4 Common Misconceptions About Data-driven Product Management
Data helps us build better products. With so many companies embracing the data-driven approach to product management, I was recently reflecting on what are some of the common misconceptions about this approach. Here’s what came to mind.
1. Qualitative data is not needed
One of the common issues I see is product managers who don’t use qualitative data. For some reason, ‘data-driven’ is being equated to ‘using numbers’ and so the words of consumers are not seen as data, which is simply not true. By ignoring such qualitative data, product managers miss the opportunity to fully understand the emotions of consumers, the why of their behavior which in turn could help explain some of the hard data. Not to mention words create empathy, a key ingredient for any team.
2. ‘Looking’ at data is sufficient
Sometimes when product managers run experiments, they say they’ll look into the data. The problem is, sometimes that’s exactly what they do. They look at the numbers and make conclusions. However, that’s a wildly ineffective way to do analysis. You need to have a hypothesis and then design a way to test it while making sure the data collected is of high quality and only then start to understand the data within the framework of statistics. To not do a thorough job in the first few steps of this process is to arrive at the wrong conclusions while you analyze the data.
3. It happens overnight
Well, it doesn’t. One day someone says ‘We need to be more data-driven’ and from that moment on not much has changed, frankly. It takes time to build up the mindset, the analytical skills and make sure all the required infrastructure to support it is in place. Not to mention, being data-driven requires practice. You might design an inconclusive experiment, or end up snowed under so much data that analysis-paralysis takes the best of you. You’ll get better over time and that’s normal. So start now.
4. Data is free
I am not sure where this one comes from, to be honest, but I see many companies wanting to be data-driven and not really investing in it. Being data-driven costs money. Qualitative data requires time and money to collect it first hand from your users. Do you want product usage data? You’ll need to invest in a good product analytics tool. Not to mention, high-quality data is not something that happens by accident and designing, implementing and maintaining a robust tracking system can be difficult and expensive. Do it anyway.
At the end of the day, data will help you build a better product but it’s not a panacea. You’ll still need all the other ingredients, the most important one being the right people in your team.
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