There's this buzzword I've seen Product Managers use relentlessly in how they describe themselves.
Cool. A few points here:
Data isn't always pulled from an analytics tool or spreadsheet.
Market or industry research is data.
A group of users sharing similar experiences or problems is data.
A customer anecdote laced with emotion is data.
Surveys, expert opinions, competitor moves, forum trends - all data.
Moreover, data isn't always served at a mouse click.
It can be a taxing endeavor at times.
We need to read a lot of the signals in the air, dust off the bias as best as we can and then process these "data points" to formulate a hypothesis.
Take RICE prioritization, A/B testing or tech estimation.
Parameters like confidence & story points are best guesses, not hard truths.
Moreover, try reconciling Analytics data with your database/server records. There's a lot of sampling & estimation in play.
You need to read data for what it really is.
Even once there is quantifiable evidence, you still have to convert that into a favorable action.
That's the REAL goal.
A gut-based decision that delivered more impact still wins despite our "love for data".
As a Product Manager, you might be asked a lot of questions during an interview. One of them includes technical questions. Here are 4 types of technical questions that you might come across.