3 goals to quickly improve the Product Management practice in your team

There is a huge number of things you need to do to be a successful product manager. And when you are starting in this role or trying to improve your current performance, there usually isn’t much clarity on what areas to focus on.

There is also a tendency to “shelter” on the activities that are more within our confort zone.

For that reason as a product leader I like to set personal goals to Product Managers that try to foster their focus on areas that will make them progress faster, with higher balance and probably with more success for their products.

The goals


I found this one very hard to measure. Ideally we want every decision to be based on data, but we can’t measure how are we making every single decision.

So my proxy is to set “learning goals” and prepare a “deep report” using current data.

For instance, we may want to see the performance of traffic sources in an e-commerce site. Of course we will see the high level conversion rate per source. But what about knowing the different steps micro-conversion among sources, or the most visited products, or cross-source attribution.

The report will have the following sections:

  • Learning goal & set of questions we want to answer
  • Analyzed data
  • Answers to questions
  • Data we found is not currently tracked (and plan to implement tracking)
  • “Surprises” (unexpected findings)
  • Conclusion and next steps (ie — put X in the backlog, or investigate Y further)

As a leader, you can target a monthly or by-weekly report and review it in 1–1 conversations. It should be a straightforward conversation, you can add questions to improve their reasoning, but it is mostly a tool for them, to help them drive better data-driven conclusions to improve their product.


As in data-drivenness, it is very difficult to measure if every decision is made with the customer in the center of your thoughts.

So again I use a basic proxy, that is number of customer interactions. The same method is used: set a learning goal and set up a customer interaction that will help you learn what the customer thinks.

  • You want to see how easy your checkout is? Set a usability test.
  • You want to investigate what drives conversion? Do a round of customer development interviews
  • You want to check if your idea of solution resonates with the user? Do a solution-interview.

As a leader, you can target a monthly or by-weekly customer interactions goal, meaning that each member will be face-to-face with 3 to 5 customer at least once a month.

You can’t easily measure customer centricity, but you can make sure teams are constantly hearing the customer, and by training that muscle make decisions with user’s pains in mind.


Finally some good news: you can measure how often you’re running experiments 🙂

As Marty Cagan says, great product teams run several experiments per week. But if you are starting out, this is a muscle you need to build, so again shooting for a monthly or by-weekly experiment goal should be a good way to get started.

If you are a leader looking to improve team experimentation, keep in mind this few tips to review when results are presented:

  • As with everything we covered, experiments should have a learning goal, hopefully aligned with testing your riskiest assumption
  • Make sure different test types are being used when necessary. Concierge, wizard of oz, live data prototype, and many more are very powerful techniques that should be used and combined to discover what is the right product to build.
  • A/B testing is not “this type” of experimentation. A/B tests are the way to make sure something we already built have the impact we expected or to try smaller changes to improve conversion or other metrics. What we want with experiments is to learn about how something may perform before we build it. That being said, sometimes “low cost” A/B tests are used to measure for instance the result of a wizard of oz or fake door experiment.

A word on balance

This goals try to work on 3 areas that I usually find are not balanced in PM profiles. Very data-driven PMs usually are not that eager to contact users, and the ones that are do not have deep analytics passion. Same goes for experiments: very detailed or user-research passionate PMs don’t enjoy the lean philosophy and not having the time for long research and analysis phases.

Considering your team, you may decide that you need to focus on different areas or get a different balance, choosing different individual goals.

Earn extra points

There are two extra activities that I haven’t yet set as goals for the team, but are very important for good Product Management:

  • Set your product strategy and work on your strategic vision
  • Embed your decisions with industry and competitors information

I may came back to those in future posts 🙂

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