Product Analytics Puts the Roadmap Back In Product Teams’ Hands
Product teams should not feel left behind when it comes to analytics. Funnel analytics have been a marketer’s best friend for years now, while one division over, product managers have clamored to make sense of the terabytes of data companies have on product and feature usage. Not only are product teams starting to see how product analytics tell the real story of the current feature set and its usage, but analytics also light the way for a better user experience (UX) and, ultimately, a more successful product roadmap.
With product analytics connected to a cloud data warehouse, product teams have significantly greater visibility into how users of websites, mobile apps and other software interact with the product. The questions product managers can ask are innumerable, ranging from which users access which features and for how long, to how usage differs depending on how familiar the user is with the product. But the best questions stem from well-thought-out hypotheses about what might contribute to greater engagement or, perhaps more importantly, what might be holding users back.
Understanding the current customer journey is critical to forming better questions and improving the roadmap. Take mobile app usage, for example. It’s common to see free and paid versions of an app, but what exactly drives users to convert into paying customers? The answer lies in the product analytics, looking at what features were most-used prior to upgrading, the length of time users spent with the app, usage frequency and more. Relatively simple tests of what features are offered in the basic plan or how the upgrade path is positioned in the app can quickly lead to new insights and better results.
A product team may choose to look even further into the data to learn more about those who are making the desired choices. How did their journeys differ? Are there distinct segments within a high-value tier? How does their feature usage compare with that of others? This kind of information can help optimize the UX for all other users, current and future. In this way, user data and product analytics begin to drive the product roadmap.
Users tell companies what they want (and what they don’t) through their very actions. Intuition can lead to thoughtful questions and hypotheses, which can be tested through product analytics tools and ultimately drive the roadmap.
Generating Internal Support
As product managers seek to make a case for better analytics, they may run into objections from CIOs and CFOs who don’t acknowledge the need for yet another BI tool. Decision-makers need to recognize that existing BI tools, which offer a look at a few key historic metrics, don’t enable product teams to ask and answer hundreds of questions about customer behaviors and feature usage any time they want. Companies can’t afford to waste time writing dozens of SQL queries every time a product manager has a new hypothesis to evaluate. With a product analytics platform tied directly into the data warehouse, product managers can be far more independent and effective.
Experts recognize this, too. Research from Gallup notes that companies using behavioral economics—essentially the analysis of user data—as part of their decision-making do better than their competitors by 85% in sales growth and, notably, by 25% in gross margin. Gallup suggests there may be more opportunity in behavioral economic approaches than in lean management and Six Sigma.
Gains like those are the kinds of outcomes C-suite executives will pay attention to. McKinsey analyst Holger Hürtgen believes CFOs may be among product teams’ best allies in the quest for better, on-demand analytics. “Project teams and senior leaders may suspect that their companies could streamline processes or export products more efficiently, for example, but the CFO can put these ideas in the proper context,” Hürtgen writes. “Of course, CFOs cannot lead digital transformations all alone; they should serve as global conveners and collaborators, encouraging everyone, including leaders in IT, sales, and marketing, to own the process.”
To supercharge your roadmap, start by pulling key insights from the product analytics platform and bringing them to your development team. Prioritize the feature improvements or additions that, based on your data and testing evaluation, are most likely to create a better UX, drive adoption and increase revenue. Two overarching goals for this process are to address areas of friction for existing users and add features that support both new and existing customers’ journeys.
Going deeper, look for customer segments that stand out. This could include segments with particularly high usage of certain features, segments whose usage of the platform has noticeably dropped or some other behavior that sets them apart. What other traits do these segments share? How long did they use the product before exhibiting these behaviors? What other features did they use or are they using now? What you can learn from high-performing segments can inform the future of your UX and roadmap, but it can also inform your marketing efforts. In short, find more prospects who share these customers’ traits.
On the other hand, the behaviors that lapsed users exhibit before dropping off can shine a light on areas of significant friction. While certain features or processes did not create an obstacle for all users, if there’s a large enough cohort of stalled users, it may well justify a hypothesis and series of tests aimed at improving the experience. The better your UX is, the less often you’ll see users come onboard (overcoming the dreaded adoption hurdle) only for their usage to stall. If usage is falling relatively quickly after adoption, those users may benefit from early outreach with on-demand training, feature walkthroughs or other opportunities to experience quick success using the product.
Once analysis begins to inform your UX and product roadmap, you’ll find that the work becomes an ongoing experience. There are always new questions to ask and different segment behaviors to explore. Form your hypotheses, and use A/B testing to measure user response to different scenarios. Continuous improvement tied to strategic objectives should be your goal, whether the focus is on user adoption, user retention, use frequency or something else. With a cloud data warehouse and product analytics at your fingertips, questions about your users’ behaviors need no longer keep you up at night.
About the author: Jeremy Levy is CEO and co-founder of Indicative, the only product analytics platform for product managers, marketers and data analysts that connects directly to the data warehouse. He is a serial entrepreneur and a veteran of New York City’s Silicon Alley. Jeremy co-founded Xtify, the first Mobile CRM for the Enterprise, acquired by IBM in 2013. He also co-founded MeetMoi, a pioneering location-based dating service for mobile sold to Match.com in 2014.