Policygenius is the one-stop platform where customers can compare and buy insurance policies from top insurance carriers and get unbiased expert advice. They’re a deeply technical company that integrates with major insurance providers and have helped millions of people find insurance.
“Narrator’s our first stop for any ad-hoc exploratory analysis.”
Daniel Gremmell
Traditional data tools are inflexible
Asking new data questions requires too much work
As an insurance marketplace, data is fundamental to Policygenius. Their data team manages a large, well-architected modern data stack that powers decision making at the company.
Even with a well-built stack it’s still a lot of work to keep up with the variety of stakeholder requests. If something wasn’t built in a dashboard, it wasn’t available to users not comfortable with SQL. Unblocking those folks took up a lot of the data team’s time.
“In the past when certain questions were asked, we'd go through the time consuming process of creating a ticket for the data team, diving into the question, building an analysis from scratch, and then sending back the result”, says Daniel Gremmell, Head of Data at Policygenius.
Policygenius uses Narrator to quickly explore data, debug their infrastructure, and provide a quick way for stakeholders to answer their own questions.
Daniel Gremmell
"Narrator really lowers the effort required to look at data in different ways, across different segments to find things you may not have thought of looking at before.”
Where Narrator Fits
How Narrator stacks up against BI tools, CDPs, and data modeling tools
“We use Narrator both in place of dbt and as our ad-hoc exploratory tool.”
Narrator allows the Policygenius data team to explore any data in their warehouse, in minutes. This fills a critical gap between their BI tools, which are limited in scope, and direct SQL queries, which take a lot of time to build and debug.
More flexible than BI Tools
“What most BI tools lack is flexibility. Narrator is great as your ad-hoc exploratory layer, allowing you to very quickly spin up datasets, aggregations, and visualizations folding in as many features as you need. This is a process that without Narrator takes a ton of analyst development time and multiple other tools to unlock. Narrator really lowers the bar and effort required to look at data in different ways and across different segments that you may not have thought of looking at before.”, says Daniel.
Daniel explains: “Before Narrator, we didn’t have a solution that gave non-SQL users the ability to generate granular datasets or evaluate hunches on top of the source of truth. We love tools like Tableau for presenting data developed, built, and sanctioned by our team, but they’re not primarily designed for dynamic iteration or much ad-hoc analysis.”
More comprehensive than Customer Data Platforms
“The major benefit has been in comparison to product analytics tools and CDPs. Those tools are user friendly but they’re limited to only online events. I’ve found Narrator to be way more powerful as it includes everything the customer touches in every tool in your technology stack. And it scales more naturally over time because it’s powered by your internal data warehouse instead of data that lives outside of your control.”
Data transformation built in
Narrator is also a full-fledged transformation layer that can prepare any data for analysis, export, or visualization. Daniel sums up where Narrator fits in their stack this way: “We use Narrator both in place of dbt and as our ad-hoc exploratory tool.”