Tag: UX

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!





Customer Support is the Last Mile for SaaS Companies

Working as a Team Lead for one of the Happiness teams at Automattic has been a great opportunity for me to learn a lot about the Software as a Service ecosystem.

I’ve been thinking and talking about hospitality and its outsized value for software companies for a while now (here’s a talk I gave in 2014 on the topic) – there are a lot of ways that support is undervalued in a general way by software companies, but folks working in the SaaS sector especially are losing out on a ton of potential value by underutilizing their support staff.

There are lots of places where we as an industry could improve here, from recognizing the import of support in the classic Build – Measure – Learn cycle to admitting that UX research is essentially Hospitality 2.0.

I’ve made it pretty clear (I hope) that my position on software, and even really maybe all products everywhere, should Just Work. Having to contact support staff, or dig through documentation, or try to figure out which Stack Overflow commenter is the closest one to correct, isn’t something an end user should have to do. That’s really it. Full stop.

However, like you, I live in the real world, and I recognize that compromises have to be made – products have to do more than one thing, and deadlines and inefficiencies and sometimes simply economic necessity means that not everything we touch can be a perfectly tailored, intuitive non-interface.

Someday. Someday.

WordPress.com is a SaaS business. Our customers are largely non-technical, and our product is fairly complex, although powerful. There is certainly a learning curve, and while we provide some educational materials, a great many of our customers, especially new customers, lean on our support system to help them gain momentum in the right direction.

We’re not alone in this – many SaaS businesses, especially ones that offer many features and powerful suites of tools, share that learning curve. You can very likely think of two or three services that you use yourself that took some time to really figure out – imagine if someone less tech savvy than you were trying to figure out that product? Where would they head?

Note here that I’m talking specifically about SaaS companies who are by and large dealing with the public – B2B SaaS companies have their own tangled web of complicated issues that I am by and large unqualified to comment on.

For companies like WordPress.com, businesses that sell to the general public and have a not-insignificant learning curve, your support staff represents the last mile service for your company’s created value.

This idea of Last Mile service comes from (ugh) telecoms – Wikipedia Link , more context appropriate Investopedia explanation – the TLDR is that the last connection in the telecom chain tends to be disproportionately challenging and/or expensive, but it remains the crucial link between the end customer and the massive network of energy or information or water or whatever.

Imagine you were running a massive telecommunications company, and you had a geographically enormous physical network in place, fiber stretched coast to coast, fully prepared to bring high speed internet to the people. This is a massive, massive amount of value. Imagine that you are, for one reason or another, unable to connect that last mile, to make that switch between your vault of value and the customer who would absolutely love to buy it from you. That’s a last mile problem.

For many would-be customers of SaaS products, that final connection, that link between an enthusiastic customer and your stored value, is your support staff. When they are able to work effectively, a good support team can multiply the value of the product, because not only are they solving individual customer problems, they’re flipping the switch for that customer, creating that last mile connection that otherwise would never have existed, leaving a customer disconnected from the value that you can offer them.

Complicated, powerful products can bring value to customers in a way that punches way, way above their weight – folks who have never heard of HTML are building multi page responsive websites right now on WordPress.com. Think about that.

The issue is, if you’re selling to the public, some percent of them need a hand flipping that last mile switch – if you can’t or won’t provide that service for them, you’ll be missing out on a whole cohort of potential enthusiastic customers, because the fact is, so, so many companies today do not bother to invest in their support staff to the extent that maximizes the last mile service.

The insidious thing about this problem is that it can manifest itself in many different forms. It might be especially high first-day churn rates. It might be that a cohort of your customers massively underuse your product’s features (because they don’t really understand them, because the last mile isn’t connected), and as such they’re dissatisfied, and go dark. It might be that folks who DO contact support, but only once, tend to churn at a higher rate (that would indicate that your support staff may need to read closer, empathize rather than grind out emails as fast as possible.)

Only you can identify if your product’s learning curve is leaving people out in the cold, denying them access to the full value of your product.

If you think that’s a potential place for improvement (and it almost certainly is), you should take a long look at the way your customers are able to access support. Is it easy to find? Are operators thoughtful and thorough, rather than perfunctory and severe? Imagine you were deeply confused by a step in your signup and activation flow – can you get help right away?

Considering the metaphor of the last mile can be really helpful in improving your customers’ access to your company’s value – think about it, and get out there and flip some switches!

October Reading Goals Recap

I almost made it – I finished Microinteractions, Elements of UX and Lean UX. I am only about halfway through Gamestorming. I do have an excuse – I picked up and spent some time in the excellent Just Enough Research, part of the Book Apart family. So, I’ll call it a draw.

Here are my thoughts in the order I read the books;

Microinteractions: I was concerned that my lack of professional experience with UX topics would make this one a bit out of my reach, but to the contrary I found it really interesting, and it has certainly changed the way I think about the tiny pieces of software and websites, and the way these pieces change my experience. I would recommend it to anyone who works with websites or software, regardless of your area of focus.

Elements of UX: This book, while thoughtful and certainly full of really important and structural high level thinking, was not for me. I lack the necessary grounding and experience to get the full value. It was the same experience as reading the third of fourth book in a series independent from the others – I could tell I was not getting the full story, the full impact. So, I would certainly recommend it, but probably not good if you’re just dipping a toe into design and UX.

Lean UX: Probably my favorite of the books I finished in this list, Lean UX isn’t really about UX per se, but more about approaching that sort of Work from a different angle. As a step forward in management and product development, I liked it an awful lot. This may be because it ties into the sort of thing think about already, have some work experience with already, so the lessons and thoughts are especially tangible and pertinent.

Gamestorming: Despite only getting halfway, have already started using the games and thinking in this book – my team at Automattic will be putting together our annual roadmap in January, and we’ll be using some of the creativity building games to help approach the next year with open minds. Game storming is mostly a collection of brainstorm games, with a short explanation of how to use them – if you work with other humans to make things in any capacity, you would get a a lot out of this book.

While I failed to meet my book goal in October, I did meet my page number goal, so I feel inspired. I am going to only choose three books for November, including the rest of Just Enough Research. I have reached out to my colleagues Jeremey and Ian for recommendations – stay tuned!

Don’t Confuse Your Success for Customer Success

Data is awesome. Scientists have known this for a while now, but now we have Big Data, which some are going so far as to call a “Natural Resource” – watching a site like Growth Hackers only confirms that we are more interested in our data, and what it can tell us, than ever before.

This is a cautionary post. I love Google Analytics. I take great pride in being a part of a data-informed company, and I think solid data analysis and the drawing of insights from that analysis has a place in any modern business.

That part we can all agree on. That part is easy.


What I want to distinguish here is the difference between your success as a company, and the success of your customer. It is harder to focus on customer success when your data provides actionable insight that could trade their success for yours. I don’t mean to preach to you which one you should prefer: I’m a pragmatist, I can appreciate that sometimes to keep the doors open you have to make compromises. I’d encourage you to be honest with yourself, and simply recognize when you’re acting for your customer, and when you’re acting for yourself.

Maybe some examples would help illustrate what I mean.

  • Pop-up ads were gone for a while – remember? But now they’re back. Visually disruptive ad campaigns are the easiest example in this category. They may lead to more clicks, to additional ad revenue, but they are clearly not leading your customers to success. They are on your site to engage with your content and your products – obscuring those things with an external (or internal!) ad is putting your success ahead of theirs, plainly.
  • Opt-out or cancellation buttons and screens that include passive aggressive or semi-threatening language are becoming popular – “I don’t want to maximize my income.” “Leaving now may leave you at risk!” – these are, again, plainly putting a win for the company ahead of a win for the customer. You may minimize loss, but you’re not only putting aside hospitality, you’re being a bit of a bully. url
  • A/B Testing is a huge part of growth engineering and data collection. A button placed differently, a header image removed or altered, testing adjustments to see what converts, what leads to more traffic. Try to construct your A/B tests with customer success in mind. Their success is not usually tied as closely to conversions and page views – I can’t tell you what their success looks like, but they sure can!
  • When defining your Goals in a tool like Google Analytics, the same sort of thinking applies: yes, knowing the path your customers take to the final purchase confirmation page is important, but it is also worth considering the (much larger) group that does not convert. Identifying where they drop off, and using a tool like Qualaroo to find out why they leave, would help focus on their success.

Keep collecting data. Keep drawing actionable insights from it, but remember: the data doesn’t tell the whole story. Additional conversions, decreasing customer churn, these may look great on a quarterly spreadsheet, but you need to dig deeper to see if they are really giving your customers the best experience they can have.