Advertisers Have the Data. What Comes Next?

It’s no secret that brands have been using first-, second- and third-party data to deliver more personalized advertising experiences for customers. And for the most part, surveys show customers appreciate it. But all those customized Amazon pop-ups and Netflix entertainment recommendations consumers receive every day could soon fall victim to their own success. This is because, just as listeners eventually tired of hearing overplayed hit songs on the radio, consumers too may grow weary of retargeted ads—and wind up ignoring them. What is it you truly desire? Think of hyper-personalized ads as a digital concierge that can anticipate customers' needs and direct them to what they want. Whereas today brands use historical data to serve up cursory buying recommendations, tomorrow they will collect, aggregate and analyze a wider array of information and truly cater to specific customer’s needs. Also known as “Segment of One,” many brands and advertisers are moving from catering to cohorts and segments to individually serving the needs of the consumer. As a result, they’ll be more likely to capture a customer’s attention and ensure their purchase. For example, imagine browsing overcoats while sitting in the lounge at San Diego International Airport in early January. A traveler is headed to Chicago, where air temperatures are frigid and snow is in the forecast. Moments later, while browsing a site, a pop-up suggests checking out a long brown coat that just happens to be on sale. But in a hyper-personalized world, an algorithm may have known the traveler was waiting at the airport. It would have consulted weather reports, traffic conditions and airline schedules. It could then provide a wider range of suggestions: winter hats and umbrellas, ideal transportation options to and from your hotel, restaurant and theater ideas for the traveler’s downtime. Because those things matter in the moment, a traveler is more likely to pay attention. This is just scratching the surface of possibility. Hyper-personalization is really a way of diving deep into data to make it work for the customer. Instead of pushing ads that pitch things they want to sell, brands could instead use data, analytics, artificial intelligence (AI) and machine learning (ML) to understand and engage customers based on the context of their behaviors: What were they doing at the time they were viewing a product? Where were they? What were their surroundings? How were they feeling at that moment? What was their life situation? Were they married, a parent, single, working, looking for work? All of this matters. Differentiation in the evolving digital world will depend entirely on a brand’s willingness to go beyond the surface to hyper-personalizing ad experiences for a customer. We are already seeing signs some companies understand this necessity. And in the upcoming cookieless world, future brands must collect first-party data on customers and prospects, in an opt-in data and privacy compliant way, to deliver hyper-personalized experiences. Without it, a brand lacks the ability to develop a personalized relationship with their customers. Differentiating in the age of hyper-personalization By delivering targeted ads to customers in more sophisticated ways, brands not only generate more goodwill through better experiences, but also create more revenue opportunities. It goes without saying that if customers click on things because they speak to their needs in the moment, they’re more likely to buy. If they don’t click, the odds drop precipitously. Investing in technology to enable hyper-personalization, therefore, becomes a no-brainer for the bottom line. Last year, for example, people watching the Discovery Channel, the Food Network and Animal Planet were treated to a commercial about a new brand of frozen yogurt bars. Not everyone saw the ad. The advertisers reportedly analyzed personal data and then streamed the ad to viewers who were identified as most likely to care about leading healthy lifestyles. Additionally, German railway company Deutsche Bahn’s "No Need to Fly" campaign used a combination of AI and geotargeting technology to pour through customer data on social media sites, identifying what international travel destinations people were considering for vacation and then juxtaposing similar in-country images to encourage them to vacation closer to home (via railway stations). Deloitte estimates hyper-personalization can deliver ROI of up to 800% on marketing spend and lift sales by 10% more. At the same time, Netflix’s recommendation engine has been instrumental in customer retention, as 80% of users follow recommendations while only 20% search for content. Conversely, the professional services firm warns that ignoring such opportunities can lead to higher customer churn, lower ROI on ad investment, fewer impulse purchases and higher product returns from customers who do not feel the brand or product fully understands their desires. Looking ahead It’s true that the path to using customer data for hyper-personalized experiences won’t be easy—but done right, it's the core of a great digital experience. By rethinking how businesses engage with customers and their personal data, businesses can gain a better understanding of what drives behavior and build a mutually beneficial relationship. Because as McKinsey’s most recent Personalization 2021 Report revealed, hyper-personalization is not going anywhere, with 71% of consumers expecting companies to deliver personalized interactions and 76% frustrated when it doesn’t happen. We’ll soon see more disruptive brands step forward to transform digital advertising—because they must.

Voice

Advertisers Have the Data. What Comes Next?

Hyper-personalization is the core of a great digital experience

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Christopher S. Dean

Programmatic

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