The Characteristics of Data-Driven Product Management and Development

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Click to learn more about author Victor DeMarines.

Gartner predicts that by 2021, some 75 percent of independent software vendors will embed software usage analytics in their products to inform product management decisions and measure customer health.

When viewed through the lens of our product management recent survey “Listening to the Voice of the Customer,” that estimate may even seem conservative.

We polled 319 product managers and those in product management-related roles for insight on how they’re using customer data. Those surveyed, consistent with other industry studies, ranked customer phone and in-person interviews as the most effective means of collecting customer data. But coming in a close second – in front of feedback from sales, support calls, basic telemetry from the product and in last place, email surveys – was advanced product usage analytics.

What’s more, those surveyed widely agreed on the merits of using that data to guide development. Some 97 percent of the leaders we surveyed said customer data was useful, very useful, or highly useful in developing product roadmaps and prioritizing features, with a large majority indicating its value in UX/UI design and beta testing.

But then there’s this: 58 percent said they use customer data less than half of the time to make product roadmap decisions.

Data, to paraphrase economist Steven Levitt, is a powerful mechanism for storytelling, and digging into the data in our survey, we saw a powerful narrative emerge that sheds light on why there’s all this agreement on the importance of using data that doesn’t always map to its actual use.

A full 43 percent of those surveyed had implemented a packaged usage analytics software product. That group said that about 2/3 of the time, they use data to drive product roadmap and development decisions – a truly remarkable number when considering all of the various change management roadblocks that stand in the way of making data-led decisions.

But then there was a second group – the 29 percent of respondents who built their own solution to collect and analyze usage data. They said they used the data they collected to make product roadmap and development decisions only about 1/3 of the time.

That latter group exposes the difference between custom development and a packaged solution – the ability to easily access, analyse, and visualize the data collected to help make decisions.

Businesses with lots of engineering resources will often build the customer data collection tools in-house, typically as part of their check for updates system, where data gets appended to a log or database. They start collecting a lot of data, but they have no good way to analyze it. Technical resources are often required to write SQL queries – taking them away from their core responsibilities. As a result, the data, and all that potential for rich insight, gets shelved.

For those of us who have tried to evangelize implementing a formal usage analytics tool with engineering and development, access is the key to ROI. If product management can’t access the data in an easily consumable way, or make sense of the data, or, most importantly, trust the data, how can we possibly expect the data to have value across the organization – to help inform product decisions within the context of their many stakeholders?

When we begin to see the value of augmenting customer feedback strategies with technology, while at the same time acknowledging the challenges of trying to custom-develop these sorts of tools, we take a huge step toward data-driven product development that cascades across our organizations – to sales, to marketing, even to the c-suite. Because easy access to data for product development provides a springboard for lots of value-adding things: targeted, relevant marketing campaigns, developing rich educational materials for sales opportunities, even helping us see patterns of use that inform relevant, and profitable, licensing strategies.

When asked what they would like customer data to tell them, respondents to our survey had many wishes, spanning insight into the success of a release, to the simple ask of knowing whether a customer was telling the truth. One respondent, though, had this to share: “I would want to know each customer more individually so that I can treat them that way as much as possible.”

That statement is rich with meaning. We know it’s not possible to develop applications for each individual user, but it is possible to individualize each application by developing features and workflows that are informed by actual use and therefore uniquely suited to the needs of user personas. Access to data allows us a view into the individual at scale, so to speak, and is absolutely crucial to helping us build applications that are irresistible to our users.

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