The big gap between Product and Analytics

Corinna Stukan
6 min readDec 7, 2020

It’s been great to see that especially over the last 5 years there has been a significant increase of resources for Product Managers. The community is growing and growing, and there is a lot of sharing of knowledge and best practise.

There are plenty of talks around product strategy, discovery and how to build great product teams. We know that communication and leadership are critical, as well as having solid strategy skills, while being strong in delivery and execution. Just the usual gazillion skills you need as a Product Manager. 🤷🏼‍♀️

We’ve also been preaching for a while now that the key for discovery is to get as close to your customer as possible. Talk to your customers, get out of your building, gather data.

Almost brushed over the last bit? Sure, we all say we gather data about our customers. And I really do see a lot of Product Managers being quite confident in conducting user interviews and research before building a feature these days.

Most Product Managers are also great at paying close attention to customer feedback that comes through the various channels. This is great!

But how come I barely ever hear about any meetups and talks on how to become better at the other key part of gathering dataproduct analytics? Why do the major Product Management resources not write more about how to measure your product usage and behavioural patterns?

I consume a lot of product content, and attend local and major product meetups whenever I can. I was wondering if this was just my bias — maybe my local product community isn’t very advanced in this topic yet. I started looking through talks from some of the biggest names in product over the past years.

The Gap in Product Resources

Mind the Product is one of the largest product communities in the world. They have great content, and organise a wide range of large conferences and local product events. I started browsing through the history of all of their talks from their conferences in Singapore, London, Hamburg, and San Francisco over the past 9 years. From Marty Cagan to Jeff Patton, most of the well known product people have presented here at some point. Despite the amazing range of talks, I was missing one particular topic.

Me going through 9 years of Mind the Product talks looking for analytics related talks 😔

You can see that my search across this list for the keyword “analytics” spat out.. 0 results. I tried the same with “data” and “analysis”, again no luck.

How come gathering data is such a fundamental part of the role of the Product Manager, yet we barely talk about it on those major events or meetups?

My tweet asking for the best product analytics resources received nothing but crickets.. although this might also be a representation of my rather low following and Twitter’s nature of your posts either going viral, or getting zero engagement at all.

But even when looking for analytics related resources, the main articles that come up are typically directly from the tools that help you analyse your data such as Mixpanel, Amplitude, or Segment. All of them have fantastic content by the way, with my current favorites being Mixpanel’s Guide to Product Metrics and Amplitude’s Product North Star framework. I learnt so much from them and am amazed by the quality of their work.

I only wish that the main Product Management blogs, resources, conferences and meetups would talk more about how to build an analytics strategy, how to choose the right tools, what to measure, and which frameworks to use.

No offence to all the wonderful analytics tools out there, but of course they will teach us frameworks that closely align with the features of their products. I’d do the exact same thing.

I strongly believe the much needed next step is to democratise product analytics knowledge. We need to talk about it more on our Product Management conferences, local meetups, and most popular PM blogs. We need a neutral view on tools and best practises, and help new Product Managers get started more easily.

The Gap In Product Management

We all agree that product analytics is a key part of a Product Manager these days. Marty Cagan has shared this fantastic article in 2014 on the many purposes of data and analytics on our product practises.

Any capable product leader today is expected to be comfortable with data, and understand how to leverage analytics to learn and improve quickly.
- Marty Cagan

If you want to shift the focus of your roadmap to outcomes instead of outputs, you need data to show progress on your product goals.

If you want product discussions and prioritisation to be less opinions based, you need data to justify what to focus on instead.

If you want to deeply understand your customers, you need data to analyse their usage behaviours.

According to a great study Mixpanel has conducted with Product School, only 10% of product teams are able to validate their most important product decisions with data.

Yet the study also shows that the most advanced product teams don’t just look at customer feedback, surveys, or sales and marketing data, but also incorporate user behaviour data into their decision making.

My friends and colleagues in product who have applied at big tech companies often told me that product analytics questions are a big part of the interviewing process.

Over the past 4 years I have conducted and sat in hundreds of interviews for Product Managers for my team across Australia and New Zealand. The most typical answer I get when asking about product analytics experience is that they’ve had a separate analytics or insights team that would present any findings and trends to them on a regular basis. Some teams even had no such capability at all and the Product Managers didn’t seem to take it on themselves to solve it either.

Needless to say, the best Product Managers I’ve interviewed over the past few years either made a conscious effort to integrate the analytics team into their product teams, or got stuck into it themselves by setting up the tools and dashboards and figuring it out from there.

It’s not about being able to perform complex queries of raw data for Product Managers, but being aware of the importance and having an analytical mindset.

Some people claim they are “not analytical” — to this date I haven’t seen a single good Product Manager who hasn’t been able to learn the skills to understand and translate product data into insights and product decisions over time.

So where to from here?

I personally took the learning by doing path — I never worked with an insights or analytics team but taught myself how to use analytics tools and what to measure. It’s fair to say that this has been quite a trial and error process for me over the last few years.

Once I started to stumble across those specific resources from tools like Mixpanel and Amplitude, I was able to apply a more structured approach to my analytics work which was a huge step forward.

But as I stated earlier, we need to get better at sharing data and analytics knowledge in the main product communities and help Product Managers get started on their analytics journey more easily.

I want to contribute to this through this blog and share some of my biggest analytics learnings from the last few years. My journey is far from over though and I will document my progress as I go. I’d love to hear from you in the comments if you have specific analytics topics or questions that you’d like to read more about.

Want to read more about data practises?

I am proud to share I have launched my first ebook to help you with your product analytics and data practises! The Insights Driven Product Manager is your essential guide on how to track less and get more insights from your data to make better product decisions. It includes practical frameworks and worksheets that you can apply to your products straight away.

Get the ebook here

Originally published at https://www.productandsystems.com.

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Corinna Stukan

VP of Product 👩🏼‍💻 Author of The Insights Driven Product Manager 👉🏼 www.insightsdrivenpm.com Helping companies build a data driven product culture.