December 11, 2013
Targeting involves a lot of guesswork. Just because someone visits a site, dwells on a profile or engages with some content does not necessarily make him or her a prime candidate for your campaign.
The digital ad industry has evolved from site-level retargeting and search and social retargeting to more controversial forms of behavioral targeting. And whether an advertiser wants to convert transactions, build audiences or simply know its customer, these ad targeting techniques still have room for improvement in one vital area: the use of consumer data.
We have come a long way, but not far enough. Is it not unacceptable to advertisers that targeting techniques are still, for the most part, experimental?
Here is a snapshot of what we are talking about:
• Site retargeting. Site retargeting re-markets to current customers.
• Search retargeting. Search retargeting seeks to engage new consumers from an audience that has shown some interest in a brand’s product via past searches, where there is no existing relationship to the consumer.
• Social retargeting. Social retargeting uses purely interest-based information from consumers’ social profiles to identify and create an audience, whether or not they have ever engaged with the brand’s product or a related product.
• Behavioral targeting. Behavioral targeting is less about fact and more about inference. As a result, marketers may be less likely to reach qualified consumers through behavioral targeting as compared to search retargeting.
• Predictive targeting. Predictive targeting leverages a wealth of data to locate qualified audiences – many of which have never before interacted with an advertiser’s brand – broadening opportunities to bid for new customers.
1. Power and technological advantage of mobile technology for predictive ad targeting
The combination of real-time bidding (RTB) and the ability to single out a consumer among millions is what begs for the capability to predictively target.
Now, instead of throwing campaigns out there and hoping for the best, we can use artificial intelligence-like technology to process millions of data-points in real-time, and deliver that to the advertiser so they may refine and optimize their message, creative and targeting on the fly.
When you think about the world of possibilities that mobile devices open up – knowing where and when consumers engage with an advertisement, combining that with who they are and where they live, what they like and how often they listen or view – mobile is a powerful medium.
However, it is the ability to harness all of this data scientifically and use technology to process and understand what it means that changes the game. Providing this data to advertisers so they may predictively target their consumers is a giant leap ahead in targeting science.
2. Remove the guesswork completely
Today in mobile advertising, we can use science to predictively target only the audiences that are most likely to convert, every time, with unprecedented accuracy.
I cannot tell you how many times large brands have come to us, telling us who their audience is to target, and post-campaign we reveal to them that they were wrong.
Advertisers often miss likely customers due to pre-determined parameters of a target that are incorrect or incomplete.
3. How predictive targeting works: No two impressions are alike
The only way to combine the various factors that advertisers need to measure to create and deliver optimized campaigns is to analyze the audience profile of each and every potential ad impression.
Next, you need to enrich this profile with first- and third-party demographic, behavioral, psychographic, environmental, sentiment, keyword and other contextual insights.
Ultimately, the ideal audiences are identified and shown the advertiser’s ad, and less optimal audiences are not.
4. Predictive science: Employing proactive-reactionary targeting
What does this mean? Mobile technology has moved us past the ad targeting guesswork and into highly advanced predictive modeling, where advertisers can now determine the likelihood of conversion for a given ad impression.
And as each campaign is run – as hundreds of thousands or even millions of data points are retained and analyzed – advertisers can refine and optimize their campaigns on the fly to achieve higher conversions.
ULTIMATELY, BECAUSE of mobile real-time bidding, the power of predictive targeting lets advertisers continue to build their audiences exponentially while reaching existing consumers where and when they are most likely to convert.
It is all about the economy of results, and growing those results.
Anthony Iacovone is founder/CEO of AdTheorent, New York. Reach her at firstname.lastname@example.org.