The world’s most innovative companies didn’t get where they are by making assumptions about what products or features to build. They used data to guide their decision-making process and to grasp what their users truly wanted and needed—before they ever started building. Leveraging data to understand users and their experiences, make strategic product decisions, and drive innovation, is a cornerstone of becoming product led. Without it, companies are forced to rely on gut instinct—a strategy that doesn’t scale and simply isn’t good enough when a single misstep could result in financial ruin.
Throughout this blog series, we’ve explored the positive impact becoming product led can have on customer health, company growth, and user productivity. In this final installment, let’s take a look at how product-led strategies help businesses of all sizes—and all stages of maturity—make data-informed decisions to innovate and iterate, faster.
Why is data so important for effective and efficient product development?
To build products and features capable of delivering meaningful value to users (and profitable outcomes to the business), product development teams need a clear understanding of who their users are and what they care about. They need visibility into how users engage with and move through the product. And they need to be able to spot where users are getting stuck in—or getting the most value from—their experience. Armed with that data, product managers (PMs) and developers can determine what needs to change in future releases.
Product analytics is critical for helping teams across the business uncover and act on these kinds of insights in a scalable, objective way. It helps the company understand exactly how users are engaging with the product, uncover opportunities for new or improved features, and identify high-value initiatives for the product roadmap.
Without keeping a firm grasp on user behaviors and expectations, product and development teams must make important (and oftentimes, expensive) decisions based on anecdotal evidence from a handful of users that often doesn’t represent the experience of the entire user base. This lack of objective product insight also forces these teams to make assumptions about what their current and prospective users care about. And this in turn leads to wasted time and resources as developers are directed to build products and features that users may not actually want or need.
It’s also critical to take user feedback into consideration in any product development efforts. This qualitative data helps product and development teams understand what customers think about the product so they can improve it in the future. Feedback also helps product teams prioritize their efforts by giving them direct visibility into users’ wants and needs, at scale. And by inviting user feedback into their development processes, product teams can effectively source new ideas, while helping users feel heard and valued—which ultimately improves user sentiment, loyalty, and retention.
What tactics do product-led companies use to innovate faster?
Product-led companies put product analytics at the center of their product development and customer engagement efforts. This data gives them insight into things like product and feature usage trends (i.e which features users are engaging with or getting the most or least value from), funnels (i.e. where users are dropping off at each step across features and pages in the product), and paths (i.e. the journeys users take leading up to or following a specific interaction). With product analytics, development teams can easily observe challenges or opportunities across their product portfolio, measure the impact and outcomes of new features being built and released, and continue to iterate with minimal latency.
In addition to quantitative product data, the best product-led teams also collect in-app feedback from users—through polls, surveys, and feature requests—to add context to the behavioral trends they’re seeing. Collecting feedback while users are immersed in the product improves the likelihood that they will actually share their thoughts (vs. doing so when solicited through external channels), and significantly improves the quality and relevancy of the feedback. On average, product-led teams see a 30% reduction in the amount of time it takes them to collect product and customer feedback.
Analytics also helps teams decide where not to focus their efforts. By understanding how users engage (or don’t engage) with underutilized areas of the app, product teams can determine whether it’s worth their time and effort to continue supporting that feature, or whether they should sunset or retire it to make way and free up resources for something new. Feedback from internal stakeholders and customers is also useful in helping PMs make these decisions by allowing them to ask users what they think about the possibility of the feature going away and giving them an idea of the potential ramifications of deprecating that part of the product.
Finally, this intersection of quantitative and qualitative data is crucial for informing the product roadmap. By bringing all of this qualitative and quantitative data together under one roof, PMs are better able to prioritize and plan initiatives and align cross-functional teams around shared go-to-market plans. On average, product-led organizations spend 30% less time on roadmapping activities, freeing up more time for active development work. And because they have processes and tools in place to quickly measure the outcomes of their efforts, they’re able to measure the efficacy of shipped features 30% faster on average.
Learn more
Download the full report, The business value of being product led, to learn how businesses like yours are changing the way they work—and the experiences they deliver—through product-led approaches.
