Month: July 2016

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.

Risk and Support in Leadership

Not long ago I had the pleasure of hosting an old friend in Saratoga (where I live).

Rob and I became colleagues first, by working together in high end coffee in New England, and then eventually friends.

Rob had worked in coffee longer than I had when I joined that industry, and is still a big part of the community in Providence. He was in my neck of the woods visiting clients of his – he’s a coffee trader these days, and sells green unroasted coffee to folks who turn that coffee brown and sell it to the general public.

Over wine and Hatties’ fried chicken, we talked. We talked a lot! We talked about family and career and what it means to live a good life. It was an excellent visit with a great friend.

One of the things that he introduced me to was the idea of thinking about leadership in terms of risk and support. You can imagine these two ideas as different dimensions on a field, like so:

Screen Shot 2016-07-12 at 7.53.10 PM.png

In a leadership position, the decisions you make will tend to fall into one quadrant most of the time – the way that we can think about these dimensions are in terms of how we work with our team.

Support here means, how well do you as a leader back up the members of your team?

When someone falls down, when something doesn’t work as planned, do you step in, do you take responsibility for the team? Or do you allow the individuals to face scrutiny and take the blame themselves?

If a member of your team tells you that they have a bold career plan, as their lead do you find ways to help move them along that journey, finding or manufacturing opportunities for them? Or do you nod, ask about their day, and let them try to find their own way with neither help nor hindrance from you?

These are both different ways that we can compare high support and low support.

Risk here means, how much risk do you allow or encourage your team to take on? Do you fully insulate them from the winds of your organization’s politics, content with their low amplitude day to day work? Or do you allow them to wander outside your team’s safest places and experience both the opportunity for great work and the chance of failure?

Risk and Support are not always absolutely good or absolutely bad – you can imagine a lead who exposes their team to great risk could create a terrible environment to work in. You can also easily imagine a leader who fully supports her team in all they do, but never offers up any Risk, which means the support isn’t ever really needed.

This is why truly great teams balance the two, and achieve a state of both High Support and High Risk – offering opportunity (and the accordant risk) when appropriate, and doing all they can to also provide support for the decisions made in pursuit of that opportunity.

As far as a guideline for leadership and leadership decisions go – I like this one a lot. I’ve been asking myself, “Am I allowing for some risk? Am I supporting bold choices?” 

This is pretty half baked on my end – there’s a lot here to consider (how much risk is appropriate? Can one over-support? What does high-risk low-support look like? What about low-risk high-support?

Have you heard of this kind of structure before? How does this gel with your own experiences, as a team lead or as a team member?

 

 

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!