Sharing Insights With Jupyter Voilà + Map Of UX Tools + Calculating LFTV (PAN #14)

Product Analytics Newsletter
Edition #14
July 8, 2019

(Image Source: Jupyter.org)

Good morning product owners!

I just want to do a quick shout out to the fine folks at Fishtown Analytics for dbt’s 3 years of existence. Tristan (founder and CEO) has written a post that sums up their journey and the road ahead.

Not only is dbt such a great addition to analytical stacks, but the community that has been built around it is wonderful! I know some of you are already part of it, but if you aren’t and want to go deeper into data architectures, their Slack community is filled with bright, generous and fun people.

We at Lantrns Analytics are also super excited to be part of dbt’s ecosystem, and it’s really an honour to share that place with companies and individuals we are learning from every day and that we respect so much.

Here’s to the next 3 years of dbt 🍾

Enough with the delirium provoked by heat stroke and let’s just move on with the 14th edition of the Product Analytics newsletter.

Olivier
@olivierdupuis

PRODUCT NEWS
Jupyter Voilà

The BI space just got a little more crowded.

This news is in the category of ad-hoc analytics in my opinion. Once you have all that analytical stack in place and you want to go deeper than what the metrics tells you, then you take those coding skills of yours and explore the data.

But how do you share the results of that exploration? How do you replicate it? How do you get other analysts from your team to contribute and build a discussion around the data?

This is where Jupyter Voilà fits in it seems. It’s the same space as R Shiny, or just opening Tableau and exploring the data.

This BI product clearly targets those who are already sold to interactive notebooks, but it might start getting bigger when teams will want to start improving collaboration for the exploration process.

STRATEGY
Product Management Stack

To manage a product is to juggle many balls at once. At the heart of it is to improve user’s experience. That in itself is a complex task. And around complex tasks tends to gravitate a lot of tools.

You’ve probably seen mappings of tools in spaces such as marketing technologies (MarTech) or education technologies (EdTech), but here we now have a mapping of all tools in UX. Not only is listing those valuable in itself, but this mapping goes one step further by grouping tools by sets of features and how they overlap those categories.

For context and the full map, read the report here:

“The 2019 UX Research Tools Map“, by Erin May

BEST PRACTICES
Calculating Subscriber’s Lifetime Value

If you’re managing a subscription-based product, chances are you are keeping track (or plan on keeping track) of your user’s lifetime value. But you might lack the knowledge and/or tools to effectively calculate it.

If that’s the case, you might find the following very useful. The author shares his approach to calculating LFTV, as well as a spreadsheet to facilitate calculation.

You can now that off your todo list. You’re welcome

“A Spreadsheet for Calculating Subscription Lifetime Value”, by Eric Stromberg

BEHIND THE SCENES
Mapping forces, dynamics and outcomes of newsletters

In last week’s edition of the newsletter, I shared the state of my analytical stack’s ETL. I finished off by saying that we’d now start digging into the data, and that’s partly right

As we’ve emphasized in our Guide to Product Analytics, the goal is not to generate tons of data, but only concentrate on a few metrics that are meaningful to your product’s growth.

First step is to map our a product’s ecosystem. Here’s what we believe is the core forces, dynamics and outcomes of our newsletter.

The circles represents the entities within the ecosystem
The inner attributes are the forces
The squares represents the dynamics generated from the relationship between forces
The listed items underneath the dynamics are examples of the dynamic’s outcomes

It’s far from a perfect nor complete model of what this newsletter’s ecosystem is, but it does provide basis on which to orient this product’s analytics.

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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.