This article is also posted on Spiceworks.
Take a deep breath. Relax. Product management is hard. I don’t know a product manager that hasn’t had feelings of insecurity. Am I making the right priority call? Will they know I’m not really an expert? Is my team going along with me just to be polite, or do they know of a better solution?
You will undoubtedly make mistakes (as all humans do!), but that doesn’t mean you’re not equipped for the job. When you’re feeling down, remember there are tools and insights at your disposal.
One of the greatest assets you can leverage is data. In my career, data has been one of the most reliable tools for overcoming imposter syndrome. Here’s how.
One of the most critical job requirements for product managers is the desire and ability to learn quickly. Data empowers you to expedite that learning process. Not only will data help you understand your market, product, and customer base, but it will empower you to ask more and better questions.
What is our TAM and how does that break down across our competitors? How has our customer mix changed over time? What are the most commonly and least commonly used features in our product? Where do our users get stuck or experience friction today? These questions, and resulting conversations, will boost your confidence as you gain new insight into the impact of the features and products that you create. You can then use those insights to inform more and better questions and experiments as the cycle of learning and iteration continues.
Establish credible humility
Credibility with your development team and internal stakeholders is essential for effective product management. Using data to guide questions, discussions, and decisions will not only contribute to the best outcome, but your peers will appreciate that you’re leveraging facts vs. using a tactic to force your will.
I remember a time shortly after joining an organization where the lead engineer had worked on a core part of the product since inception, and felt very strongly about how we should fix a particular problem. I disagreed based on what I had seen so far, but was afraid to speak up out of fear I was missing some hidden context and might lose the respect of the team. To overcome this trepidation, I analyzed behavioral data showing how often users actually performed the workflow in question to help validate my assumption, and brought my findings and questions to the team. The conversation went very well — we actually dug into more data together, and in the end unanimously agreed on the best path forward based on the data, rather than conflicting biases.
I think it’s important to highlight here that you must use the data in an approachable, respectful, and learning-focused way as opposed to trying to win an argument/debate with numbers. You’ll find that more often than not engineers and other internal stakeholders have the best ideas and questions, and curating a safe space to analyze data together can go a long way in creating the best outcome for your customers.
Identify customers to learn from
When identifying customers to speak to, qualitative feedback can be invaluable, but so can quantitative data. We usually tend to interview customers who give feedback, but you can often learn as much by analyzing usage data to find customers who don't use the product or feature much, so you can find out why. Some of the best customer interviews I’ve had were found through analyzing usage from folks who had never submitted written or verbal feedback, but had tons of incredible insights and ideas when I got them on the phone. Bottom line: there’s a gold mine of insights to be discovered in analyzing product usage first before asking for customer feedback.
Validate or challenge existing POVs to produce the best outcomes
As product managers, we’re hired often strategically to bring a fresh perspective and worldview to existing problems our organization has faced for some time. Using data is a great way to productively challenge existing points of view and ingrained biases to help shed new light on existing problems. The result? Clearer direction toward more valuable wins.
In a previous role, there was friction between the support and product teams over the bugs that were prioritized. The support team felt that the product team was spending time fixing the wrong things vs. what had the greatest impact in their mind. I decided to meet with the team and outline/discuss the data behind our bug prioritization process which was largely a combination of ARR and breadth of impact. Not only did the team appreciate this overview, but they understood our point of view better. This gave them more confidence when speaking to customers, which translated into more reassurance and trust from our customers. It also helped validate that our process was effective, and that based on our top line metrics, we weren’t missing critical bugs.
Increase your confidence
Finally, confidence is imperative in Product Management, and I’ve found that my personal confidence and performance as a PM are closely correlated. Leveraging data has helped me improve that confidence in every organization, with every team I’ve worked with. Data has empowered me to speak up countless times when I’ve felt shy or ill-prepared. Even when I’m wrong, data-focused discussions almost always lead to additional context that I would not have learned otherwise, which contributes to my growth, confidence, and performance as a PM.
Bottom line: Being a PM is no joke. It’s a tough job, but you are more than capable. And data is ultimately what can best help you (and others) realize that truth!
Learn more about qualitative vs. quantitative data and how SaaS teams can use both.