, up 26% since 2020, well ahead of its competitors.
How? They raised awareness for problems most did not know existed — such as mobile app ID, I.P. address and email “tracking” by marketers — and then provided a solution. In a single release (IoS 14.5 for ATT), Apple went from enabling to solving a problem. Its brand as neighborhood watch for the web extended to TV spots showing creepy characters stalking us on our phones until a superheroic ATT intervened.
Lesson: Counteract trust erosion by investing in a brand of law and order.
(2) Make the Opt-In Positive
Apple has championed the opt-in model of consent, arguably influencing pending national privacy legislation. Opt-in presents the consumer with a mandatory choice to accept or reject (opt-in or -out) whatever is requested.
The challenge here is well-studied, although not by advertisers. It even has a name: “The Paradox of Privacy.” As it turns out, there are a lot of cognitive biases that affect a person’s decision in that magic opt-in moment.
We are lazy (“can’t think about this right now”); overestimate how much data is collected about us (“tracking me around the web”); underestimate the benefits (“what is ‘relevance,’ anyway?”). In short, quite logically, we lack both time and data to make a good decision.
Very few people watch ads by choice, and nobody endorses tracking. The most successful modern platforms — paid search, social in-stream, retail media — are not optional. Opting-in to ads is a default on sign-up.
A meta-study of dozens of academic studies of the privacy paradox concluded: “Privacy attitude was best predicted by internal variables likes trust ….”
And that’s why the language on the opt-in box itself — the experience around the decision window — is critical. Apple knows this.
As we all know by now, the required headline for the required ATT prompt read: “[‘Brand’] would like permission to track you across apps and websites owned by other companies.”
We note that tracking is not a benefit, and no rational actor would agree to it, even with time to think.
When it came to describing the rewards of targeting in its own environment, Apple provided more benefit-centric headline text and copy: “Personalized Ads … help you discover apps, products and services that are relevant to you.”
Lesson: Frame the benefits of behavioral data collection in positive terms.
(3) Focus Down the Funnel
The cookie and mobile IDs may be engaged in one of the longest death scenes in history. But pointed targeting and powerful measurement are more possible than ever — in controlled (“opted-in”) environments, sometimes called gardens.
Digital ad money was always further down-funnel than linear, and it’s getting more so. People forget that paid search is still half of digital ad dollars, and it’s a strong signal of intent. Retail media is more than a trend: connecting ads with purchases is as outcome-based as ads can get.
Building up a campaign, smart marketers start with (1) moments closer to the point of sale, and (2) outcomes they can track. They build out from there, into intent and targeted awareness (like CTV) and then less controlled environments like late-night cable for reach.
Apple’s media business starts with Apple Search Ads for app installs in the iTunes store, an estimated $5 billion business. Exempt from ATT, Apple can tie these ads to app installs and in-app activity. (Compare this with the brand-focused, abandoned iAds project.)
What comes next? It added hero placements on the App Store’s opening screen. It also offers ads in its News, Podcasts and Maps apps. Maps in particular offers direct-response opportunities tied to location.
That long-rumored DSP and network could allow Apple to bring some of this helpful intent information to ad targeting in apps it doesn’t own.
Lesson: Future-proof ad businesses start with direct response ads.
(4) Focus on “Non-Ad” and Peripheral Placements
There are ads that are ads that don’t seem much like ads. They’re more likely to be acceptable even to more paranoid web surfers and even to regulators. Paid search is an example, I think: despite Google ingesting some of the most private material on earth, consumers don’t seem to think it’s a problem.
Contrast search with a retargeted banner, which appears out of nowhere indicating it was watching me elsewhere. The retargeter knows much less about me than my search engine but seems to know more. Why? It’s overestimated. And it was widely noted that Apple Search Ads flourished after ATT limited retargeting last year.
What does this mean for your future-proofing ad player? What I’m calling “non-ad” ad formats are those that are ads but don’t feel like them. Look at product placement. These ads are growing almost as fast as CTV, are a $23 billion business, and are not even mentioned in the 11 Chapters of the of the GDPR text — which mentions just about everything else.
As AI gets better, weaving products into shows on Apple TV and network apps becomes appealing. Other trending formats don’t interrupt but marginalize ads, literally placing them around content. TikTok Pulse and Meta’s Reels released new “multi-advertiser” formats like this.
The real opportunity may be in shoppable commerce. These are non-ads in that they put a buy-now button on other content, like a show (or product placement). As mobile ad expert Eric Seufert has noted, commerce, retail and CPG are Meta’s largest verticals. Innovative units could shift some of that spending around.
Lesson: Future ads look more like buy-now buttons.
Without appropriate cultural relevance, data analysis and distributed resources and knowledge, centers of excellence can undermine global success, writes Salesforce’s Martin Kihn as part of The Drum’s Globalization Deep Dive.
/ Leon Seibert
Many of us remember where we were during the great chopstick scandal of 2018, when a storied luxury fashion maison launched three highly-produced videos on YouTube in China to support an upcoming show.
In them, models tried to eat traditional Italian food like cannoli and pizza using chopsticks, with predictable results: a hot mess for both the utensils and the brand, which faced a chorus of complaints from Chinese consumers on Weibo and other platforms, claiming cultural tone-deafness.
The brand quickly pulled the videos, canceled the show and has since lost share in the Chinese market. Part of the problem was a lack of localization in global brand messaging – or what one study of social marketing fails politely called “inadequate research.” The brand had a world-class marketing team, but it was back in Milan, the company’s de facto ‘center of excellence’ (CoE).
During a time of cultural sensitivity, global marketers must balance the imperative to build out such centers with a growing need for in-market nuance. There are new forces facing global marketers that call into question the conventional rush to build centers of excellence across almost every functional discipline.
It turns out, excellence may increasingly be found at the edge – not the center.
Four horsemen of the CoE-pocalypse
There is much logic and some evidence that CoEs can add value. Firms such as Gartner have long championed CoEs for marketing functions such as analytics and data science. They generally define a CoE as a discrete cadre of coordinated professionals with specific, uncommon expertise, who cross-reference ideas, disseminate practices and templates and function as a skilled resources for dispersed global operations.
So compelling is the impulse to the CoE model that it is difficult to find any doubters. Consultancies such as McKinsey routinely recommend establishing a CoE for advanced functions. For example, a recent McKinsey report on automation says: “A center of excellence is vital both as a source of expertise and to define priorities.” Meanwhile, the US Army has at least 15 CoEs for functions from missile defense to human resources.
Global marketers have taken the advice and adopted CoEs. A Gartner survey indicated that two-thirds of enterprise marketers already had an analytics CoE five years ago – yet this year, 26% of CMOs identified analytics as an ongoing capability gap. The same research revealed global marketers had a lot of swagger about their ’operational excellence’ (only 15% cited as a gap), due in part to CoEs.
Yet as the chopstick incident implies, not all wisdom can be centralized. And there are a number of rising forces that point toward the need for global marketers to question the march toward CoEs.
The four horsemen of the CoE-pocalypse are:
Cultural relevance: Local consumers require local nuance – and will take to social media if it’s missing.
Data bias: AI and machine learning models can inherit bias from data collection and processing methods, both of which can have a cultural dimension that is only now being recognized.
Knowledge resources: Many formerly ‘specialized’ disciplines – including reporting and campaign automation – are more common, with widespread learning resources.
Distributed workforce: More dispersed and hybrid employment models undermine some of the CoEs’ neo-Xerox Park ‘skunkworks’ premise.
To CoE or not to CoE?
How is a marketer to assess whether or not a CoE makes sense for a particular situation? As an ex-consultant, I’d be surprised if I didn’t propose a solution in the form of 2×2 framework.
CoEs are supposed to support: (1) availability of specialized skills; and (2) processes that can be run globally rather than locally. So by implication the axes of our 2×2 are:
Skill level: specialized v unspecialized
How hard are the skills to find in most global markets? If they’re rare and uncommon, or less rare in some regions than others, a CoE may be in order. As marketing teams get more sophisticated over time, fewer skills may fall into this area. (According to Gartner, the hardest marketing skills to find in the current environment are data and analytics, customer experience management and marketing technology; the easiest is social marketing).
Cultural proximity: embedded v not embedded in local culture
Is the function something that requires an awareness of how actual human beings talk, think and work in a specific context or not?
Another way to evaluate this requirement is in symbolic terms: How much does the function use global symbols, such as numbers, versus more culturally loaded symbols like words and images? If it’s mostly about numbers, a CoE could work – and if not, it may be time to reevaluate.
So the CoE is most useful for marketing challenges related to data modeling and predictions, such as next-best-action and -experience – and for data operations and automation projects that can be standardized across regions. It is less useful for developing creative artifacts for specific regions and building media plans.
Let’s apply the framework to our original example. We see the capabilities required are video production and creative development, skills that are both locally available and deeply embedded in the culture – so, not amenable to the CoE treatment. On the other hand, were that same brand to implement a marketing automation system, it would be entirely reasonable to spin up a CoE for that.
As we go forth into our new world of global marketing, we should take care to discriminate non-human processes from very human communications and recognize that both standardization and globalization have their limits.
Martin Kihn is senior vice-president of strategy at Salesforce Marketing Cloud. For more on what marketers and their partners need to do to succeed on a global level, check out The Drum’s Globalization Deep Dive.
This article first appeared in The Drum US on August 31, 2022
We’re all under the influence.
Influencer marketing is the fastest-growing paid channel this year, after connected television (CTV), resilient even in the face of recession. As companies plateau their use of social media, 75% of US marketers plan to invest in influencers this year – up from 66% in 2020, according to eMarketer.
And it’s not about products-for-posts anymore – it’s big business. Global marketers spent about $14bn on influencers last year, including media. B-listers such as Joanna Gaines and Addison Rae enjoy multi-figure deals, while real-life stars including footballer Cristiano Ronaldo get an estimated $500,000 per post. And there are thousands of creators in niches from travel to beauty to – of course – cats who are paid an average of $100 per 10,000 followers per meow.
In a world where 50 million people call themselves ‘creators,’ there are a lot of options for brands to partner their way into feeds, tweets and videos. Influencers can provide creative content, access to elusive audiences, higher engagement and compelling social proof.
But there’s a problem. Brands using influencers, surveyed by the Association of National Advertisers (ANA) in 2020, admitted their top challenge was measurement. The situation is no better now. How do you know if you’re getting a worthwhile return-on-influencer (ROIn)?
Channels are not created equal
Measuring the impact of an influencer program is notoriously sketchy. It’s an emerging channel without industry standards. Although the Media Rating Council (MRC) has established guidelines for paid social measurement, most of the value of influencers comes from organic engagement – all those likes, shares and comments from followers and friends of friends that turn a snippet of video into cultural cachet.
Challenges with measuring ROIn include:
Data collection: Brands without API access to influencer accounts rely on methods such as emailed screenshots for metrics
Reach: It is difficult (read: impossible) to deduplicate audiences across platforms
Engagement: Different platforms present different options (where TikTok garners likes, Pinterest culls clicks) and define ‘engagement’ in different ways
Consistency: Agency partners often use proprietary roll-up metrics that can be opaque
Earlier this summer, the ANA released the first ‘Influencer Marketing Measurement Guidelines,’ taking a step toward standardizing organic measurement. Developed by the Influencer Marketing Advisory Board – formed in 2020 with reps from brands such as Puma and Target – it was based on meetings with 25 agencies and the eight major platforms (Facebook, Instagram, LinkedIn, Pinterest, Snapchat, TikTok, Twitter and YouTube).
Brands that have been there will tell you that working with influencers is special – more like hiring an improv troupe than deploying a bot. Companies like control, but creativity is part of influencers‘ charm. So it makes sense to start by asking them how they measure success. A beauty star such as Huda Kattan might value video engagement, while a photo influencer such as Murad Osmann might care more about shares.
Most brands measure ROIn based on ‘engagement,’ a blunt sum of actions divided by exposures, aggregated across all the platforms in the campaign. But this method assumes every creator aims for the same responses, and it ignores the platforms‘ real inconsistencies.
Many roads to the rainbow
Using basic discipline, the hard-working marketer with an influencer program wants some combination of three KPIs:
Awareness: This is driven by reach and frequency, generally available for each platform in isolation, but not across platforms; video views are usually counted here
Engagements: These are measured interactions with the influencers‘ content, including likes and shares – often expressed as an ‘engagement rate’ (ER) or engagements per reach
Conversions: Often the ultimate goal, this is likely undercounted and based on direct clicks through to the brand’s commerce site or other destination
Now, the ANA performs a public service in teasing out the vagaries of the platforms‘ self-reported metrics. Anyone who’s spent time parsing reports from social networks will appreciate this effort. Key differences among the platforms‘ influencer reporting include:
Facebook and Instagram: For Meta-owned platforms, ER is total engagements divided by impressions, not including video views
TikTok: ER is total engagements divided by video views, excluding replays
YouTube: ER is the same as TikTok; however, TikTok counts any video that’s started as a view, while YouTube only counts a view after 30 seconds or 100% for its short-form ‘Shorts‘
Twitter: Twitter is similar to Meta, but quote-tweet counts aren’t available via the API
LinkedIn: ER does not include video views, which are counted after two seconds with 50% viewable
Snapchat: Interestingly, Snap doesn‘t yet provide organic influencer reporting
Understanding the components of the platforms‘ reports unlocks comparisons. Obviously, an autoplay video view on Twitter isn‘t as meaningful as a video view on YouTube, and a retweet on Twitter is not exactly equivalent to a pin on Pinterest.
For awareness and conversion measurement, reach by platform and direct attribution are useful. They aren‘t perfect, since the former misses duplicates and the latter indirect attribution (ie people saw the content and converted later, or offline). But they‘re reasonable baselines.
The problem comes with the most important influencer metric: engagement rate. How can it be improved?
Worth the weight
The answer is by weighting the different components of engagement. Intuitively, we know that a like isn‘t the same as a share or a comment. It‘s easy to like a post – you just tap the heart, right? But sharing to your network is a kind of endorsement, and a comment – with the right sentiment – indicates more visceral involvement.
A principle I used when measuring the impact of social media for brands was one I took from the self-help guru John Bradshaw: “We give time to those things that we love.” Simple enough. Extending it to social platforms, I‘d argue that actions that take more time and effort should count more toward ROIn.
For example, the marketer can create a consistent weighting factor for different actions based on the time they take to complete. Say it takes a second to commit to and tap a like. Even a short, positive comment takes at least five seconds. And a share with a comment might take longer. Typical viewer patterns should be considered, and they will vary considerably based on the influencer and type of campaign.
The ultimate ROIn plan might include breakouts for awareness and conversion, and an approach to ER that considers weighting actions by their level of effort. (The ANA guidelines don‘t address weighting.) Of course, a detailed formula requires access to the platforms‘ API and permission from the influencer. Art, science and some social engineering are required.
But that’s what puts the ‘sure’ in measurement.
Martin Kihn is senior vice-president of strategy, marketing cloud at Salesforce.
This article is based on interviews with participants. It was inspired by Microsoft’s supposedly surprising selection as Netflix’s ad tech partner. But driven by the acquisition of AT&T’s Xandr, that’s just the latest chapter in a breathtaking adventure of pivots, write-downs, partnerships and potential.
In the beginning were these words …
Bill Gates:
The future of advertising is the internet.
The occasion was the IAB Engage conference in London in 2005. At the time, Microsoft had MSN, an ad network and content deals with Fox, NBC and others. But it was focused on one particular upstart in Mountain View. Having lost a bid to acquire Overture, Microsoft launched its own search engine, originally code-named Project Moonshot.
Jed Nahum (director, product management, Microsoft adCenter): Google made about two times what we made on each keyword. We had this functionality which enabled you to bid for age and gender on top of keywords for search. It was our differentiator – but it wasn’t enough.
Eric Picard (director, ad tech strategy, Microsoft): Microsoft was focused on search, but Bill Gates recognized it was bigger – that ads could be another MS Office or Windows-sized business. We looked at investments in Xbox and PC gaming, video ads on Microsoft TV and Media Player and MSN Video. We looked at ads in Office. Around this time, Brian Burdick wrote a paper … that basically invented RTB.
Brian Burdick (principal group program manager, adCenter): In 2005, a couple people on my team and I wrote a proposal for an Online Listings Exchange. … We were piloting a contextual ad program that competed with [Google’s] AdSense. Microsoft had deals for content controlled by a premium display system. I realized on a drive home from work one day that if the revenue per impression between the contextual and premium systems was materialized in real time, any external third party could also participate.
Nahum: The insight of Brian’s paper was basically that what ad networks need is the User ID – like a cookie, IP header info, and a URL that corresponds to the context and location of the ad. If we could pass those three things to ad networks, they could evaluate on an impression-by-impression basis.
Burdick: Gates was super-bullish in the meeting. He had a bunch of comments. He said, “This is bold and ambitious and something we should do.” … Eventually, a lot of other teams wanted to piggyback on the idea, and our ask was for hundreds of engineers. It didn’t get approved.
Microsoft also took a look at Right Media, a pioneering exchange that allowed ad networks to bid on one another’s inventory. That meeting didn’t go so well.
Brian O’Kelley (CTO, Right Media): We went in to Microsoft to talk with a Technical Fellow. He put us through the wringer. I remember he asked us, “How many man-years did it take you to build the platform?” I said, “You’re missing the point. It’s liquidity you’re buying as much as technology.” Back then, Microsoft had swagger. I came away from Redmond feeling they were arrogant.
Right Media was later acquired by Yahoo, and Microsoft set its sights on another target, then owned by private equity firm Hellman & Friedman.
Nahum: Hellman & Friedman pitched DoubleClick to us. On my team, we were f*ing terrified. We understood the value of DoubleClick and what it would mean if it went to Google. After a low bid from Microsoft, Google and DoubleClick went into a quiet period. … We were very depressed. … Steve [Ballmer] quietly bid $3 billion, but Google threw in another $100 million to shut down the dalliance. We were left feeling burned. We were in a situation where we had to get a competitor to DoubleClick.
Picard: We left that meeting where we lost DoubleClick, and a week later Steve [Ballmer] had me and a few others in the room. He says, “This is like that scene in Animal House where Belushi rallies the troops.” And he says, “Okay, we lost DoubleClick – what else we got?”
Microsoft ended up buying aQuantive – including the agency Razorfish, the DrivePM ad network and the Atlas ad server – for $6.3 billion. On the same day, it acquired the AdECN exchange for, reportedly, somewhere between $50 million and $75 million. Bill Urschel and a rising star named Jeff Green ran AdECN.
Bill Urschel (co-founder, AdECN): They bought us and it happened pretty quickly. It was at an Ad:Tech [event] … Eric Picard and Jed Nahum came by our booth and asked all kinds of interesting questions.
Picard: We walked up and started chatting. We talked about what they’d built – it was interesting. Jed, [Microsoft GM] Joe Doran, Bill, Jeff and I had a fancy dinner and got along well. We were kindred spirits.
Jeff Green (COO, AdECN): Everyone wanted to see Microsoft do well. The AdECN strategy was to get Yahoo and AOL to join up and create a pool of liquidity that rivaled Google. But aQuantive was saying, you know, our ad server [Atlas] is better. Let’s combine it with Microsoft tech and build the world’s biggest ad network.
Burdick: DrivePM was the internal ad network aQuantive ran for Microsoft, and it had more than 40% margin. [They] put the head of strategy of aQuantive in charge of strategy for Microsoft. … They eventually came around to the exchange model, but not in the beginning. There was resistance to the exchange, putting margins at risk.
Boris Mouzykantskii (founder, IPONWEB): I think AdECN had a chance to test real-time bidding in the market. It never happened. It’s possible, if they’d done it, Microsoft would be AdX.
Urschel: After the acquisition, on the Microsoft side there were some brilliant people who saw a vision of a bigger exchange, but they were essentially drowned out. The cash at the time was flowing from the aQuantive business, so I don’t think the exchange business ever got a serious look and didn’t get the resources.
Burdick: I went down to be CTO of AdECN. … We built the first real-time bid exchange. But between the aQuantive people and our VP, they would not let us go outside [Microsoft] for inventory. The reasons are murky to me. They just didn’t greenlight it.
Meanwhile, Brian O’Kelley had started AppNexus, originally a cloud hosting platform that became an SSP and exchange.
Brian O’Kelley (co-founder, AppNexus): My pitch to Microsoft was that they can’t fight Google in search and display. Let us be the market maker, make us the dominant exchange platform. But that would only work if you put the whole heft of Microsoft behind it – all MSN inventory – [and] make everyone buy through us. I spent a lot of time in Bellevue and got a mind meld [for] how we could beat Google. It was an incredibly strategic conversation about the future of the internet, not just about product.
Picard: I introduced Brian to [Microsoft Ads exec] Rik van der Kooi. I said, “If we’re not going to be allowed to build this internally, it’s not a bad thing to invest in another company that’s a credible competitor to Google’s ad exchange.”
O’Kelley: We made a deal where [Microsoft] gave us inventory and they got one-third of the company. … Exclusive inventory from one of the top five publishers. Over time, we delivered. Some things were not successful, like a Windows Phone integration, but Microsoft was the first fully programmatic major seller.
Nahum: After the AppNexus deal was done, we branded our instance of [as] MAX, [the Microsoft Advertising Exchange]. We couldn’t get the aQuantive guys to put inventory in AdECN, but we were able to put it into the waterfall after direct sales for AppNexus. Immediately it started making money. My team launched 35 markets internationally. We sold to aggregators of demand, to DSPs, agencies and trading desks.
Picard: It was really bittersweet. The day I decided to leave, I was in a meeting with Ballmer. He said, “I want us to shut MSN down, divest all the non-search ad business [and] the exchange and double down on paid search.” Ultimately, the team convinced him MSN was too critical – but the strategy shifted from editorial to being a portal with content from other publishers. It took about six years to fully divest the display business, until 2015.
Microsoft Press Release, July 2012: While the aQuantive acquisition continues to provide tools for Microsoft’s online advertising efforts, the acquisition did not accelerate growth to the degree anticipated, contributing to the write-down [of $6.2 billion].
AdExchanger, June 29, 2015: AOL to Absorb Microsoft’s Display Ad Business Along with 1,200 Employees, Bing to Power all AOL Search
O’Kelley: AOL’s pitch to Microsoft was [to] let us rep everything. There was tension there. [AOL CEO] Tim Armstrong and I would see each other on the street corner “growling.” Microsoft wanted AOL to choose Bing as its search engine. That was a $1 billion deal. We couldn’t beat that. How could we possibly win? We had to massively overdeliver.
David Jacobs (SVP, sales & monetization partnerships, AOL): I’d give credit to Tim Armstrong, who really leaned in, and Bob Lord who pushed the deal through. It seemed like a good thing. … It was almost like a scale play. AOL and Huffington Post were relevant properties that had legs, but this created an opportunity to take brand sales to another level. Header bidding was not mature yet.
O’Kelley: I convinced Microsoft to give AOL [some] major markets, including Japan, the US and UK, and [to] give us the rest. The deal was good for everyone. We made Microsoft hundreds of millions. That was a $30 million revenue account for us. We ran with 17 [or] 18 “demand evangelists” providing a lightweight sales model. My nightmare was AOL would drive us out of the deal.
Jacobs: It happened at a time with a lot of moving parts. AOL acquired Millennial Media around then. I was in Dulles with some Microsoft people when the deal was about to be signed – and that same day the Verizon acquisition [of AOL] was announced. … There was a lot of change management happening. It allowed Microsoft to not have to support a display ad sales team.
O’Kelley: There were so many of those moments. That was constant. Google was selling against us. AOL was selling against us. I used every bit of leverage to keep from losing our biggest client.
Jacobs: While not core to the deal, we would have liked to get Microsoft inventory into our SSP [from AppNexus]. Eventually, we migrated the Microsoft display inventory over to AOL’s ad server.
Brian Lesser (CEO, Xandr): Clearly there was some value there that we created, because Microsoft could have bought a lot of things, and they bought Xandr. … I think Xandr is going to be great with Microsoft.
John Cosley (senior director, brand marketing, Microsoft Advertising): We have bold ambitions, including the innovations we’ll drive with Xandr now that the deal closed – [also] continued momentum with our PromoteIQ offering, Microsoft Audience Network solution, our new measurement partnership with Roku – and ongoing innovations and market expansion for our advertisers across our search and audience network.
O’Kelley: I have mixed feelings because I wanted Microsoft to be the buyer the first time around. It felt like the right home for the company.
So, it’s a little bittersweet that they end up there now. I would have wanted to work at Microsoft. … LinkedIn is a huge asset. Activision is big. Windows is free now. There’s search, gaming – amazing ad assets. It doesn’t seem crazy that they could be successful in the ad tech business.
This lavishly illustrated article is based on a talk I gave not long ago at the ANA Masters of Data event in Orlando and at Salesforce Connections in Chicago. It could interest cats wanting an overview of the state of digital marketing and ads, with an emphasis on worry beads. As usual, if you’re already a genius, I have nothing to tell you.
Now if you’ve noticed more speed in the digital space in recent years, you’re right. Of course the pandemic raised the velocity of digitization, but the real change had happened before 2020. In a phrase: digital won.
Advertising is a proxy for attention, so the movement of ad spend into the digital realm is an expression of our virtual migration. The –verse is already meta: we’re living in the ether. Those of us who remember the early 2000’s when digital was maybe 10-15% of ad spend at the most innovative shops, and most of that was search – well, we knew this would happen, but we’re surprised that it did.
There’s big money here, which is the best explanation for all the battles over IDs and OSs and privacy rights I can give you. On a related note, it’s also become an increasingly concentrated business. Pareto rules as 80% of the rewards go to just three companies: Alphabet (aka Google), Meta and Amazon. There’s a theory in market strategy called “The Rule of 3,” which is self-explanatory, and there’s some analogy to the Big 3 networks of the 1970’s.
To be clear: it’s not all about the third-party cookie. Cookies were the CNS of programmatic ads and tactics like retargeting, but they’ve been ebbing out for years. Mobile apps don’t use them, nor does search. Apple’s Safari browser defaulted away from them a half-decade ago; only Google’s Chrome remains loyal, and as you know the sand’s running down there as well.
We’re already living in the ‘cookieless world.’ In VERY round numbers, here’s a rough breakdown of digital ad spent in the U.S.
If you figure half of ad spend still goes to linear channels, then your perfectly proportioned big-media mover is likely allocating something less than 10% of her budget on cookied media.
Speaking of cookies – as I so often do, making me lethal at parties – we do have the pandemic partly to blame for what I like to call the Longest Death Scene in History. Google’s Chrome blog announced their departure in January, 2020, and has subsequently extended the final flicker to some vague moment late in 2023 or beyond ….
So What’s Going On?
Let’s remember a concept called expected value. As we learned in business school, expected value is a product of (what something is worth) x (how likely you are to get it). So if the jackpot is $1 million and my odds are one in a million, that lottery ticket is worth $1 to me.
That’s how digital marketing works. Take an ad. When figuring how much to pay for it, the smart media planner will more or less think: (what is a positive outcome worth) x (how likely is it to happen)? In other words, they try to estimate what part of the audience will respond to the ad and what a “response” means in dollars.
This math is easier to describe than to do. How would you treat a car ad, that might raise awareness but inspire few sales – at least, this year? You might know the value; what’s the P? But the principle abides, and it helps explain a phenomenon we can call the Late Night Cable Ad Experience.
Imagine you’re on your sofa and it’s 2 a.m. and you’re randomly scrolling through cable. Those ads are barely targeted at you at all. And what you’ll see – so I hear – are a lot of ads for medications and class-action lawsuits and for food and cleaning products. In other words, either very expensive or very common items.
Why? It’s the expected value. When messages can’t be targeted very well, they will default to those with a very high P (hit rate) or those with a very high value; that is, the mass-iest of the mass market stuff and things like lawsuits, where you could have one in a million respond and still pay for the campaign. As marketers lose the ability to target on the open web through data deprecation, every ad experience in the wild will converge on cable.
It’s my theory that most consumers only think they don’t like targeted ads. In truth, we’ve become so used to applied data for aiming and attributing messages that we’ve forgotten what it’s like to be anonymous. It’s not pretty. Nobody remembers the mid-1990s and the beginning of the internet, but it was full of irrelevant emails and ads.
Apple has an on-and-off relationship with media, but it’s decided that “privacy” is its brand and an explicit opt-in is required for any kind of cross-domain view. Its App Tracking Transparency (ATT) framework is only a year old but has had a major impact on mobile networks. The Financial Times made some noise with its second-half 2021 estimates of lost revenue, due to ATT:
Meta – $8B lost revenue
Snap – $600M lost
Twitter – $400M lost
One surprise winner in FT’s analysis was … Apple, whose paid search ads business in its iTunes store was a significant gainer.
How did this happen? Mobile apps don’t use cookies because they don’t run in browsers; they’re equipped with a mobile ad ID (MAID) which is persistent and unique at the level of the operating system. Before ATT, this MAID-based system was better than cookies because it required less cumbersome ‘synching.’ Mobile ad networks like the Facebook Audience Network (FAN) used it to target and measure in-app ads very well.
In fact, many digital-first businesses focused most of their media spend on the singular channel of Facebook/Instagram ads. Back in 2017, the New York Times magazine ran a story headlined: “How Facebook’s Oracular Algorithm Determines the Fates of Start-Ups.” It was about just how powerful Facebook ad targeting was.
A lot of these businesses used Shopify as their commerce platform. Not surprisingly – but rather dramatically – the roll-out of ATT also had an impact on Shopify. Well before the recent market meltdown, Shopify’s market cap was cut in half from its peak.
(h/t Eric Seufert)
At the RampUp event earlier this year, I saw a presentation from a large publisher estimating the impact on their ad prices due to ID loss. They used Safari’s cookie deprecation as a proxy for estimating what would happen when cookies disappeared in Chrome. The punch line was: down 50%.
As a general rule, we can say the cookie (or MAID) doubled the marketers’ ability to find a likely customer.
So Who Is Fixing This?
Some are trying, and some don’t think there’s anything to fix. A few years ago esteemed Apple privacy engineer John Wilander described the situation nicely in this thread on Twitter. (Note that his phrase “There may be problems worth solving that were previously solved with third-party cookies” reduces two decades of ad tech innovation to a triviality.)
Privacy Sandbox. You’re likely aware that the World Wide Web is tuned up by a large and largely anonymous volunteer army, technical types who hold long calls over years and process fixes large and small through committees into production. From its foundations in HTML and TCP/IP, protocols are what makes it a Web, after all.
Browsers are overseen by the World Wide Web Consortium (W3C) and its various Community Groups and Business Groups. This is where Google’s Chrome engineers and others bring their proposals for the post-cookie world, and they’re discussed more or less openly by Apple, Mozilla, Meta, and others. You’ve heard of the ‘Privacy Sandbox’ and FLOCs and FLEDGEs and so on; this is where they nest.
We started with anonymized cohorts generated by the browsers (FLOCs) … moved to a less detailed version of the same with more randomness (TOPICS) … and are now excited about publisher-defined cohorts. Basically, we’re left with publishers (and in one proposal, browser users, aka, us) labeling ourselves for targeting.
So far, we’ve learned what won’t work – but not much about what will. Tension is fundamental – and perhaps irreconcilable – between people who hold:
Theory A: Browsers and apps can collect some form of information safely, without explicit opt-in
Theory B: Opt-in should be required for everything
Although so much is in flux now, it’s entirely believable that Chrome and Safari, Android and IoS, Mozilla and Edge will all have different rules in the end. Debates are in terms that have not been defined. What is “privacy”? What is “consent”? What is love – baby don’t hurt me …?
On that penultimate point, not enough legislative chutzpah has been pointed at the language of the opt-in box itself. It seems to me more important than anything else. Theory B assumes we average humans are actually equipped to know (1) exactly what data is collected about us; and (2) exactly what ‘personalization’ looks like. I’m not so sure. (Look up the ‘privacy paradox’.)
Note that Apple’s language (on the right) for its own ad experience is somewhat more attractive than the frowsty boilerplate it issued for ATT (middle). One woman’s “tracking” is another ones’ show of respect.
What Happens Now?
Digital marketing is a field that’s weathered teething and teen years, gone to college in a difficult political climate, and is old enough now to think about moving out of the basement. The first commercial browser, Netscape, was launched in 1995, making our Web 27 years old. Yes – definitely time to grow up.
Maturing is messy. There’s experimentation; fits and starts. We try one direction, go to Europe, and come home with a different look and outlook. Fundamentals apply; we’ve got a bright future. And we’ve got to play by the rules; we’ve got to adapt.
Marketers are adapting, fast. In my travels virtual and real these past few years, I’ve seen nothing but admiration for the challenge and a willingness to work. Stripping out the arbitrary vectors, what do we marketers need? I like the IAB’s framework, reducing requirements down to two categories: Addressability (finding people), and Accountability (measurement).
Both will always be possible; it’s their precision that’s in transit.
Some conclusions about the future seem reasonable to me. We can take these as likely hypotheses for planning:
User-level IDs will require opt-in to share (this includes IP address and maybe email)
Marketers have to get better at demonstrating data use
Publishers and people have some control over their labels (if they want to)
Measurement becomes a complex mesh of next-gen MMM and testing (see Analytic Partners)
First-party data builds competitive advantage
Yes, let’s talk about 1PD. First-party data isn’t new, nor is the idea of a ‘single view of the customer.’ What’s new are improvements in technology’s ability to support the V’s of big data (velocity, variety …) at reasonable rates. It makes sense to organize, harmonize and deduplicate your customer and prospect information, gathered with consent.
This is where the mighty Customer Data Platform comes to help you, and I’ve co-written a book with the multifaceted Chris O’Hara about this very topic (see B&N or Amazon: “Customer Data Platforms”).
It makes sense to try to collect more 1PD/0PD using increasingly inventive techniques.
And that’s what marketers are doing. Just ask them. I thought it was puissant that the IAB/Ipsos State of Data report this year named two ‘solutions’ to deprecation challenges: (1) gather more first-party data, and (2) analytics.
These answers seem right to me, but they’re also something of a holy rosary. We don’t have data: we’ll get more. We don’t know what to do with it: We’ll ask the machines. Of course, we all know it isn’t that easy, and I recall from my Gartner days that spending on marketing data science is generally rewarded. But the tone is defensive.
So what’s going on? We’ll stop here. The most mysterious impact on digital marketing’s future will come from forces we’ve barely mentioned: legislatures and mergers & acquisitions. A government could decide tomorrow that ad targeting is illegal and marketing is mind control.
Martin Kihn 