Challenges of Data-Targeted Advertising: The Publisher’s Perspective

By Thought Leaders Archives
Cover image for  article: Challenges of Data-Targeted Advertising: The Publisher’s Perspective

Working in ad sales, a lot of what I hear these days is “data, data, data.” I am not dismissing it. Data is, and will be, important to the media business. Big data can give us valuable insights into audiences, programming, media planning, attribution and more.  But I worry that in our eagerness to embrace data -- especially data-targeted advertising -- we’re forgetting the power of content.

For ad buyers, the promise of data-targeted advertising is exciting.  More than 100 years ago John Wanamaker said, “Half of what I spend on advertising is wasted; the trouble is I don’t know which half.”  Buyers believe that with data-driven targeting, they can finally know which half and spend more efficiently.

But what about the people who sell advertising?  If buyers could really spend half as much and get the same results … that’s not necessarily good for publishers.

The answer I hear to this predicament is always price.  Being able to hit a target with no waste should be worth more. In the Wanamaker “half is wasted” example, if the price or CPM doubled on the right half, then even if Wannamaker only bought that half, publishers’ revenues would remain intact.

How realistic is this? Do we think advertisers will agree to increase price at the same rate as any gains in efficiency they achieve through targeting?

I am not so sure they will. More importantly though, the extent to which they are willing to pay that premium is going to vary across publishers. It will depend on how high a publisher’s CPMs are today and the supply constraints on that publisher’s inventory. Even with targeting, there is a ceiling as to how much an advertiser is willing to pay.

The next comeback I hear to this point -- that there are limits to price increases – is that (again using the Wanamaker example) CPMs need to go up but they don’t need to actually double because the publisher still has the remaining half to sell. But what is that leftover inventory worth? It could be that the leftovers are people of lesser value to buyers because of their age or income. Or perhaps they are very valuable, but we don’t know that because they clear their cookies, are on an unmeasured platform, or their device ID or identity isn’t available or is not being shared.

Either way, from the publisher’s perspective, who is going to buy that leftover inventory if your existing client base is buying on a targeted basis? And how much will they be willing to pay for it?

For a seller like Google or Facebook, awash in supply, data targeting is a no-brainer. Both companies may be growing rapidly but they still don’t come close to selling all of their inventory, and there is a big spread between the price they command versus the top of the market. With data targeting they have nothing to lose, and it is probably convenient for them that data targeting commoditizes content while placing a premium on the rich data assets both control. Meantime, for a premium publisher with high CPMs and sell through, the math is different.

At ABC, we call this the lift-versus-drag challenge. The idea is: Will the lift, or premium, a publisher gets on data-targeted buys exceed the drag, or discount, a publisher has to offer on the inventory that’s left over after advertisers have cherry picked their targeted audiences? An inconvenient truth is that a lot of advertisers are chasing the same niche of high-value consumers.

In fairness, I don’t know the answer to the lift-drag challenge. But it is an important question, and one that any capacity constrained video publisher needs to explore.

Of course, all of this assumes data-targeted advertising is more effective for the advertiser – that it unequivocally drives more sales.  But does it? Again, the answer probably varies.

Recently, two marketing giants made surprising changes to their strategies. I will discuss these changes and our independent research at ABC in a column next week, when we tackle some key challenges of data-targeted advertising from the marketer perspective.

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