A former colleague at Forrester Research recently published a study that described his view of the future of online marketing.
The study is available to Forrester clients only, but the crux of the argument is laid out in a blog post: Why Google – Not Facebook – Will Build The Database Of Affinity.
The author, Nate Elliot, describes large media companies building a “database of affinity,” which he described thusly:
Recently we described an idea called the database of affinity: A catalogue of people’s tastes and preferences collected by observing their social behaviors on sites like Facebook and Twitter. Why are we so excited about this idea? Because if Facebook or Twitter or some other company can effectively harness the data from all the likes and shares and votes and reviews they record, they could bring untold rigor, discipline, and success to brand advertising.
Nate’s argument as to why the database of affinity represents the future of online marketing is this: online search was revolutionary for marketers because it allowed them to target their customers better than ever before. Marketers could now spend advertising dollars to get their brand in front of people actively searching for their products (e.g., Samsung advertising to searchers of [buy LCD TV]) rather than passive watchers of TV or print.
In keeping with the thinking that more targeted is always better, Nate argues that brands will be able to use historical affinity behavior of consumers to target more precisely than ever before.
It’s clear that the database of affinity is a prize of gigantic proportion, and ultimately, Nate concludes that Google will end up the winner in that battle because they have the broadest data to draw upon and best chance of making sense of it.
I want to set aside the question of who will win that battle and question some of the assumptions upon which the affinity database argument is built.
Nate’s argument rests on the assumption that if some targeting is good, more targeting is better. Thinking about this in isolation, at the level of “theory,” it stands up to scrutiny. But there are places where, at the level of “practice,” it seriously falls down — and in my view, these flaws are sufficient to make me question the validity of the whole argument.
For example, not long ago, I bought a pair of jeans online from Bonobos. A little while later, I was shown an ad for Bonobos in my Facebook feed. I was perplexed by the timing of it, until I read an article that described brands’ practice of providing Facebook with customer email addresses that were then mapped to Facebook logins so that targeted ads could be shown to brand customers. This is technically more targeted, but I responded negatively since I had never opted into their feed.
I think the question this raises is this: when it comes to targeting, is there a point of diminishing returns? Maybe there is such a thing as just enough targeting and no more.
Any discussion of which media powerhouse (Google, Facebook, Twitter, etc.) will win the affinity database race presupposes that all players have the same ability to act upon that information. But, context matters.
In search, I am in research mode: in entering a query into the search box, I am announcing my intent to accept “bids” for my attention from all takers, and I’m prepared to act upon the provider of the best information in the search results to that query.
In social, I am in a very different state of mind. I expect content from my closed network, and unless I have invited a brand in by Liking or following them, their presence is very much viewed as an uninvited intrusion. It’s the loud, slightly drunk guy at the party that keeps interrupting your conversation with the interesting guy/gal.
It’s possible that users will become more accepting of ads appearing in social streams and begin to specifically turn to social networks for a wide variety of information retrieval scenarios — for shopping/product research, job search, etc. This would give brands a strong opportunity to leverage the database of affinity in marketing on social networks.
But as the chart below shows, this is not yet occurring at significant rates. This all adds up to our remaining highly skeptical that purely social companies have the ability to effectively leverage any database of affinity they may be able to build.
Finally, I want to question a concluding assumption Nate makes in how the affinity database must be leveraged if marketers are to be successful:
If marketers are going to use affinity data to power brand advertising, simple text-based ad units won’t cut it. Brand advertising demands large, video-based ads to create discovery — TV spots, pre-roll ads in online videos, and supersized online banners.
I don’t buy the argument that large, video-based ads are a minimum requirement to reach consumers. Context matters — there is more than one way to reach an audience, and Google’s $29 billion search advertising business shows that text-based ad units do, in fact have their place.
The idea that digital marketing is progressing to targeting via a database of affinity makes sense. The argument had me nodding my head in agreement initially, but further reflection produces some serious doubts about the assumptions upon which it is built.
First, there is some question about whether more targeted is always better; and second, there is a question of whether all players involved have the ability to effectively leverage a database of affinity.
What do you think?