• Data-Driven Decision Making and Feature Prioritisation for a Product Managers

    Data-driven decisions are inherent in product management, be it B2B product or B2C. PM has to take numerous decisions on a daily basis whose impact and value addition can not be estimated beforehand. Hence, PM needs to dive into the data to provide basis and sound justification of their decisions. Key areas where data analysis is essential: 1. Measuring Product Performance against benchmark KPIs 2. Setting up product vision and roadmap 3. Identifying the next feature to build (feature prioritisation) 4. Optimise team performance 5. Should the product be expand or kill or revamp 6. Managing product P&L How to find the direction when your data is saying something and your gut (and your team) is saying different things. In the practical world, data does not always show the true picture. It is full of biases, deviations. Hence, data can not be sacrosanct. but, thankfully, PM doesn't have to be data expert. It becomes a lot easier if a PM acknowledges the limitations of the first hand data points and use it with an acceptable margin of error. How to enable data tracking in B2B and B2C product. Once you have data, now what? - How to make sense out of millions of data points that you get. Interpreting data without being an expert in data analytics. How to convert interpreted data into product improvement and verifying if it is helping you to achieve product goals. Not all metrics has to be monitored regularly. Once the tracking is in place, some KPIs has be to monitored daily, some weekly and some monthly. But a PM should have a bird's eye view on the product and should be aware how every product change is impacting the KPIs. Once a PM gets the experience how KPIs behave with product changes, taking a data driven decision becomes easier without diving deep into the data.