Two easy mistakes to avoid when using customer data to iterate.
Mistake #1: Product team doesn’t solicit feedback or delegates the responsibility to sales/customer success.
This mistake comes in two flavors, teams that use their “gut” to make product decisions and teams that get all of their customer feedback from other teams (sales, marketing or customer success).
Don’t outsource this work. You will not get the same results.
The product team — a product manager or leader — must gather customer feedback on behalf of the product team.
Trusting your “gut” often means building the coolest thing you can come up with. Outsourcing customer feedback to another team results in building that team’s pet project — the latest thing that they believe will help meet their goals. You’ll often find that those goals are not perfectly aligned with customer’s goals.
Some good news: Your customers want your product to get better. Why not ask them what would make it better?
These people are paying you! They have a vested interest in helping. Amazing things happen when people ask their customers what can be done to make things better. I’ve seen long time customers actually ask to be charged more money for a feature they want. “Build x, please! Charge us more money if you have to.”
Mistake #2: Drowning in data.
A few years back I got pulled into a newly formed team that was in charge of revamping our up-sell page (where customer elect into features which cost more money). I told my peers that we were lucky because: “We’re close to the money. We have a chance to move the needle”.
Our pain started quickly. The trouble discovering what needed to be changed about the application was not a lack of data. We had a data glut.
Because of compliance requirements, every single action that customers performed in this part of the application was logged. The trouble was literally no one at the company queried this data because while we were required to keep logs for compliance, we never actually had to use the data.
So here we are, a rag tag group of software engineers. No dedicated data scientist to deep dive for us. The data we have is complex and painfully slow to query. The volume alone was intimidating.
You know how we overcame the data glut? We ignored most of it. In the sea of data we found two key actionable metrics and used those as our guiding light. Could a data science team have taken the information that we had and delivered incredible insight? Probably. But we managed to move the needle by identifying actionable metrics.
Don’t be intimidated by volume. Find actionable metrics and leverage those for as long as they continue to be useful.
Looking for something that goes in-depth? Check out training.askinline.com where we publish new product iteration and customer insight resources every week.
