Actionable Insights, Instantly!

Ever heard of Rapid Relevancy? Put simply, it is human conversation made digital.

“But we already do that,” you say. Not quite …

Most customer engagement delivers clunky conversations, driven by a mishmash of customer likes, dislikes and other basic information. Rapid Relevancy lifts the conversation to a more intuitive level — fast.

If we compare how online conversations compare to real-life interactions, there’s an awkward gulf. Humans use millisecond analyses of non-verbal signals — tone of voice, inflection, words, physical gestures, body language, facial expressions — that computers are not equipped to match.

We subconsciously intuit and adapt what we say next. Then we repeat the process, making infinitesimally small adjustments that move the conversation forward. It’s an art that has evolved over millions of years.

Rapid Relevancy seeks to digitally emulate this instinctive interaction by identifying not just the basic information, but also the nuances, as they happen, and continually asking the question: “What next?” In a way, it builds on the “related recommendations” or “related searches” approach utilized by Google, Amazon and YouTube.

And it’s now a system store brand marketers can use — for each and every customer.

It’s our response to the changing landscape of customer relationship management — a way of building incremental layers of relevancy, faster and deeper than traditional e-marketing.

The goal is to create more value from customer conversations. Sometimes that comes from the store brand talking; at other times, it’s about knowing when to be quiet and let the customer run the conversation.

Complex response radars can tell us how well we’re listening, and using real-time technology, we can pick up every morsel of customer information, mid-flow. All that information gets turned into accurate, actionable insights.

This heightened ability to listen, evaluate and learn creates a highly personal response. Each piece of feedback creates a deeper, richer appreciation of the individual customer.

Imagine a consumer is looking up a story about the latest diet craze on a news website. Based on that search, she could be served advertising for store brand products or related articles on the effectiveness of the diet. However, by applying Rapid Relevancy in real time, we might learn that just seconds before, she was browsing the celebrity lifestyle pages and reading articles about Hollywood stars.

This instantaneous insight tells us that the consumer might be more interested in celebrity news than losing weight. Advertising for store brand products or related articles (such as sponsored recipes), therefore, could be more relevant if it uses a celebrity angle rather than a diet focus.

Rapid Relevancy draws on the analytical power of three crucial dimensions:

• ■ An individual’s known characteristics (e.g., age or gender)
• ■ An individual’s transactional history (e.g., past purchases or services) and, therefore, predisposition to make a store brand purchase
• ■ An individual’s interaction with content within different media (e.g., online, e-mail, social media or offline options).

Whether related to news articles, products or service offers, the same approach could be applied to increase audience engagement and push significant sales increase.

Of course, that level of insight is complex, but it demonstrates how advances in technology are making the ebb and flow of conversation with store brand customers more intuitive and meaningful. The rewards, however, are significant: faster, deeper customer engagement and, in turn, an improved bottom line. In short, more better-qualified, more-responsive customers who are buying more. Nice.