Regular touch points with customers are a pillar of continuous discovery. If you’re not regularly talking directly with your customers, you increase your risk of building a product that no one wants or needs.
Regular touch points with customers are a pillar of continuous discovery. If you’re not regularly talking directly with your customers, you increase your risk of building a product that no one wants or needs. – Tweet This
However, even when product trios commit to weekly interviews with customers, their companies may have other avenues for collecting customer feedback and insights. Their customer success and sales teams hear directly from customers all day. The support team has a constant flow of tickets that paint a picture of what’s not working well in the product. And the company might even have analytics tools or surveys in place to monitor customer behavior and collect feedback directly from customers.
Your coworkers from other teams may be excited to pass along what they’re hearing from customers—whether it’s in the form of complaints, feature requests, or even praise. These insights don’t exactly count as customer interviews, though, so many product teams wonder how to process and act on this information. Today’s Ask Teresa tackles what to do about the customer insights you receive outside of customer interviews.
Question: What should we do about other forms of insights we receive from customers such as requests via support, sales, or other surveys?
Product trios should definitely monitor these other sources. We can learn a lot from support tickets, sales conversations, behavioral analytics, and many other inputs.
The challenge, however, with these inputs is we tend to get fragments. A customer files a support ticket asking for a feature request, but we don’t know the whole story. Why do they need that feature? What will it help them accomplish? When will they need it? Without this broader context, it’s hard to build the right version of that feature.
We can learn a lot from support tickets, sales conversations, behavioral analytics, and many other inputs. The challenge, however, with these inputs is we tend to get fragments. – Tweet This
We also don’t know who else needs that feature. We might have several customers requesting what sounds like the same feature, but without a lot of context, we don’t really know why they need it or how they might use it. If we build our best guess, odds are we’ll learn that these customers all had different needs, even though they were requesting the same feature.
Even worse, we often see customers requesting many different features, even though they share the same need. This results in us building way too much. This happens because customers don’t always know the best solution for their own needs. And so each feature request represents their best guess, but none are the ideal solutions. In this scenario, we often build several features that don’t work for anyone when we could have built one solution that worked for everyone.
When feature requests represent best guesses, we often end up building several features that don’t work for anyone when we could have built one solution that worked for everyone. – Tweet This
Don’t Expect Your Sales Team to Know How to Collect Stories
Some (but not all) sales folks are good at getting context. When a prospect asks for a specific feature, some will be diligent enough to dive into the why behind it. They might ask, “What would that feature do for you?” This context helps. But this question invites the customer to speculate about their future behavior. And we already know that’s not a great way to get customer feedback. It’s rare (I’ve never seen it) to meet a salesperson who is trained in story-based interviewing who can collect the full context behind a feature request. And that makes sense. It’s not their job; it’s ours.
Behavioral Analytics Tell Us Something—But Not Everything
Behavioral analytics are an amazing window into our customers’ behavior. That window can tell us what our customers are doing, but it can’t tell us why they are doing that. Analytics are missing a lot of context. What is the customer trying to accomplish? Do they know enough about our product to accomplish that goal? Do their actions represent a success path or are they simply wandering trying to find the path?
Behavioral analytics are an amazing window into our customers’ behavior. That window can tell us what our customers are doing, but it can’t tell us why they are doing that. – Tweet This
Other Sources Can’t Replace Interviews, But They Can Help Guide Our Conversations with Customers
Given these challenges, these sources of information are not a replacement for interviewing. However, these inputs are great inspiration for what to explore in your upcoming interviews.
If customers are requesting a feature over and over again, interview them. Ask them what they are doing that is creating that need. Collect the full story. If your support tickets indicate there’s an unaddressed pain point, interview those customers. Find out what they are doing when they experience that pain point. When your analytics point to interesting behavior, talk to some of the customers who are exhibiting that behavior.
Interviewing is one of the most effective ways to get the full context. But it’s not the only one. You can also get the full context by observing your customers. The reason why I advocate for interviewing over observations is because it’s a more sustainable activity week over week. That doesn’t mean you shouldn’t do observations. Add them in where you can.
If you want to ensure that your opportunity space reflects reality, I’d recommend limiting the opportunities on your opportunity solution tree to the ones that you were able to explore firsthand in interviews or that you were able to observe firsthand yourself.
This question came from the Continuous Discovery Habits community, where we discuss all things related to putting the continuous discovery habits into practice. Come join us!