What is “Data. Empower. Product”?
Redefine what I’m going to write.
During these years as a data-hungry product manager, I step out from viewing reports to data transferring, how to create numbers as the fact I share with others. I found it has the power to change people’s minds. It is more powerful when it includes not only the numbers but also the intentions, and desires behind it. The most influential ones are from the users’ mouths.
As a product manager, I launch products to create value. To validate it works, I start by checking the fact. The fact includes the users’ behaviors that data can tell and the intentions that user interviews can tell.
⭐️ Data is one path to the fact
While doing data analysis, the findings from the fact are powerful. People call it, insights.
Say you have an ad position that used to have a 3% click rate. You’s goal is to make it 5%. One day, you make some change and it becomes 15%. Would you celebrate?
I had a similar experience. The celebration popped into my mind for 2 seconds, then was called off by many customers’ complaints about not being able to close the ad.
A number is not enough. I need to know the reason behind it.
It took a long time to get the insights.
While I tried to analyze a product, I went from defining how to log, the formulas for the metric, and communicating with engineers. Waiting for the metric after developing sprints, I can validate if my analysis makes sense.
The transferring logic manipulates the numbers. Even changing the way to present it is enough to flip the opinion.
Therefore I step out from viewing reports to building the dashboards. I want to know the logic behind the scenes, and how we make the fact.
And I don’t stop at the beautiful dashboards. I want the fact makes an impact.
⭐️ Talking to users is another
When I’m looking for a restaurant, even if they all have 4 stars, I read the comments to help me choose one. I view the product data dashboard daily but also watch out for the emails sent from customers. They tell real stories.
An average height of a class is 160cm. It doesn’t mean everyone in the class is 160cm. Someone may be 149cm and someone may be 180cm. Though data helps us get the average quickly, seeing the people is real.
From Teresa’s continuous discovery habits, a user interview is a great way to get real behaviors and intentions. It’s not aimed at large numbers. It’s aimed at cumulating the understandings.
We like to do things at scale. Sometimes, do not scale things is a way to scale. It helps us understand the truth behind the numbers.
Full view is powerful
Knowing the truth is power. When you convince your boss with an insightful report with solid numbers, you feel the power.
Though reviewing data is a quick way to understand the users, they are not numbers. The users who use the products and the markets that count the revenue are composed of real humans.
Besides users, there are buyers who don’t use the product but pay for it, makers who build the product, resellers…etc. As a PM, I can not log these people’s behavior data. I want to know their thoughts, which impact what I should build.
Empower others
We don’t want to rely on one team member to do all of the interviewing. This gives a single person too much power in a team decision-making model.
- interview customers together by Teresa
Plus, if I’m the single person, I’ll burn out while building products that no one wants to use.
Collaborating with diverse professions is the way to build great products. Professional people can work what they want. To attract professions or make people want to be professions is passion. Humans can resolve any problem if they want to. Give them the reasons so they want to.
Lead by context not control. This principle follows human nature. We all like to resolve problems. If we know the problem is real, we like to resolve it.
Show the full view to others. Invite them to collect the pieces of the full view. Give others the tools, the methods, the permissions, and the time to access the fact.
I always get more after empowering. When I invite the engineers to join the user interviews, they find and fix the technical bugs I don’t even notice. When I set up the BI tools so non-technical colleagues can self-serve analyst, they work more efficiently and level up their analysis.
Data. Empower. Product.
I find it works like a virtuous cycle.
I’ll write about what I learned, and don’t learn yet here.
🤩 I’m happy to hear from you. Feel free to reach out to me on LinkedIn Karen Hsieh or Twitter @ijac_wei.
🙋🙋♀️ Welcome to Ask Me Anything.
