his and her ugly sneakers
PHOTO: Atrueleo

At the beginning of last year, dad sneakers trended in a big way. For those of you who may have missed it, a “dad sneaker” is a big bulky sneaker, the kind your Dad might have worn 20 years ago. Thanks to celebrities like Kendall Jenner and social media tools like Instagram, dad sneakers became a thing. Retailers took note and started producing big bulky sneakers to meet the demand. As of the writing of this article, the popularity of dad sneakers shows no sign of wearing down.

Is Your Business Running 12 Months Behind the Trends?

I mention this footnote for a reason: trends like this are happening all the time around us. In our age of social sharing and uber-connectedness, companies that can capitalize on emerging trends like this have a real competitive advantage. But therein lies the challenge: even so-called “actionable” insights rarely arrive in real-time. Instead, it could take months before trends like dad sneakers are detected because of the time it traditionally takes to collect and analyze data.

While accelerating insights is important, it’s not the only bottleneck. If you look at most marketing campaigns, they follow a very deliberate pattern:

  • Identify the various customer segments.
  • Create a campaign/offer for each segment.
  • Execute the campaigns and measure their performance.

For a large consumer packaged goods company, this entire process, from ideation to execution, can take up to a year. During that time, new trends have come and gone, early market entrants have already established their brand and you could be entering a market that has already shifted significantly since you formulated your original strategy.

Editor's Note: This is the final in a three-part series on mastering the art of audience-driven marketing

True Personalization Is Closer Than Ever Before

Customer data platforms (CDPs) have the potential to break this bottleneck by allowing marketers to do real-time decisioning and predictions. Instead of dozens of manual decisions about who gets what offer, when and through which channel, CDPs can do all this automatically by making real-time recommendations for each offer based on individual content affinities and behaviors. And CDPs also provide real-time feedback to let marketers know how their campaign is performing, so they can adjust it or roll it out to wider audiences without waiting weeks to get the results.

The sheer number of decisions that need to be made in marketing also make it a natural fit for machine learning. Machine-learning algorithms can uncover the why behind the what: Did Jane Smith buy a pair of sneakers because of the comfort, color, price or is it part of a social media trend that hasn’t appeared on the radar yet? Taking this a step further, marketers can use this data to predict future trends and buying decisions. If an online travel site sees an uptick in interest for flights to Tahiti, is it a reaction to a cold winter, a hot location, lower costs or is it trending as Kim and Kylie go in search for the perfect pina colada?

Managing the speed of decisioning is critical as marketers compete to deliver personalized, relevant experiences. As we’ve seen in this series, companies need to tune into audience signals, understand which features are really impacting those signals, listen to what their data is really telling them, and act quickly on those insights. It’s a far cry from the way many businesses market their products today, but with technologies like CDPs and machine learning, true one-to-one marketing is closer than ever before. If, however, you’re counting on the same old customer segmentation to create great customer experiences, you’re just waiting for the other (dad) shoe to drop.

Related Article: Decisioning – The Only Way to Accelerate Analytics to Value