Your Current Metrics Are Failing You

Uncrowd
Uncrowd
Jul 15 · 3 min read
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This article was originally published December 3rd, 2019

You’ve asked customers how to improve, maybe you’ve asked customers why they shop your rivals. They’ve told you that it’s about price, choice and convenience. They always tell you that.

You try to be cheaper, offer more choice and be the easiest to shop. You think about friction and pain-points. Your pick-ups with NPS detractors appear to reveal useful insight. Improve delivery, they say, put more staff on, they implore. Always a headline without context.

You do all the things your c-sat, preference, insight and promoter metrics tell you to do and nothing much happens. At best, you’ve maintained a standard, at worst you’ve added cost.

Though we know customers lie — what they say rarely aligns with what they do — the voice of the customer feels instinctively like it means something significant, so we take it at face value even though it’s warped and lacking context.

I’ve been writing about creating amazing retail experiences for 16 years, my books feature case after case on the best in global retail. One thing ties all of those successes together; an instinctive understanding of their customer. That’s special but incredibly rare, and unsustainable over time. Walmart rises, falls, rises again. M&S rises, falls, then… Relying forever on instinctive brilliance is clearly not the way forward. Celebrate it when you have it but strategically you need a different approach.

That’s where I was when I decided there must be a better metric to explain why a customer prefers retailer A over retailer B. Or C, D, E… NPS was the only half-decent option and that’s missing measurable and comparable causality.

What use is a macro metric anyway? A number that describes a catch-all is worse than useless, it obscures the useful highs and the attackable lows.

A better solution looks like this: think in terms of individual shopper missions and of your ability/likelihood to win each one. Then look closely at your performance across key missions versus competitors. You’re looking for the specifics of why you are the most attractive option in that mission.

Uncover that, the contextual specifics of your relative position, and you then have a map for delivering strategic improvement; you’ll see if it’s queuing over inspiration, theatre before trust.

So then, it’s the question of what variables and in what relationship to each other? That was the missing part of the puzzle, a solution to which we’ve spent two years crafting. When you know all your customer inputs and your customer outputs and the relative relationships between them then you get a crystal clear picture of which combination of levers delivers the experience most likely to put you in a winning position in that shopper mission. Do that mission by mission to win mission by mission. That’s why Friction/Reward Indexing had to exist, because without it, we’ve been running blind. Too much guess, not enough data-driven truth. No more!

The Uncrowd

After the customer analytics herd there is the…

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