Product Analytics Newsletter
Edition #19
September 2nd, 2019

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Good morning product owners!

Your product analytics journeys usually goes through a walled garden provided by one of the key analytics SaaS providers: Google Analytics, Amplitude, Mixpanel, etc. But that might end up not being enough, and you could take that extra step to own your data with a service such as Segment. That gives you control of your data, while also giving you flexibility to try out multiple analytics SaaS providers.

That said, I love and use some of those tools. And they are definitely pioneers in the product analytics spheres. That’s why I am excited by the features they come up with (see the Amplitude’s Engage story below) as well as the content they share (see the Summary vs Growth KPIs story).

That story on KPIs is rich and is probably the achile heel for analytics SaaS providers. KPIs are so unique to each product that it’s hard to come up with cookie-cutter solutions for them. Coming up with KPIs might be more witchcraft than science and so I thought the podcast I’m sharing below on Jobs To Be Done might help you think about what struggles your product is solving and how to measure that it’s delivering on that promise.

Finally, I’m sharing my understanding of the building blocks from user behaviours towards business KPIs. You’ll appreciate my lack of talent in design, but I also hope that it will give some perspective on how all that data bubbles up towards building KPIs.

Hope you enjoy this edition’s stories and I look forward to your comments on those.

With that, on with the 19th edition of the Product Analytics newsletter.

Olivier
@olivierdupuis

PRODUCT NEWS
Amplitude Is Taking On The « Acting » Part Of Analytics
Amplitude Engage sure reminds me of Segment Personas. I think product owners have more to win by owning their data with Segment and using Personas, but it’s definitely a nice addition if you are confortable staying within the Amplitude ecosystem.

That raises a lot of questions about product categorization in analytics as the lines blur between Customer Data Platforms, analytical SaaS providers (or digital analytics softwares), CRMs even, etc. That is definitely a topic for a future blog post though.

Amplitude Engage

STRATEGY
JTBD and KPIs
You might be familiar with the Jobs To Be Done idea, but maybe you haven’t taken the time to dig deeper into it. I hadn’t. If you’re like me, where JTBD is not too much of foreign territory, but you lack the foundations to find it useful, this is a great podcast.

While listening to it, I was thinking a lot about how if JBTD are the key reasons a product was hired to tackle a user’s struggle, than the leap wasn’t that far to use it to define your product’s KPI. Again, maybe a topic for a future blog post 🙂

A Jobs To Be Done Masterclass with Andrew Glaser and Bob Moesta“, by The Disruptive Voice

BEST PRACTICES
Summary and Growth KPIs

“The most successful companies set themselves apart by how sophisticated they are in defining their KPIs. They assess themselves at multiple levels, using Summary KPIs for a snapshot of digital health, in addition to Growth KPIs for a leading indication of long-term product success.”

That’s a great contribution by Mixpanel on how to think about product’s KPIs. I really like that separation between KPIs as there is always that tension between the KPIs that provide an overview of a product’s success, but also KPIs that tackle the current challenge in your growth’s journey (my definition might differ a bit from their for that last one though). You’ll notice how I’ve shamelessly stolen that idea below

Identifying Growth KPIs that are leading indicators of product success“, by Jeff Beckham

BEHIND THE SCENES
From User Behaviours to Business KPIs

What is product analytics and how does it relate to metrics, KPIs, user events, user journeys, business performance, etc., etc.? 🤯 There are so many angles to data-driven product development that I thought I would put together a fairly ugly graph that structures what I think constitutes the building blocks of a product analytic’s strategy.

Here’s a quick definition and example for each layer:

  • User Event – That’s the raw actions taken by a user on a product, such as submitting a newsletter subscription form.
  • User Journey – That’s a variation from the Pirate Metrics that I think Mixpanel came up with (again stea… ummm… borrowing). Each step provides an idea of the health of that user’s relationship with your product. For example, if a user hasn’t returned to your product in more than 60 days, he could be classified as “Dormant” in Active Usage.
  • Product Metric – Those metrics are aggregations of those journeys. For example, how many users logged in today, how many published a post, what was their session’s length in average, etc.
  • Product KPI – I like that idea of splitting KPIs between those that provides insight into overall health of your product (such as the ratio of newly registered users that log in more than 5 times during their first week), and those that relates to your growth stage and the initiatives your put in place to push that growth (for example, the number of users who have shared a free meal with their friends after a promotion you sent out).
  • Business KPI – Now, that’s where the line can get confusing. Sometimes, and for most startups that’s how it is, the product is the business. But for others, they have multiple products. I like to keep it distinct, as you might have other parallel products (such as a newsletter or even your business’ Instagram account), that do not generate revenue, but that could grow awareness of your business.
What do you think? Does that equate to your own interpretation of how your analytics strategy is structured? I’d love to hear your thoughts on this.

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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 incrementally and intelligently improve their product.

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