We are excited to walk through a Looker Block developed by our founder, Aron Clymer: Dynamic Cohort Analysis. Looker Blocks are building blocks — pre-built pieces of code that you can leverage to accelerate your analytics in Looker.

Looker Block Description:

Anyone doing a deep dive analysis on customer behavior will want to easily look at a cohort and see what kinds of interesting insights can be discovered about that cohort. For instance, imagine a simple but powerful question like “Of the customers that purchased Product A, what other products did they purchase?” This insight can help sales target upsell or cross-sell opportunities.

Why This Is Important:

Looker is an amazing data platform, but because it’s generic it doesn’t come prepackaged with advanced analytical patterns. So, we developed this Looker block to give end users a powerful pattern for dynamic cohort analysis.

In the world of SQL, this kind of question requires a sub-query to define the cohort (customers who purchased product A) and a main query to answer a question (what other products did they purchase). In the spirit of creating a friction-free, self-service analytics environment, the question is: how can we give end users the capability of dynamically creating ad-hoc cohorts at run-time and then asking other questions about the behavior of those cohorts? All without having to develop any LookML or write custom queries!

At a Glance:


Looker block: Dynamic cohort analysis

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