Let’s start with a story!

At Automattic, we’re lucky enough to have some pretty sophisticated internal tracking and analysis tools. I was recently involved in a conversation with my friend and colleague Martin, about a particular slice of our customer base, whose churn is higher than we would have expected.

One of the ingredients for this particular group of customers was that they had, at some point in the seven days before leaving our services, interacted with our Happiness Engineers via our live chat support offering. Given the tools at our disposal, we were able to pull together a list of all of these customers – and with the churn rate being what it was, and the total userbase for that product what it was, the list was not terrifically long. Double digits.

Some of you out there know this story, right? What better way to find out what is going on with your customers (or former customers) than asking them outright? Put together some post-churn interviews, offer an Amazon gift card, learn something new and helpful about your product or service. This is a pretty standard flow for researchers – start with Big Data to identify a focus spot, then focus in with more quantitative methods, interviews, surveys, what I think of as Small Data.

In this case, rather than jump to the usual move, and at Martin’s suggestion, I pulled up all of the chat transcripts, and read through them, categorizing them along obvious lines, pulling out noteworthy quotes and common understandings (and misunderstandings!) – treating these last live chats with churned customers like they were transcribed interviews, because in a real way, that’s what they are.

I was really surprised how insightful and interesting these live chat sessions were, especially when read back-to-back-to-back like that. In fact, I did not even feel the need to follow up with any of the customers, the picture was clear enough from what they’d already communicated with us. I was honestly floored by this, and left wondering: how much good stuff is already in these transcripts? 

Moving forward, I’m including customer email and live chat review as an integral part of any user cohort research that I do – it will allow me to come to the interviews three steps ahead, with far better questions in mind, and a much sharper understanding of what their experience might have been like.

Especially with robust data slicing tools, being able to cut down through verticals, cohorts and purchase levels means that I’ll be able to see a ton of useful, relevant conversations with customers similar to those I’m looking to learn more about.

This is also the case with you and your customers.

Even if you don’t have a user research team, or even one researcher, your support team is interviewing your customers every day. Even without data slicing tools, you can do something as simple as a full-text search on your last month of email interactions and get something close to what you’re looking to learn.

If you enjoy a support tool that has a taxonomy system or plugs into your existing verticals and cohorts, all the better.

This Small Data on your customers, these conversations, already exist. You don’t need to generate new information, you don’t need to sign up for third party user testing.

You’ve heard me say it before, folks – there’s value in the data you have. Use it!

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