Everyone wants to be data-driven in building a product and running a business. But exactly what that means and how to put it into practice isn’t an exact science these days. In this post, we’ll explain how and why you should use data to inform, execute, and measure product strategy––not just optimize around the margins. Even when big initiatives are already underway, putting quantitative data to work strategically in your product (and business decisions) is likely to be a crucial factor in the overall success of the business. We’ll also reveal how Fuzy helps you do this at a tactical level, empowering you to not just optimize metrics, but introduce new features with confidence and make game-changing bets that put you ahead of the curve.
Analytics aren’t just for optimization
Looking at a variety of teams and companies across sizes, growth stages, and sectors, we’ve observed that most tech orgs fall into two camps: those who think about analytics as a tool for optimization and those who strive to leverage data in wider decision-making and product strategy.
In the first mode of thinking, you’re trying to make what you already have better. Usually this involves a lot of counting, like landing page conversions. Then when it comes to making a big bet, innovation, or rolling out a new feature set or product, data often falls to the wayside and leaders begin reverting back to intuition and shooting from the hip. But doesn’t it make more sense to lean even farther into data-based decision-making when you’re launching something business-critical?
If we think about data only as a backwards picture of what’s already happened, one common misconception is that you can’t use data to accomplish something that’s new––something outside the daily product delivery cycle that keeps the machine running. However, making sense of the data you already have to inform your next move is an equally (if not more) powerful application of analytics.
From data to insights to product strategy
As a UX design and qualitative research specialist, I never take for granted that some level of synthesis has to occur between the collection of data (through interviews, for example) and the decisions that follow. But it’s easier to skip over this thinking with quantitative data because there’s often little abstraction between numbers being counted and what needs to be done. What’s required is a shift in mindset from counting (which informs output) to context (which informs outcomes). Creating context from data helps you see what’s going on around the thing you’re interested in––what might be related or affecting what you care about.
Here, I find another great parallel with design: we often think of the scientific method as zooming in as far as you possibly can to eliminate any noise. With UX research, you're trying to zoom out instead of just looking at one number in a vacuum.
Early in our careers, designers tend to focus on individual components or an individual screen. As we grow, we start thinking at the application level. Eventually we come to realize that design is everything––the sales motion, the go-to-market motion, the customer kickoff meeting, the documentation we provide for implementation.
As it translates to analytics, being laser focused on optimizing one metric may be rewarded as the right approach in some contexts, but there's a shadow side to that focus. You miss context clues from other metrics that give you a better informed picture of the reality of product performance and customer interaction.
In other words, context allows you to develop insights, or understand ‘the why.’ While some feel that ‘why’ doesn’t matter as long as numbers are moving in the right direction, knowing ‘why’ has a very important benefit: it allows you to develop strategy and build for the future, rather than just reacting. Most organizations want to grow from the insights they collect and scale that institutional knowledge, so as they continue hiring and expanding their product footprint, they don't have to relearn the same lessons over and over again.
How Fuzy helps set and execute product strategy
Growing businesses and fast-moving startups rarely have the human resources, product science expertise, or bandwidth necessary to gather, analyze, test, and interpret data quickly and accurately enough to inform product strategy. Fuzy gives teams product science superpowers by distilling data and serving up key insights that connect products and user behavior to business outcomes. These are just some of the tactical ways that Fuzy can help your team go from data to insights to strategy, and beyond.
Identifying targets: Applying outcome-first thinking, the first thing Fuzy does is understand what’s important to you. We help you define your targets (aka your behaviors or metrics of focus) in the application. It’s a great forcing function to have an internal conversation about what actually matters to the business and avoids the pitfall of overwhelming dashboards where every event is created equal. With Fuzy, you’ll rally focus around important metrics, milestones, and use cases. Are more users following your ideal “happy path” with each intervention you make? Were there unintended consequences from a recent release? Are we seeing lower outcomes with a specific segment? The process creates cross-functional clarity on the focus and how progress is trending.
Mapping into your product cycle to provide context and a historical timeline: Fuzy aligns the way our product works to your product development cycle. Sprints, agile, OKRs, and quarterly business reviews can all be informed by the insights served up in Fuzy.
Auto-generating annotations from your CRM and continuous integration software: We automatically record annotations for releases and CRM events so you can build appropriate context and better understand product performance. When you see a peak or a valley in your data, you can reference what was happening during that time frame—rather than applying the quickest, easiest explanation for why something went well, which could be biased. Over time, this builds a historical record in Fuzy about what's happening with your releases, customer records, growth, and stability.
Democratizing data across disciplines to enhance velocity and alignment: The mathematical rigor built into Fuzy gives teams all across your company on-demand access to, not only data, but the stories hidden within, boosting the quality and speed of decisions. Operations and analyst teams especially benefit, reducing repeat questions and analysis and getting back to more rewarding work.
Auto-surveilling for anomalous activity: Fuzy continuously surveils your data for relevant anomalous activity and alerts you to findings, helping you recognize atypical patterns or significant changes in behavior, and act on new information across different functions—even though you weren’t paying attention to it. These alerts may be an early signal from a feature introduction or UX change, a bug, or an opportunity to course correct. Reaction times are heightened and less time is spent watching dashboards.
Exploring hypotheses and identifying opportunistic patterns with correlations: As an extension of your identified targets, Fuzy also gives you Insights that build meaningful context about how customer interactions with your apps affect outcomes differently. For example, what in-app behaviors, usage patterns, or account characteristics distinguish likelihood of a positive outcome (retention, expansion, revenue) and how can you make more customers look like or interact with your app in those ways? Are there parts of the app having a negative impact? This can accelerate rapid, evidence-based hypothesis formation and discovery of unexpected insights that may even be a quick win for your team.
Providing targets, segments, pathways: Fuzy allows you to organize information by targets, segments, accounts, and pathways, giving you different lenses into your insights. For example, you can start with revenue as your target, then drill into segments or correlated behaviors for context about which is contributing more or less to this outcome. From there, you can gather second and third order insights that together become more than the sum of their parts.
In this post, we’ve looked at how you can use Fuzy to drive outcome-focused product strategy. Stay tuned to learn how we can help you “close the loop” by measuring adoption and outcomes of your initiatives, releases, and features.