This article was originally published on Mode’s blog by Emily Ritter, Marketing at Mode.
We’re excited to announce a new partnership with Mode, a collaborative analytics platform that tightly integrates SQL queries, Python notebooks, and reporting tools to make a profound impact on an entire organization’s ability to use data effectively. Now, you can use Mode to query your raw Heap data retroactively alongside data from your CRM, marketing automation tools, payments platforms, and more.
Analyze raw retroactive data
We recently shared an interactive guide of queries to help users make the most of Heap SQL. All of these queries are open sourced on Mode and can be used to explore user behavior, revenue, attribution, and more. Think of these queries as a starting point. Modify them as you go!
Using Mode’s charting tools, you can quickly build charts on top of these queries. Bring your most important metrics in one shareable report for regular monitoring. And with a direct connection to Redshift, anyone can update the data in one click (or on a schedule).
You can also build custom visualizations. Here’s an example of a path analysis showing the 20 most common user flows through a site. To apply this to your own Heap data, it’s as easy as Cloning the report and swapping in references to your own schema.
Using Mode Python Notebooks, we’ve also compiled a couple of pivot table examples that can be used to explore multi-touch attribution.
The possibilities are endless!
Curious to learn more about the many benefits of Heap SQL? Check out our Heap SQL Guide. We’ve teamed up with Mode to bring you an interactive guide detailing common queries you can run, metrics you can pull, and visualizations you can build using raw Heap data.
Ready to dive into your Heap SQL data now? Send us a note at firstname.lastname@example.org and we’ll put you in touch with someone who can help you get started.