Frequently Asked Queries - Chapter 04 - Mixpanel
Chapter 04

Who’s doing analysis?

In this section:

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Who’s doing analysis

Who should be doing product analysis?

We’re confident that (nearly) everyone at a company benefits from learning more about how their products are being used. When looking at the total reports queried, the clear winner is Product Managers–by more than 2x!

However, if we slice the data based on reports queried per user, Analysts take the cake 🎂. On average, they create hundreds of queries per week and are the most likely to be Data-Informed users of any role. Together, these findings suggest that while people in Product rely heavily on their product analytics tool, they’re more likely to gut check existing data and modify saved queries, whereas Analysts constantly dig deep into their data to uncover new insights.

Analysts are also 4x more likely to export data for analysis than Engineers, likely to join the insights with data elsewhere (when armed with Excel or a BI tool, they can take their analysis even further). Marketing teams take a close second, probably because they use exported lists for campaign outreach. Growth runs more conversion analysis than any other department, suggesting how users convert (in-product or otherwise) is top of mind. 

Executives and Founders want to have a pulse on their most important metrics and do this using Dashboards and engagement analysis. 

In general, Engineers run the fewest queries compared to other roles. That could be because they support the implementation of a product analytics tool and typically help with the creation of new products, but monitor their performance less frequently. However, with rapid developments in the modern data stack, engineers are increasingly becoming more frequent adopters of product analytics.

“Depending on the size and scope of the leadership role, leaders should make sure they are not spending too much time in the weeds, but instead challenging their teams to make use of the data at their fingertips and asking the right questions to get the product managers looking at the data in new ways. It’s about finding the balance between DIY and delegation.

Emily Tate Managing Director at Mind the Product

“Data is core to more than just our product development. Over half our company actively relies on insights from Mixpanel every week. From Analytics and Product to even Customer Success, everyone uses product data to be better in their role and to enable the company’s success.

Ryan Withop Director of Analytics at WeVideo

Try it yourself

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See how a Saas company looks at key activities like “Sign up” and “Send message” broken out by department to better refine their ICP.

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Segment differences

For Digital Transformers and Startups, Growth teams are more likely to be Data-Informed users than other roles. Every improvement made upstream has a compounding effect downstream to the product, impacting retention, LTV, and more. It’s no surprise that users in Growth are more likely to dive deeper into the data to find high-leverage insights. Other teams at these companies (like Product) rely on data to understand which features are most impactful and how they could affect retention.

The takeaway

Tech Giants often have teams dedicated to owning product analytics, and this role is key to uncovering meaningful product insights and running efficient product development.

But if you want to keep up with—or beat—the competition, it’s important that team members throughout your organization take time to engage with your product data as well. While product analysis may not be core to a particular team’s responsibilities yet, the insights in that data can help inform key decisions that determine future trajectory.

Resource from Mind the Product

Cracking The Data Code – Mike Bugembe on The Product Experience

In this episode of The Product Experience, Mike Bugembe talks about working with data scientists, and how best to collect, work with, and make decisions based on data.

Who’s doing analysis

Who consumes pre-built reports and who creates new ones?

People love viewing analysis. But creating it is a whole other prospect. Our analysis shows the majority of insights come from reports and dashboards already built—Data-Curious and Data-Informed users view existing analysis over creating new reports more than 70% of the time. Data-Informed users, however, are more than 10% likely to create new analysis than Data-Curious users.

“Product teams are normally the ones building the widely used dashboards, however, we actively encourage everyone to do so. With product analytics, it’s really easy to quickly modify a “pre-built” report to get a slightly different perspective, and I will often add an extra filter or two myself while browsing through them.”

Miloš Ranđelović Head of Product Analytics

Segment differences

As we noted before, Startups depend on product data the most. However, they’re also the most likely to reuse existing reporting. It could be that Startups’ data and products don’t change as frequently as other companies’, so they’re able to reuse the same reporting for longer periods. It’s also possible that Startups have less bandwidth dedicated to data analysis, so they aren’t able to build out new reports as often as more established companies (though they are running and saving queries within those reports more often, as we noted above. Go Startups!).

In contrast, Tech Giants and Scaleups are more likely to create new reports than Startups and Digital Transformers. That’s likely related to the ever-changing product innovation that takes place in these companies—as new events are added and created, creating new reports to track launches, experiments, and more is necessary.

The takeaway

If we can give you one piece of product analysis advice, it’s this: Take the time to build your core reports well. When those reports are dialed in, everyone throughout your company will benefit from the ability to answer common questions with minimal friction. Once those core reports are created, you can always zhuzh them up to better answer more specific questions by adding new filters, breakdowns, adjusting the time frame, and more.