Make your Product Intuition Stronger with Data
As product people, we sometimes get flashes of creative genius thinking where we are certain that a particular idea will be adopted by all users or will improve a user experience and our natural bias is to push to prioritizing it on the roadmap. When asked why this should be prioritized so highly, we would typically respond with “it just feels right and it is what the users will want. After spending so much time understanding the users, I just have this gut feeling that this is what we should be building next.”
This is product intuition.
We feel confident enough to rely on our instincts to determine what we should release next for our users since we understand the behaviors of our users by interacting with them. Sometimes we are spot on with this gut feeling and other times these gut feelings are amiss.
Product success rises and falls on product strategy. What is your product strategy, intuition or data?
Product intuition helps guide the direction of our product but we should also be critical of the direction we choose. We should be critiquing our decisions and when we do, I would encourage that we are thinking about them from these three perspectives.
- Money — How Much?
- User Base — How Many?
- Time — How Long?
Money — How Much?
Nothing tickles the ears of higher ups more than a report on the additional revenue to be made or cost to be saved if a particular feature is built for the users. We are able to get more buy-in from the business when we are able to tell the story of how shipping a particular feature will result in $$$ money to be gained or saved. Think of the internet companies that sell ad spots and then turn around to offer their users an opportunity to pay for ad-free services.
User Base — How Many?
Consider the following:
- In thinking about growth, we are thinking about how many more users we plan to reach by implementing certain decisions.
- In determining if and where we should be improving the user experience, we are deciding trade-offs and measuring the number of users affected.
- In deciding whether to say yes or no to a feature request, we will need to have a way of understanding the impact to the user base.
We are confronted daily with unlimited choices but limited resources. As PMs, we have to be able to make the most do with what we have and find innovative ways to create/get more resources. One way we measure impact in terms of scale and reach is when we are able to measure the amount of impact on the user base.
Time — How Long?
A popular saying goes like this “Time is Money”.
- How many steps and therefore time are we able to save our users in performing XYZ task?
- How much faster are we able to get our users to their destination within the product?
Product decisions are easier to make and product intuitions are easier to defend when we are able to tell the story of how much time we are saving our users by building certain features.
Time is important to us all, a common example is when we opt for signing in to services with our social media accounts rather than creating login credentials for that same service. What we are doing is saving our time up front from trying to remember our passwords and then going to through the “forgot password” sequence only to forget our passwords again 😄.
For the most part, users are impatient so any product gut feelings that save up on time is typically greenlit.
Summary
As product people improving our craft, we should make it a habit of validating our product intuition with data. Leaning too much on either intuition or data to form our product strategy leads us into making subpar product decisions as these product viewpoints are meant to complement each other.
As product people, we should make it a habit of validating our product intuition with data.
I have not always succeeded in validating my product intuitions with data but I have realized that I am able to make better product decisions and sound more convincing when I am able to validate my intuitions using any of the perspectives above.
Do you rely on only intuition or data, or do you try to balance both for your product strategy? Please share in the comments below.
