quant vs qual customer health

Ever had a customer (or client) tell you in advance that maybe one day they’ll consider leaving?

Or has it been more sudden and without so much warning?

In Saas there are quantitative signals and qualitative signals when it comes to customer health. Quantitative signals are things like product usage, tenure, adoption, user activation, engagement.

Quantitative signals are based on actual behavior. A customer either uses your app or doesn’t. A big customer adds users from inside the company or it doesn’t. This is hard data.

Qualitative signals include things like sentiment analysis and questions about roadmaps and workarounds.

Quantitative explains what happens. Qualitative can explain why it happened.

Product or app usage is a real indicator of customer health. How engaged are they? Do they regularly get value from the product? Given analytics tools, it’s also possible to see when customers do not use products or features or experience key moments of value.

I’ve been reading up on customer health scores and there’s a lot of talk of adding in lots of qualitative signals. It makes me think I need to be part shrink, part customer success pro, to understand the real intent behind people’s behavior.

Hubspot apparently calculates customer health scores from hundreds of signals. Salesforce the same. Usage signals and people signals pulled from every touch point imaginable.

With these robust and surely wicked complicated health scoring models, these companies can predict churn with pretty amazing accuracy.

At the risk of being one of those guys who looks at a neighbor’s new car and says “must be nice,” it must be nice to have armies of customer success managers who can build models like that and use them.

For most of us, bootstrapping or taking only enough investment to get momentum, complicated customer health models that merge quant and qual data are out of reach. Unrealistic.

Customers surprise us when they leave. But that doesn’t have to be the case even if we don’t know what they’re really thinking and if we don’t have a 137-point health matrix.

Measure how often a customer uses your app, how deep they go with your features, and how many of their teammates are in there too. Add in a few more quantitative data points and I think you can get pretty damn close to knowing how to keep more customers longer.

If you have to choose between qualitative churn signals and quantitative customer health signals, I’d take the quant any day.

Peter

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