Product Analytics Newsletter
Edition #18
August 19, 2019

(Image Source: Martech Today)

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Good morning product owners!

Sloooowly crawling (or swimming) back to normal working life as I spent the last 2 weeks exploring pools with my kids. Can’t say I found anything useful at the bottom of the waters, but I thoroughly enjoyed it 🏖

Hope you’re also all enjoying your Summer and I’m looking forward to all the exciting conversations that get started from those emails.

On that, how about replying to this one and telling me what’s currently puzzling you or getting you excited in the product analytics world. I’d love to hear!

With that, on with the 18th edition of the Product Analytics newsletter.


Difference Between Customer and Product Analytics
Now I’m a fan of the Drill to Detail podcast by Mark Rittman. I’ve had the chance to speak with Mark a few times and he’s just such a curious and very generous person and that transpires in each episode.

That “Conversion Rate Optimization and Other CRAP” episode with Bhav Patel catched my attention as it briefly touched on product analytics.

I love Patel’s take on the difference between customer and product analytics. How customer analytics is pretty well defined with all the steps and well-known metrics surrounding the customer’s journey (acquisition, activation, retention, etc.). But that product analytics is still a somewhat new field where the practices of measuring a product’s performance might not be as well defined.

Time-Based Analysis of User Behaviour
Now that one was shared to me by Pascal Laliberté. It’s a much too brief take on usage frequency analysis by Ryan Singer, who is the head of product strategy at basecamp.

The problem he’s tackling is the following:

“Analytics apps don’t tell you much about usage behavior. You might be able to see how many users performed an event, or how many times they did it. But none of the analytics packages out there are good at showing you how often people do things. Are they using to-dos once a week? Every day? Only signing into the app once a month but happily paying for years?”

The types of analysis he comes up with and the associated visualizations are worth the few minutes you’ll spend there.

Product Analytics for Newsletters

A little bit of shameless self-promotion to stroke my ego . I just published a post on how we implement a data strategy and infrastructure for newsletters at Lantrns Analytics. Newsletters and simple products but core to a lot of businesses and it’s worthwhile to make data-informed decisions to continuously improve them.

If that topics is of interest, I’d really love to learn how you currently capture your newsletter’s data, measure performance and report results to stakeholders.

Owning Your Data

“At a young company, you probably don’t have all the analytics pipes setup. You should store your own data even at the very start. In this post I’ll explain why and the default way to get it done.”
Why You Must Store Your Own Analytics Data, by Ivan Kirigin

It’s not always straightforward why should own your data right from the start. The main point being formulated is that if you can’t answer (or easily answer) questions via traditional digital analytics tools such as Google Analytics, Amplitude or Mixpanel, then you probably won’t ask them. This forces you into a frame of mind that is delimited by their walled garden.

To fully explore your product’s data, you need to go beyond what those tools offer. This blog post is short, but I like the simple ideas it conveys. You should note though that it is a bit outdated when it talks about Segment, as sending your data to a data warehouse is now so simple and cheap.

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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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