3 Strategies to Transition from Product or Data Analyst to Product Manager
Making the leap to product manager (PM) from any background can feel like a major challenge. It’s no secret that the PM market is getting more competitive and while there’s no shortage of good advice out there on how to become a PM, very little of it is targeted at people with data/product analyst backgrounds. While working in analytics functions can get you very close product management, there are still a few key growth areas needed to set yourself up to break into the role.
I have talked to several analyst types looking for advice on making it into product, but most content I can point toward is aimed at people with developer, design, or sales backgrounds. As demand for product analytics grows to all-time highs, so will the cohorts of analysts looking to make the transition into product management.
I spent two years in product analytics and strategy-oriented roles at a scaling B2B SaaS company. I collaborated closely with PMs on a daily basis before transitioning, and a year into the switch, there are a few things I have learned to help others do the same.
Here are 3 key strategies to leverage your strengths and pitch yourself as a future PM:
- Become your product’s go-to expert in measuring AND articulating user value
- Get involved in the “Discovery” process
- Start thinking and working like a PM
1. Become your product’s go-to expert in measuring AND articulating user value
First of all, make sure you are working to position yourself as an expert on not just how users are using the product, but also where they are deriving value from it.
In some organizations, product analytics can be wrongly perceived as a purely supportive role. You can quickly find yourself writing SQL queries, building reports/dashboards, or creating pivot table after pivot table until a stakeholder is finally satisfied or moves on to a new question.
An empowered product analyst should not only be fielding requests from stakeholders, but also prioritizing time for proactive analysis of the product.
Here are some questions to proactively research:
- What are the key “aha moments” in the user’s journey?
- What are the key contributors to churn in the data and why?
- Where do we see the least amount of feature adoption, and why?
This is a small sample of questions, but the point is that in order to pitch yourself as a PM, you first have to make sure you are working proactively and strategically in your role.
As you take on these projects, you can grow your confidence in understanding what opportunities exist to improve the performance of the product and meet either product or business objectives.
As a product/data analyst with high fluency with account data and usage metrics, you can be an expert who can answer questions that any PM should know (and show the data to back it up).
Example 1: Understand your customers?
- How can internal data be best used to segment the customer base?
- Which segments represent the largest revenue or usage?
- Which segments are growing fastest? Which have the highest churn?
Bonus points: Think about ROI / Tradeoffs
Try to plot some 2x2s to see a combination of clients along two key dimensions.
For example, can you show what segment represents the largest revenue base and highest churn? If a PM hasn’t already asked for this, they will definitely want to know in order to dig into the user needs of this segment in more detail.
Example 2: Understand what the data says about use cases
- What series of events represents an established use case
- Can you infer any new/interesting use cases or segments of users based on their usage behavior?
- Is everyone in your organization clear of the different use cases and the definitions within the data? This could be an excellent opportunity to drive alignment based on your research.
Example 3: Propose your product’s North Star metrics
Amplitude and other product analytics software products have a lot of free resources on how to structure metrics to make sure they are measuring value to users and value to the business. You don’t need to overcomplicate it or invent your own framework — make sure to take advantage of some common approaches!
Bonus Points: Demonstrate Product Manager skills
First, I would recommend that you take a stab at a North Star analysis once for yourself. Use your knowledge and stake out some claims on how to best measure usage data in order to ensure that the product managers are optimizing for the right thing in their work.
Second, take the initiative to organize and facilitate a North Star workshop with a PM and include other stakeholders. This is a valuable opportunity to:
- Learn how to run a workshop with multiple sets of opinions and arrive at a result that aligns across different stakeholders
- Make a very compelling case to transition into a PM role where this type of activity and influencing is a highly sought after skill
Socialize what you learn
One key to being a strong PM is to learn how to influence without authority. You don’t always need to wait for a dedicated forum or opportunity where a PM asks for your opinion. If you are seeing something new or useful in your data, show how it can be applied to the product itself.
Creating compelling artifacts for your PMs to leverage your insights is a great way to pitch yourself as a PM in the future. First, make sure to communicate your findings clearly and concisely, but also prepare yourself to get feedback and iterate on your analysis.
It helps to think about your audience and their perspective — this can help you anticipate questions and make sure you don’t come on too strong with quantitative analysis to an audience that might be more comfortable working with qualitative research.
2. Get involved in the “discovery” process
Data analysis is a necessary skill for a PM, but far from sufficient. One of the key missing pieces in your tool belt as an analyst is the concept of “discovery.” In short, discovery is the process of figuring out what to build. PMs start by learning from customers and stakeholders to understand the problem to be solved, spending time talking to users, and creating a set of requirements that attempts to solve a shared set of user problems.
As a product/data analyst, you are uniquely well-positioned to make the process of discovery more efficient and accurate. While recruiting users to interview is often a burdensome process, by leveraging usage data to help specifically target segments of users where feedback will be most valuable, you can quickly streamline the process.
But the most important value-add you can provide is the concept of validity in qualitative feedback. User interviews can only happen at a limited scale — PMs often struggle with whether or not specific user feedback is representative of a larger issue or if they are at risk of over-indexing on one outlier.
To combat this, product/data analysis can help isolate more “typical” users and ensure they don’t represent an extreme in any kind of user behavior. Good analysts can also create pools of users for outreach that are balanced in their representation across key segments — this is key to building confidence that what PMs are hearing from users will scale to the wider customer base.
3. Start thinking and working like a PM
The more you start working like a PM, the easier the transition will be. Here are a few tactical things you can start doing:
Prioritize all inbound analysis requests into a “backlog”
A backlog is just an organized list of output needed to be worked on. Here is how I would approach it:
- Come up with clear guidelines for how you prioritize tasks that are based on ROI. For example, the Weighted Shorted Job First is leveraged by many product managers as well, but many other lighter-weight approaches can be used.
- Look for themes across items in your backlog — try to see if there is an underlying problem to be solved with one approach, rather than several one-off analyses.
- Think about what work you do that will have the greatest impact at scale. For example, it helps to think about what it would take to answer 80% of the outstanding questions for 20% of the effort, rather than aiming for 100% of all questions and blowing up your timeline to deliver.
“What problem are you trying to solve?”
Product/data analysts often get requests to pull specific sets of data with little context provided. The ability to reframe these requests is one of the most transferable skills to becoming a PM.
Here is the analog citation faced almost every day for PMs. Users and stakeholders are constantly requesting new features/solutions, and a good PM will always try to dig into the problem driving that proposed feature/solution. They need to ask, “what problem is the user facing that underlies this request?”
You can do the same thing when working with PMs or other stakeholders — instead of responding to a request for a specific set of data or a certain dashboard, a strong product analyst will always try to understand the decision that needs to be made, then find the right data and methodology to inform the path forward.
Key Takeaways
If you have the urge to not just analyze product or business performance, but instead help decide what gets built in the first place, then making the jump to PMing can be very rewarding.
The ideas and examples may represent work you are already doing, but you may not realize are already helping to prepare your product resume. It’s vital to connect the key components of the data/product analyst role to what’s expected in product management. While it will be hard to check all the boxes at first, starting to think and work like PM while in an analyst role is a great way to get started.
