Product Practice #295 |
Dear Reader,
Many product teams perceive the focus on User Outcomes as arbitrary goal-setting and the opposite of serving users. And it‘s easy to understand why.
Many widely shared examples of User Outcomes out there read like this:
„Users buy more tickets“
„Customers use more integrations. “
„Returning shoppers add more items to their basket.“
A product leader recently approached me after a conference talk, sharing his team‘s concerns that Outcomes would just be repackaged business goals. Looking at the above examples, his team would be right. These read like how the company or business wants their customers to behave.
To make Outcomes (aka changes in human behavior) useful, you have to remember that they should describe changes in behavior that are useful to the audience you intend to serve, which requires a proven problem.
Useful Outcomes = Useful for the User
It‘s not enough if Outcomes describe „technically correct“ changes in behavior. Instead, there should be a clear connection between business-informed research intent and insights generated by qualitative and quantitative techniques.
Another way to approach this is to look at Outcomes as flipped user problems:
The simple question teams need to try and answer here is, „How would users whose problems got solved behave?“ This will then be the foundation for finding appropriate measures to set in your OKRs.
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Thank you for Practicing Product,
Tim
PS: My friend Itamar released his long-awaited book "Evidence-Guided" last week. It's a practical synthesis of the principles taught by Itamar to help companies move away from opinions and towards more evidence. I highly recommend checking it out
Amazon USA: http://amazon.com/dp/B0CJCDP1H7
Amazon UK: http://amazon.co.uk/dp/B0CJCDP1H7
Amazon Germany: http://amazon.de/dp/B0CJCDP1H7
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As a Product Management Coach, I guide Product Teams to measure the progress of their evidence-informed decisions.
I identify and share the patterns among better practices to connect the dots of Product Strategy, Product OKRs, and Product Discovery.
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