Continuing to think about the decision journey. With a broad brush, wondering how–given the latest studies in decision science–brick and mortar retailers can more effectively nudge shoppers toward mutually beneficial decisions. With a narrow focus, exploring the value of recommendations. Types of content and where and when, by segment, they have the most impact.
And, of course, personalization. What it means, and what it takes to deliver it in ways that matter.
With a furrowed brow, three thoughts come to mind.
Forrester’s wise Brendan Witcher made a great point the other day. When it comes to recommendations, it’s more about the relevance than it is the content. Relevance to an individual shopper. At a specific time and place. In other words, true, one-to-one personalization.
Strong agreement (of course) with Brendan. And he also acknowledges the challenge: Relevance is not a destination, but a never-ending journey. A journey paved by an ongoing dialogue with an ever-changing human being.
Millions of them.
Think of what ongoing dialogue will reveal. Think of the data categories you’ll need to capture all the information. Perhaps hundreds, thousands more categories than allowed by current systems. Hundreds, thousands more categories than used in current processes.
Semi-bald male, connoisseur of Russian history, Cleveland Browns, and Bayern Munich fan who dirties his hands each week in the at-home rose garden, partial to the Rolling Stones, manual-transmission cars, Beethoven’s Ninth, and cedar-grilled salmon . . . .
The take-away question: What is your comprehensive, relevance-driven data strategy?
How will you get what you need to be relevant—with resonance?
A second thought: Yes, it’s about dialogue, but to obtain resonant relevance, that dialogue will need to progress from a simple, mostly opaque transactional interaction to ever-deepening levels of intimacy.
A telling analogy? Human conversation. A transactional interaction happens every day at check-stands. It may reveal attitudes on the weather, but little else.
Yes, you can create processes (and spend money) to win e-mail addresses and social media connections, but ultimately, the intimate, data-rich interaction that we want will only unfold in an atmosphere of trust.
The kind of trust you share with a spouse, a best friend, or a twin sister.
The transactional can happen anywhere at any time. The intimate is earned (and expands) over time.
Big question for us in retail: How can we begin to earn such trust?
Perhaps, if we listen to Geoffrey Moore (as we should), we’ll learn it’s won on the operational side.
Could better POS queue management equal more and better data?
A third thought: I wonder if retailers (and their technologists) must simultaneously work on two sides of decision-journey management. Especially in the brick and mortar environment.
One side will be about deep-and-wide relevance with resonance. Hugely data-driven. Call it the “personalization” side. It’ll be defined by increasingly-intimate relationships with brand loyalists. The individuals who browse and purchase to the tune of higher margins across all the channels. Perhaps equaling 20 to 25 percent of your unique shoppers.
They’ll use your app, use your promotions, and give you a hefty share of wallet.
They’ll trust you, and as the years go by, offer ever more data richness–which will lead (for those retailers well-prepared to use it) to a lovely spiral of growth.
The other side will be about the anonymous shopper. Perhaps now 75 to 80 percent of the unique visitors. You’ll have knowledge about them (and, for data-smart retailers, lots of knowledge), but they may simply not be interested in a dialogue.
Let us not forget that, like ballroom dancing, dialogue takes two.
Yes, you can approach the anonymous shopper as one of a large cohort, but here we need other intellectual tools. This is where I increasingly believe we need the industry-wide exploration of the new decision science. The application, for example, of the work of Paco Underhill, and the lessons found in the new Journal of Shopper Research and online at https://www.behavioraleconomics.com/.
Next time: A behavioral economist does retail. And what we can learn.