Create Value With the Support Data You Already Have

Editor’s note: The following post by guest author Simon Ouderkirk is based on his May 2016 talk at SupConf, a conference for support professionals.

Your support team can create value within your company using the data you already have at your fingertips.

No need to develop and run experiments or try wild new stuff — chances are, you already have all the tools and information you need to test your hypotheses and back up your findings. This way, you can advocate for customer support using the shared language (hint: data and money) that drives positive change within your business. Here’s how.

Ask the right questions

Leveraging your existing customer support data to unlock the value present in your support unit begins with asking the right questions.

If you haven’t used Google Analytics or Kissmetrics or Mixpanel before, these tools are powerful, but they can also be overwhelming. If you go into that jungle without specific questions, it’s easy to get lost, wander around, and never bring home the treasures that are out there and waiting for you.

I recommend starting by your support team’s existing assumptions about your customer base. Challenge yourself to identify the big, untested beliefs that power your support team. Every team is different, but at Automattic, some of our assumptions might look like this:

  • Our customers want plugins for their sites.
  • Our customers speak English first and every other language is a distant second.
  • Our customers prefer replies from the same person, even if it takes longer to get a response.

The next step is to look at that same set of assumptions and explicitly ask yourself, “Are these true?”

  • Is it true our customers want plugins for their sites?
  • Is it true our customers speak English first and every other language is a distant second?
  • Is it true our customers prefer replies from the same person, even if it takes longer to get them?

This step helps you get in the mindset of a great data-driven support practitioner.

Assume best intent

When someone makes an assertion about the way people use your product, your first inclination should be optimistic curiosity.

Optimistic curiosity means you assume best intent, but you’re curious about the grounding of the assertion — does it come from anecdotal information? Does it come from a personal motivation? Is there data to support it? Can we see the data? And so on.

Consider each of your beliefs, no matter how strong, and ask yourself: “What measurable behavior would our customers engage in if this belief were true?”

  • If it is true our customers want plugins for their sites, then we’d expect “plugins” would be a top search term in our knowledge base.
  • If it is true customers speak English first and every other language is a distant second, then we would expect traffic to our English language support docs would be far greater than other languages.
  • If it is true our customers prefer support responses from the same person, even if it means waiting longer for them, then we’d expect to see higher feedback scores for the products or teams who “own” tickets than the products or teams who do not.

Now we’ve moved from untested beliefs into questions, and we’ve developed our hypotheses around more helpful “if-then” statements.

Answer your questions

For your first steps as a data-driven support professional, it’s important you become a confident and competent practitioner of your particular toolset, such as Google Analytics or Mixpanel.

Once you get a feel for how your toolset of choice works, you can use it to test your hypotheses. For example, let’s open Google Analytics with the following hypothesis in mind:

  • If it is true our customers want plugins for their sites, then we’d expect “plugins” would be a top search term in our knowledge base.

Since our question is about customers being interested in plugins, one way to check our hypothesis is to see how traffic for our support documentation on plugins compares to other support documentation. Here’s how to find the answer in Google Analytics: in the left nav, click on Behavior -> Site Content -> All Pages.

Here, we see a list of our top ten most-visited pages, as well as a breakdown of Pageviews, Unique Pageviews, and so on.

Google analytics page views

While I’ve blurred out some proprietary data, what this shows is that taken together, “Plugins” and “ and” represent our second-most visited support document.

Google analytics page views

Further, the Navigation Summary tab tells us that when people visit one of those two pages, they often immediately visit the other one.

I’d take this data as sufficient evidence that our hypothesis — “plugins” is a top search term in our knowledge base — is supported. The confirmation helps us recognize this as a Real Problem. Now we can unpack it into useful steps, such as accepting that our customers use the word “plugins.” That knowledge helps us design an interface that does a better job meeting their real expectations, rather than what we suspect their expectations are.

Presenting and persuading

Once you’ve converted your biggest beliefs into hypotheses and confirmed or denied those hypotheses using your company’s existing data, you’ve arrived at the hard part: explaining this data to stakeholders at your company who can enable change.

So how do you use the answers you’ve found to persuade others within your organization to add value for you, your customers, and your organization’s bottom line?

Start by asking yourself, “What is most important to this decision maker today?” Then, use data to show how the issue you’re championing can have a direct impact on what matters to them. Are you in a high-growth startup where “Monthly Active Users” is your most important metric? Use data to show how support can help move that needle once they have the resources they need. Are you in a mature company, struggling with turbulent retention rates? Use data to show support’s impact on customer retention.

If you need to run a test or an experiment to verify that something needs to be solved or addressed, then you’re approaching it the wrong way.

Big problems, problems that deeply need solving, will manifest in some way.

Go into your archives. Dig into your analytics suite. Find that manifestation and use it to enact positive change.

Finally, remember to set your own ego aside in this process. People in your organization have their own have challenges and motivations that you may not be aware of, but sharing a mutual victory outranks being 100% true to your own perspective. Sometimes this means going back to the drawing board; you might need to do some more digging to find information that will speak to different parties. This is OK. At least in this situation, it’s better to do more research than not enough.

Every support team answers customers. Great support teams use data to discover trends, make the business case for fixing big problems, and improve the customer experience.

Simon Ouderkirk
Simon Ouderkirk

Simon is a support team lead and Happiness Engineer at He blogs at

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