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Data for subscriptions podcast - Episode #29

Usage Insights to Drive Product Development

Guest

Tobias Gunnesson

Tobias Gunnesson
Chief Product Officer, Avinode Group

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Episode description

Usage Insights to Drive Product Development

In this episode of the Data for Subscriptions podcast, we look into the significance of using usage insights to comprehend the authentic value drivers, as well as methods for monitoring usage and leveraging usage insights for achieving product-market fit and developing go-to-market strategies.

Highlights

What role does data play when it comes to you and your team making decisions for product investments, product roadmaps, and product development.

Very, very important, especially if you don’t want to run blind. I’d rather have blurry vision than be blind, but it would be even better if I had perfect vision, which you rarely (have) in product. Within Avinode, the roadmap should tell us where we’re going. And so looking at the data and how that plays into the roadmap, it’s really about three things: The first thing is on the leadership level, like how do we decide what problems are worth solving? And this is really like about where we are putting our chips on, where are we investing our money, and how do we make good bets. So classical product, it’s both about focusing on the business opportunity, like how big is this? How valuable is it? But it is also looking a lot about the usage data in our product to say how valuable would this be? How many of our customers do we think this would fit, but also to identify what are the pains that people are having, both from where we see gaps in the adoption funnels, gaps in the user journeys, where people are dropping off, or customer feedback, or the value metrics in our products, like this is what our product should do, it doesn’t seem to be doing it. How can we move the needle on that. The second step is really setting direction, so like giving an objective to a team. How do we guide them with the goal of what they’re trying to achieve and agreeing on what are the key results, like what would the success look like and how would we measure that to give an idea of like, OK, this is what we’re trying to achieve. Which leads to the third thing which is really tracking success and being to celebrate and have some fun together, but like, yes, we’re moving the needle. Good things are happening. So, validating our ideas and then tracking the success of them to celebrating like you cannot do that without data.

If you could give us an example, from seeing the data, learning from it, and deciding as to what you should solve for.

One fairly recent example is deciding what problems to solve for. So we started to hear two things. One was that here was a new business model that was appearing. But the other thing we also started to see was that the accuracy of the marketplace was decreasing. So, the matchmaking act, like how good we were of actually guessing was decreasing. And so we then looked into the data and said, well, why was that? And we identified that it was actually related, this business model was growing and people that had that business model, they couldn’t really set up how they should appear in the marketplace correctly, and this was having an impact. So that was the data there, which allowed us to identify a problem. It allowed us to match it to a trend that we were seeing in customer feedback that we were having and really setting like this is both a goal, but the goal isn’t just to like support this business model, which can be very vague. The goal was actually to support this business model, make it the standard for all customers that had it, and move the metric on the marketplace accuracy.

What are the key metrics that you derive from your subscription data?

We’re really looking at the leads, the acquisition, activation, and adoption (rates). (There’s) retention and time-to-activation, but we also tend to look at conversion, and for me, I very often look at conversion from activation to adoption, because that’s really where the product influences a lot (of the) company. Then on the product side, we are the drop-off in the funnel, and we need to look at how we are providing more value (with) the features or how we are providing more usability in a feature.