The challenge of relevance

According to Rob Walker, PhD, vice president of decision management at Pega, relevance is "providing customers the answers or information they need based on what’s known about them, along with what is likely on their minds."

Walker's point takes us back to the human element of marketing. In the same way your best friend might know that you bought a new TV online last week, adept marketers will use predictive analytics to shape their message, based on what the customer has done, and might be looking for.

Using a newly purchased TV as an example, Amazon.com would be doing itself a disservice by serving you offers on new TVs. A relevant execution, however, might include a new TV stand or home stereo system.

Predictive analytics help anticipate customer needs and, by extension, help form meaningful digital relationships rooted in understanding.

Context is key

Walker describes context as "using real-time data to deliver that relevant information in the moment, with an understanding of the customer’s mindset, as well as their information needs."

In other words, the difference between relevance and context is the timing in which data is gathered. Determining relevance is based on a large body of historical data on the customer, while context is based on in-the-moment behaviors.

Using the TV purchase example from above, a contextual offer would be delivered when a customer is, say, browsing stereo systems on a competitors website or when a customer abandons a cart on your website.

Understanding your customer's unique needs and providing a relevant and contextual offer is part of what Walker claims to be a new movement in successful marketing — one marked by personalized targeting philosophies that treat customers like entire campaigns were designed just for them, not the masses. In Walker's words, "relevance simply requires context, because what seemed relevant only moments ago (before the customer said 'no,' clicked 'yes' or became upset) may no longer be."

However, with this move toward intense personalization comes complexity. Highly personalized campaigns informed by predictive analytics cannot be managed in real time by a marketing team — there's just too much volume to deal with. Instead, the companies that succeed rely on customer relationship platforms that can execute thousands of predictive functions per minute.

At scale, Walker says that relevance and context "opens up a new world of creating deeper, more personalized and more valuable relationships with your customers."

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