What's your strategy for staying on top of product metrics and KPI trends?

While product goals and key performance indicators (KPIs) provide essential guidance, they should not become unwavering constraints that hinder necessary pivots in a product's direction. Here's why this shift in perspective is crucial: 1. Flexibility In Uncertainty: The modern business landscape is characterized by rapid changes and evolving customer demands. Static goals can be impractical in such an environment. Focusing on product-market fit allows teams to adapt and pivot to prioritize what matters to users. 2. Efficient Resource Allocation: When a product falls short of goals, it is vital to understand what worked and why, so that resources can be channeled into features that resonate most with users, thereby maximizing success.

Focus on Data analysis go by inputs what data says not by intuition or insights! There are times where you can take seasoned hypothesis and assumptions but prioritizing data over all is the market requirement! Continuous Improvement and Monitoring is needed backed with data and market insights! Be in the field and understand customer inputs over anything! Be a Consumer Centric Listener always in the journey

In my experience, defining success metrics early in a product lifecycle helps set the right expectations with stakeholders. The key metric often comes down to measuring the ROI of a product, whether it is user engagement, new signups, or an increase in $ amount. Senior leadership is often looking for a justification for investment in a particular product area. So quantifying, as much as possible, what the expected ROI will be and how you will measure it is crucial for most projects.

It’s much less about trends (easy to get lost focusing on that) and much more about making sure you have well better non-vanity metrics that tie to the value you offer customers or a core business need.

My priorities would be: 1 - Can I import/export easily what we create in case we switch + data safely. 2 - how easy the integration is. 3 - Does the chosen solution add to what we can come up with ourselves? With AI being a critical booster to everything, I would expect analytics tools to add additional value.

When possible, turn to data analysts or data visualization experts to build dashboards based on the requirements you set that should be met by dashboards. Think about what dimensions you’ll need to segment data by in advance, before the first dashboard is even published. As new data questions come up, always ask yourself if you will make decisions based off of the answers rather than creating multiple views for the sake of curiosity. This will help to make sure you’re optimizing your time, or the time of whoever builds and maintains the dashboards.

Look at your dashboards at least once a day, even if just a glance at your primary KPI to make sure nothing has dramatically changed that will require quick action. Do deeper dives at least once a week. Consider what new views or analysis could help longer term planning on a monthly or quarterly basis. Lastly, make sure you have regular data auditing checks to validate data quality and accuracy. These can be more or less frequent depending on how often the data tables or data capture is being changed.

Find ways to share insights and anecdotes you’ve gleaned from regular data analysis. Leverage data in regular product reporting, or in future documents you are writing where data can and should be used to support your decisions or plans. Whenever possible, pair a data insight with an action you’ll take as a result. After all, data should be used to inform actions or decisions. Have a bias for acting off of the insights you learn from regular analysis.

While product metrics are crucial in healthcare as well, more crucial is to continuously share thoughts and capture emotional and quality of life aspects from groups of early adopters, and negators. A factor which converts a negator could be given higher weightage.