Commentary

AI Puts Data In Driver's Seat

We all know creative has historically driven the advertising planning process. Media has largely taken its cues from the “big idea,” and digital advertising has played as backup band to the main message and traditional media channels such as print and TV.  

But times have been rapidly changing, marked by milestones such as digital media spend surpassing TV media spend in 2016.  The days of advertising campaigns founded primarily on big creative ideas appear to be dwindling, and data is stepping up to play more of a leading role.  

A recent Forrester report written by Joe Stanhope, "AI Must Master the Basics Before It Can Transform Marketing," points to numerous ways we can expect content and creative to be more closely tied to data strategies in order to achieve “efficiency, smarter decisions, speed, continuous performance improvement, and customer journey optimization.”  

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In a conversation about the study, Stanhope said Forrester clients are asking for more ways to create content personalization, and AI tools provide a path for doing this at scale.  As the report title suggests, there are some basics to address, especially the role data strategists will need to play in setting the stage for creative executions.

The new creative palette draws from an avalanche of data ready to be exploited by AI algorithms. This unlocks a new level of information about each and every person with a social profile by capturing “data exhaust” from their interactions and posts, revealing hints about their motivations and beliefs.

Doing the work of the insights department, which has traditionally employed various forms of research to uncover emotional drivers and buying intent from which to target and personalize campaigns, AI algorithms can assess how people think and feel in real time.  This can obviously happen a lot faster than with traditional methods and delivers far more granular segments.

Stanhope quipped, “If you are operating AI at scale, will the insights department primarily become a monitoring function?”

Still, his report more seriously calls for joining forces with the customer insights team when using AI to effectively manage data, define KPIs, and assign goals.  

Let me give you an example of an AI targeting strategy that produced very specific information leading to an equally specific messaging strategy:

You may have heard of the AI firm Cambridge Analytica, which by now is famous (infamous?) for its help in winning the Brexit vote and later the Trump presidential campaign (Steve Bannon sits on the board). Using AI, the company has built a database of approximately 300 million profiles in the U.S. that include “Myers Briggs-like” personality traits.

Presumably, in the case of the 2016 Presidential election, Trump’s team applied this data to identify Democrats who were still on the fence, and then served messages (cough, fake news, cough) meant to keep them there (i.e., stay home on voting day.)  The Trump campaign denies this, and I’m not debating its exact strategy.  But I do want you to think about the significance of being able to exactly target Democrats who hadn’t yet made a decision, as well as the process of exploiting that information. To execute, the creative brief would be born of the data strategy, versus the other way around.  In terms of the campaign’s success, I will let you be the judge.

Renee Bunnell, founder of another psychometric AI data platform called REAL, which uses character strengths (vs personality traits) to define target audience segments, cites improved engagement rates of four to eight times better than the best previous methods used.  

I don’t know about you, but that gets my attention, and it fits with the heightened interest brand marketers are showing in increasing their personalization capabilities.  It’s another example of using data to inform creative automation, an important next frontier for delivering meaningful ROI lift.

In order to deliver on AI’s promise, most agencies will have to grapple with structure and process, bringing data and analytics closer to creative development.  There are a few new agencies, such as Born-AI,  that are configuring around AI technology.  Co-founder Max Fresen (an ECD by training) says, “The great promise of AI is to unlock empathy. By understanding humans, machines can respond to our needs and wants with emotionally appropriate messages, and can earn our trust.”  Other agencies are looking to inject AI into their existing work processes by investing in leadership to evangelize and execute AI-driven strategies

Crossmedia recently appointed Karim Sanjabi (a longstanding thought leader and digital entrepreneur from the Bay area) executive director, cognitive solutions (cool title!) to do just that. 

Sanjabi’s philosophy connotes a data-centric model: “Creative is a core part of the cognitive solutions we offer. The tools and techniques at our disposal demand a vastly different approach to data, planning, analytics, and creative than a traditional model.”  Both agency models address AI as the beginning of something big, and commit to the long game in delivering on that promise.  

As Stanhope’s report professes, “AI provides the cognitive scale brands need to keep pace with escalating customer demands, the deluge of data and content, and almost limitless customer journey permutations.”  

Among other things, he urges that we “anticipate the intense content requirements for AI powered systems,” and he lays out the first necessary steps to take in this journey.  “Buy into AI for the efficiency, stay for the performance,” Stanhope suggests.  Certainly a part of this will include putting data in the driver’s seat and bringing creative along on a new ride.

2 comments about "AI Puts Data In Driver's Seat".
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  1. Henry Blaufox from DragonSearch, June 16, 2017 at 11:37 a.m.

    AI will probably help further identify the target audience "hot buttons" for messaging. But if the audience is too narrowly defined, isn't there risk that the individual message won't have more than a marginal mpact on total sales, because the audience size is too small? P&G ran into something like this last year, if I recall correctly.) If that is true, AI segments could become overkill. Also, good creative will still be important. The well defined target audience doesn't matter if the message isn't good enough to elicit the desired response. A bad ad is still a bad ad.

    As for Cambridge Analytica, afte explring their own site, I wonder how much impact they actually had, and how reliable their methods really are. There is a com pany video on the site Ior there was when I checked a few months ago.) In it, the firm CEO explains what transpired. For starters, they were hired first by Ben Carson, then the Ted Cruz campaign. Both were blown out by the Trump campaign, of course. SO the CA method lost before it landed with the ultimate victor. By the time Trump brought on CA, he had the nomination sewn up.

  2. Sarah Fay from Sarah Fay replied, June 16, 2017 at 3:03 p.m.

    Thanks for these thoughtful comments, Henry.  You are certainly right that Cambridge Analytica (and any tech platform) could never have won these campaigns alone.  You can make the case that the Trump campaign also had the big idea that the data and targeting strategy supported.  But it does tell the tale of data's increased importance in the mix.  

    As to the many segments and messaging strategies that AI helps to create, remember that this is still a scale play - AI has the ability to surface and exploit the many narrower targets in a way that has not been previously possible.  I think my article might make it sound as though I no longer believe in the big idea, which is not the case - I believe that a unifying message can give credibility and meaning to a brand at the same time micro segments are leveraged with more personalized and relevant messages that convey value to the individual - and data driven creative will play an increasingly important role in doing this.  Perhaps in another post I will go deeper into how these things exist together...

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