Wanamaker, a Philadelphia department store legend, famously said, “Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.”
Because Big Data allows companies to serve up online ads (display, native, pre-roll, etc.) to people who’ve demonstrated interest while surfing, it sounds like the recent trend in programmatic advertising would render Wanamaker’s quote obsolete.
And this hope is precisely what’s getting so many DMOs excited — a better metric and a clear return on investment.
But would Wanamaker, if he were alive today, still claim that a large part of Big Data advertising (aka programmatic advertising) is “wasted” and not know which part? Probably.
Why? Let’s say you’re only showing Coke ads to people who say they like Coke. Chances are you’d be “wasting” ads on people who were going to buy Coke anyway.
And this is the same basic issue destinations face with Big Data. They are serving ads to people who have demonstrated intent and then taking credit for the conversion even though many of those people were already planning to book trips to that destination.
Casey Soulies, a digital marketing veteran at Mering Carson who looks after the online advertising for Visit California, put this way:
“It shows ROI for the money spent on the programmatic advertising, but it doesn’t factor in the millions of dollars spent on top-of-funnel inspirational advertising that likely contributed to many of those bookings.”
In other words, Big Data advertising takes advantage of a major disconnect in the funnel. Cree Lawson, the CEO of Arrivalist (a marketing services company), told me:
“There are three big online intent signals in tourism.
1. They visit a destination information website [e.g. the DMO’s site, the destination’s TripAdvisor page, the destination’s Lonely Planet page, etc.].
2. They search for a term in the destination [e.g. MoMA, Central Park Zoo, Grand Central Oyster Bar]
3. They search for a specific flight or hotel.”
Who demonstrates this sort of online intent? People who are passively thinking of visiting, people who are definitely planning to visit, and people who are very interested and could be nudged off the fence with the right offer.
Ideally, DMOs want to target this last group exclusively with these well-placed online ads (sorry, impossible… for now) and by the time a statistical effectiveness survey could be measured (if that was even possible), the campaign would be over.
Another hypothetical way to analyze efficacy would be to track bookings for a large sample of people who exhibited intent and saw a destination’s online ads and compare those results to an equally large sample of people who exhibited intent but didn’t see any online ads.
The problem is that there are almost always print, radio, and TV campaigns going on in addition to the online advertising, plus other variables in the media, which would make it extremely difficult (perhaps even impossible) to create any effective control group and isolate the effect of just the online advertising.
“The key to interpreting this data,” says Lawson, “is the word ‘incremental.’ If you compare your figures before you start running ads with the figures you get after you start the ads, hopefully you’ll notice an uptick. It’s that uptick that represents the most interesting portion of the spend.”
Considering these various shortcomings, big data ad buys and the analytics produced by them may not be quite the easy gain they seemed to be at first glance. But they still offer appeal.
“We’re finding value in the current tools,” said Dan Mishell, Visit California’s Director of Research. “But in terms of where we’d like to see it go, the next data evolution is to be able to show influence instead of coincidental exposure.”
“Even if you factor in some redundancy, it targets a particular audience with effectiveness and it does generates some useful analytics.” – Casey Soulies, digital marketing expert at ad agency Mering Carson.
As John Wanamaker would have likely announced with a smirk, “Half the money I spend on programmatic advertising is wasted on people who were buying the product anyway; the trouble is, I don’t know which half.”
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