Is Efficiency Bad For Digital Display?

ohara-ddt-nextmark-usethis“Data Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.

Today’s column is written by Chris O’Hara, Chief Revenue Officer at NextMark.

I’ve always loved the notion of programmatic RTB. As a data hound and an early adopter of AppNexus, the idea that advertisers can achieve highly granular levels of targeting and utilize algorithms to impact performance is right in my wheelhouse. Today’s ad tech, replete with 300 companies that enable data-driven audience segmentation, targeting and analytics, is a testament to the efficiency of buying ads one impression at a time.

But what if driving efficiency in display actually does more harm than good?

Today’s RTB practitioners have become extremely relentless in pursuit of the perfect audience. It starts with retargeting, which uses first-party data to serve ads only to people who are already deeply within the customer funnel. No waste there. The next tactic is to target behavioral “intenders” who, according to their cookies, have done everything but purchase something. Guess what? If I searched four times in the last three hours for a flight from JFK to SFO, anyone who serves me enough ads is likely to eventually get last-view attribution for my ticket purchase. Next? Finding “lookalike” audiences that closely resemble past purchasers. Data companies, each of whom sell a variety of segments that can be mixed to create the profile of a 35-year-old suburban woman, do a great job of delivering audiences with a predilection to purchase.

But what if we’re serving ads to people who are already going to buy? Is efficiency really driving new sales, or are we just helping marketers save money on marketing?

To me, it seems like online display wants to be more and more like television. Television is simple to buy, it works, and it drives tons of top-funnel awareness that leads to bottom-funnel results. We know branding works, and even those who didn’t necessarily believe in online branding need look no further than Facebook for proof. With its Datalogix offline-data partnership, Facebook conclusively proved that people exposed to many Facebook ads tended to grab more items off of store shelves. It just makes sense. So why are we frequency-capping audiences at three, or even 10? I can’t remember the last time I watched network television and didn’t see the same car ad about 20 times.

The other thing that RTB misses out on is profit. RTB drives advertising to lower the overall cost of media needed to drive a sale. Even if today’s attribution models were capable of taking into account all of the top-funnel activity that eventually creates an online shopping-cart purchase (a ludicrous notion), we’re still just measuring those things that are measureable. TV ads, billboard ads and word-of-mouth never get online credit – yet I believe they drive most of the online sales. Sorry, but I believe the RTB industry creates attribution models that favor RTB buying. Shocking, I know.

So what is true performance, and what really drives it? For most businesses, performance is more profit; in other words, the notion that a sales territory currently generating 100 sales a day can achieve 120 sales a day. That’s called profit optimization. If I can use advertising to create those additional 20 sales, while still making a profit after expenses, then that’s a winner. Meanwhile, RTB makes it cheaper to get the 100 sales you already have but doesn’t necessarily help you get the next 20. Getting the next batch of customers requires spending more on media to drive more top-funnel activity.

Part of the problem is that RTB doesn’t take into account how real-life sales actually happen. Sure, audience-buying technologies know what type of audience tends to buy a given product and where to find it online, but frequency-capping and a lack of contextual relevance keep them from effectively selling to new buyers.

Let me explain. In real life, people live in neighborhoods. In most neighborhoods, the Smiths drive cars similar to the Joneses, eat at many of the same restaurants, and shop at many of the same stores. If the Joneses get a new BMW, then it’s likely the Smiths will keep up with the Joneses, buying a new Audi or Lexus in the near future. When neighbors get together, they ask each other what they did during February Break, and they trade vacation ideas. That’s how life works.

What media most closely supports this real-life model, where we are most influenced by our neighbors?  Is it serving the Jones family a few carefully selected banners on cheap exchange inventory, which is highly targeted and cost effective? Or is it jamming the Smiths and Joneses with top-funnel brand impressions across the Web? The latter not only gets Jones, the BMW owner, to keep his car top-of-mind and to be more likely to recommend it, but it also predisposes Smith to regard his neighbor’s vehicle in a more desirable light. That takes many impressions of various types of media. You can’t do that and remain efficient. The thing is, though , you can do that and create incremental profit.

Isn’t that what marketers really want?

Follow Chris O’Hara (@chrisohara) and AdExchanger (@adexchanger) on Twitter. 


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  1. Hi Chris,

    I agree that we need to rethink success metrics and really focus on incrementality. I think as the industry begins to factor in touch points from other channels (especially owned media), it will be forced to rethink display attribution where the pivot is incrementality. Display is one of the few outbound media tactics that a marketer has, and regardless of whether the tactic is branding or performance, we need to look at and quantify how that media initiates brand interaction.

  2. Adam Heimlich

    Great piece, Chris, and Dina, I concur. It’s hard to imagine, though, what will inspire advertisers to plan and evaluate media exposure across multiple channels. They seem to love their silos! For marketers with a legacy of channel DR and/or branding, even the prospect of predictable growth doesn’t seem enough to break the addiction to outmoded ROI proxies. And startups lack the necessary scale. It seems a strange case of capabilities surpassing the market for them.

  3. Peter

    Well written article, Chris. While I agree with you that dialing in targeting too much, or focusing entirely on re-targeting (common for “performance-minded, DR advertisers”) doesn’t do much to create incremental sales generation but simply makes existing sales more efficient, I disagree that RTB/ programmatic buying is the problem. The targeting is the issue! RTB is purely about buying the best available impression at the best cost to serve the right ad to the right user at the right time. Advertisers should care about these factors, just like they do with their television buys (which channel and during what hours do they reach their target audience). There are multiple ways in which to create a larger custom audience beyond site retargeting. Look-alike modeling is a great example (which you’ve mentioned), so is search retargeting, email domain retargeting, or even leveraging 3rd party data sources… Finding the right targeting parameters is different for each advertiser and campaign. But once it is dialed in, RTB should help make the buy more efficient and increase performance. Just my two cents.

  4. Great call, Peter. I agree that RTB tactics can be used for profit optimization. My point was bascially that sometimes we sacrifice growth for efficiency in spend, and we seem to have created a lot of attribution metrics that favor precision rather than growth. As an example, leveraging geotargeting inside of RTB (along with context signals) would be the perfect tactic to raise top-funnel awareness among neighbors.