Product Analytics Newsletter
Edition #8

Good morning product owners!

Product development is many things, but it has a lot to do with experimenting with ideas. As we are the Product Analytics Newsletter, of course I believe this should be done with rigour.

I’ve had some interesting discussions on that topic in Reddit (full reveal, I am 3CheersForManhattans): here and here. What I’ve learned is that we all have very different ways of running experiments.

My process is far from perfect. I currently document my experiments in Asana with a bunch of custom fields. Those are exported to my data warehouse (Snowflake), I do some transformation of the data (with dbt) and analyse it with R.

I already have a pretty good idea of how I want to improve the process and I would very much want to learn more about how other product owners are running their own experiments. If you care to share, send me an email at

With that, on with our 8th edition of the Product Analytics newsletter


  • In Product News, Mark Zuckerberg talks with Yuval Noah Harari about how technology impacts community and individuality – take me there
  • In Strategy, Dan Olsen build pyramids… that’s product-market fit pyramids – take me there
  • In Practices, we design valuable product experiments – take me there
  • In Behind The Scenes, we show off of our own evolving Product Analytics stack – take me there

Is the TL;DR section above helpful?
*|SURVEY: Yes|* *|SURVEY: No|*

Last week, I asked if you readers were product owners. And 100% of you are (with a solid sample of 2 responses, lol!)!

Theoretical vs Practical Considerations of Next-Generation Products
Mark Zuckerberg & Yuval Noah Harari in Conversation

Has that landed on your radar? Ok, it might not directly talk about products, but core to that conversation are how digital lives and AI are impacting individuality and communities.

To be honest, I was so expecting a PR stunt, that I kind of forgot that this 1.5 hour video was a conversation between 2 great minds of our time.

The conversation starts by asking the following question: what is the purpose of online communities? Is it about connecting people, or harmonizing them? And how to make sense of a world that is more connected but, at the same time, is building more walls, is more fragmented?

The conversation gets a little bit more heated when Harari asks what is the goal of Facebook. If it is to facilitate the building of communities, shouldn’t it try to remove individuals from their screens and actually participate in building real-life communities?

A part I really liked touches on the impact of AI on human agency (also a high point when I read Home Deus). What happens when AI knows me better than I even do and I allow it to make decisions on my behalf. How am I still myself if a product acts on my behalf?

PR stunt? Most probably. But Harari does take that opportunity to question how Facebook, as a product, empowers its users and communities. And Zuckerberg does come off a bit defensive at times, but still is able to provide solid answers to Harari’s concerns.

P.S. If you’re one who believes that Zuckerberg is an alien, that WILL NOT change your mind.

Product-Market Fit Pyramid
“Mastering the Problem Space to Achieve Product-Market Fit” by Dan Olsen at Mind The Product SF 2018

“Dan Olsen… again?” you may be asking? And I retort: “Yeah! I like him. Sue me!”

This thing is 30 minutes and just plain filled with great wisdom. Here’s a quote:

“There is a set of universal conditions that needs to hold true if you want to have product-market fit.”

I mean, that totally sounds like Yoda.

So, what’s the Product-Market Fit Pyramid? From foundation to top of pyramid:

  • Market
    • Target customers – who are we trying to build value for
    • Understand their Needs
  • Product
    • Value proposition – what needs we’re targeting, how we’re filling those needs and why we’re better than anyone else
    • Feature set – Functionality that conveys benefits
    • User experience – How they interact with product to get the benefits
To get towards Product-Market fit, you need to get those 5 layers right.

This is all foundational to the The Lean Product process. It’s about formulating and validating each layer, from foundation (target customer) to top (UX).

Now, why do products fail? You probably guessed it (or watched it), it’s because product owners tend to focus too much on the product layers. But the market layers are really what’s important to understand first.

We do this because we live in a solution space. We’re more interested in the solution than the problem.

“Solution is not what you’re seeking, young jedi. Seek the problem.”

Designing Product Experiments
How to Design Experiments for Your Product, by Richard Holmes

If you read this week’s intro, it won’t be a surprise that I will start pestering you with a bunch of stuff that relates to product experiments. Case in point: this gem.

Central question to this article is: are you learning anything valuable from your experiments? You might be running them, but they also might be just utterly useless (sorry ).

That’s why experiment design is so important. If the goal is to create new knowledge, then you need adopt the proper methodology (a scientific approach).

“Changing button colors may give you incremental improvements but if you’re not Google or you don’t have the resources to conduct hundreds of concurrent experiments at the same time, you’re probably better off focusing on a few distinct experiments which answer interesting questions and provide you with real, tangible insights that can drive long term improvements or achieve your product goals.”

So how to even conduct experiments? This is what the rest of the article explains and it’s well worth the time to read it as it will put you on a path to better experimenting.

Our Own Product Analytics Stack
As a product owner, you want to go deep into how your product is being found, adopted, engaged with and promoted.

For this, you need event data that informs you of your user’s journey and behaviours.

There are quite a lot of analytical SaaS tools out there (think Amplitude, MixPanel, HubSpot, etc.) that allows you to go deep. But you’re confined within their walled garden.

Say you want to link your experiments to user behaviours, this cannot be achieved within one SaaS tool. Or maybe you’d like to enforce a difference product-growth framework such as HEART. Or how about your OKRs, how to link them to your product analytics?

Being stuck within one single analytics SaaS tool, you don’t get that flexibility.

That’s why I like my modern analytical stack to be modular, flexible and opinionated :sunglasses Here’s what it looks like.

This stack accomplishes a few things:

  • It first defines user events so that we always have a single definition throughout your analytics (Event Configuration File)
  • It captures data from sources and moves it (Stitch and Segment) to a staging area in your data warehouse (Snowflake)
  • It transforms that data (dbt) directly in your data warehouse and creates entity tables consumable by multiple analytical tools.
You may like to stick with R or Python for custom analysis, do all your visualizations in Tableau, Power BI or Looker, or just plainly send your data to your favorite SaaS tool(s). Whatever the UI, you will always analyse the same single source of truth, with all the flexibility you require.

I’ll probably go deeper into this in the upcoming newsletters. But in the meanwhile, if you want more info, just send me a line at

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How can you leverage data to strategically grow your digital product? This newsletter’s mission is to share data analytics’ best practices and new ideas with product owners, so they can accelerate their development cycle.

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