Tag: data

It’s Good that Data is Man Made

There’s a post from the folks at Highrise that’s been going around Customer Support and Success circles over the last couple of weeks: Data is Man Made, from Chris Gallo.

As someone who writes and speaks about customer support and leveraging data to do customer support better, I’ve had this article dropped to me in at least two Slack channels. Folks get a sense of mirth, I suspect, from needling me with articles and arguments that run contrary to the sorts of things I write about, and try to be persuasive around.

Yes; I will admit that I found this piece hard to swallow at first blush. Opening with…

Here’s a secret from the support team at Highrise. Customer support metrics make us feel icky.

… is a guaranteed burr in my side. Arguing against measurement from emotional premises?

Continue reading “It’s Good that Data is Man Made”

You’re Already Interviewing Your Customers

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!





Full SupConf Video for Use the Data You Have

Hey folks! I’m really happy to share with you the full video of my recent talk at SupConf 2016, where I gave a talk on leveraging your existing data to build value from your support organization – here it is!

I also created a supplementary Page with a three-parter on how to execute the ideas I present in the talk – you can find that at https://s12k.com/supconf/ .

SupConf East is coming soon – as a speaker and an attendee, I cannot recommend it highly enough! You can get updates on the next SupConf event by signing up for the mailing list here.

Pies and Waffles: Delicious Charts

I’m trying to catch up on my massive Pocket back scroll, and in surveying the massive and diverse landscape of its contents, noticed a few pieces all from the same site,  eagereyes, and all on the same topic, pie charts.

So, naturally, I read them. 

(As a sidebar, am I the only person who struggles with this with Pocket, or other content saving services? Am I coining the term “Pocket Zero” right now? Am I the next Merlin Mann? )

Here are the pieces – they’re all quite short, less than ten minutes reading, even if you do take in the discussion with Hadley Wickham in the comments section:

A Pair of Pie Chart Papers
Ye Olde Pie Chart Debate
Pie Charts
One thing I was surprised to learn was just how long the Great Pie Chart Debate has been going on – over a hundred years! And yet,  the pie chart lives on. 

It’s also interesting to me that,  despite their ubiquity in popular media, we don’t have a great sense of how or why we perceive pie charts the way we do – it makes me consider firing up the Doc’s eye tracker, just to see how eye patterns map onto different visualizations.

In this series of posts I was also introduced to the Waffle package for R, which makes it easy to put together a pie chart alternative which I quite like – like this:

It strikes me as easier than a pie chart to compare each of the pieces to one another, and indicates that each point is part of a continuous whole in the same sort of way that a pie chart does. 

I’m excited to play around with this package some in the coming days. I’ll have to dig a bit and see if it’s supported in Shiny yet!

SupConf Talk Rehearsal Recording

If you weren’t able to make the first ever SupConf in San Francisco this week (and today’s the second day!) , here is a previously recorded rehearsal for the talk – not quite the same as being here, but I hope valuable! I am not 100% certain if there will be a recording of the live talk available, but if it is, I’ll share that once it’s in my hands as well.