Know who your most valuable customers are, hint... it isn’t about a persona

Knowing who your most valuable customers are (and what they want from you) can be a game changer but figuring that out requires starting from a different place than the common launch pad of personas or demographic profiles.  

All customers aren’t created equal and shouldn’t be treated equally either. Yes, with your customer-facing service hat on that sounds almost heretical. Like something you should be whispering if you say it at all. But it’s true.

Let’s unpack.

Some customers get more value from your service and thus create more value for your service. Others get/create less value but can still consume just as much of your precious time and attention.  

The trick is knowing the difference and orienting the work across your teams accordingly to your highest value customers:

• How do we find more of them?

• How do we evolve the product/experience to serve them better?

• How do we know when we’ve moved the needle for them?

• How do we avoid spending time and energy on stuff they don’t care about?

And to get at who your most valuable customers it helps to start with Customer Lifetime Value (CLV) based on actual customer activity, NOT with pre-determined profiles or personas.  

Why? Because chances are your best customers are way more heterogeneous than it seems.

If you limit your focus to the attributes you can neatly capture in composite personas like Performance Paula and Convenience Carl, you exclude a bunch of potentially great customers who look a lot different but add a ton of value. Not just in terms of spend but also in terms of critical clues on what to build next, where to look for more like them, etc.    

Let me give you an example from a project in the consumer space…

In a round of customer interviews in the nutrition world I came across two people (I changed their names below, feels very investigative journalist-ey) who by any demographic or persona measure couldn’t be more different.  

Steven - Retired international biz executive, in his early 70’s, living in an affluent suburban neighborhood in a single family house, he and his wife adjusting to health challenges and associated disruptions to their routines.  

Beth - Late 20’s professional, CrossFitter, living in a small apartment, she and her husband managing a full city life juggle of work, fitness, social life, etc.  

Yet when I talked to them about what they were managing in their lives and why the service in question was helpful to them, they articulated quite similar underlying challenges - limited time, hectic/interrupted schedules, spouse cooking less, etc. - albeit for VERY different reasons.  

Wilder still… when we got to discussing their current experience with the delivery part of the solution, Steven and Beth both cited limited space as a big challenge with the delivery bags in between deliveries.  

Really?  A retired couple in a big house, and a young couple in a small apartment, landing on a similar challenge/potential problem to solve… from completely dissimilar starting places.

How did I find these two people to chat with in the first place?  We had run CLV based analysis of customer data to find some high value folks to chat with. Lo and behold, these two - who would NEVER fall into similar persona buckets - turn out to both be very high value customers.  

All of a sudden the thinking about how to improve the current experience expanded. Turns out space matters to more people than we thought. You can have suburban, center-hall colonial amounts of space in your house but still feel like you’re living in a second floor walk up in the city.  

And the consideration set for potential audiences to reach and where to find them expanded too. Steven for example had heard about the service through one of his children, someone we would previously have spoken to with a different message.

Point is it’s easy to get romanced by the simplicity and living color of personas and profiles which are so often the language stakeholders (agencies, investors, colleagues) want to talk in.  But the reality is your best customers are quite likely more defined by overlapping needs than they are by caricature.

So to see improvement and growth opps more clearly, we need to flip the conventional customer understanding approach on its ear.

Instead of focusing on predetermined personas/segments to which we then attach value based on activity data.

We should start with CLV calcs based on real customer activity data and THEN work to figure out which characteristics separate higher and lower value customers and build segments around those.  

That work might result in some persona-esque elements, but chances are it’ll land you with a mix of indicators that while not as neatly packaged, are much more actionable and instructive.

And maybe most important… when you embrace the heterogeneous nature of your customers and loosen the grip on trying to fit demographics around them, you tend by definition to focus more on understanding the actual job they turn to you for, the progress they want to make in their life that you can help with.  

P.S. A good read recommendation (particularly for non-contractual, repeat purchase consumer businesses) if these notions of starting with customer lifetime value and not all customers being created equal interest you… Customer Centricity by Peter Fader.