FIGS combines Heap and Shopify to increase its conversion rates

About FIGS:

Since the COVID-19 outbreak, online medical apparel retailer FIGS business has seen a boom in business and demand. To try to make the best out of a harrowing situation, they’ve responded with donations and care packages for healthcare professionals. They’re also using Heap + Shopify to optimize A/B testing and conversions. We spoke to Brian Kim, Senior Director of Data Science of FIGS, about their experience.

Figs, Brian Kim

Brian Kim, Senior Director of Data Science

“We run a really efficient Data Team, so our approach to analytics is to keep things as simple as possible. This means that we use more modern, fully-managed services where we can, and we keep our tech stack pretty simple. We don’t try to reinvent the wheel unless it’s core to our business.”

Heap has been a key part of this philosophy. Because of its minimal overhead, which doesn’t require a ton of engineering resources, it really fits into the paradigm we have with minimal devops and data engineering effort involved.

- Brian Kim, Senior Director of Data Science

“With most other analytics platforms, you need to really have a dedicated engineer to make sure events are tagged correctly. With Heap, this type of work can be offloaded to non-technical folks in a way that isn’t really possible with anything else. This allows us to work together with the Product team in managing our events.”

How they’re using Heap + Shopify:

“The integration was simple because the back-end events go straight into Heap from Shopify. This means data such as order ID, customer ID, and other order metadata pass from Shopify to Heap and we don’t need to tag any of it. And I can trust the accuracy of that data before sending it into our data warehouse.”

“We’re using Heap + Shopify to measure how conversion rate differs across different shopper cohorts; for example, based on different acquisition channels and on-site behavior such as viewing certain pages and interacting with on-site features. What we’ve been doing is mostly tracking conversion rates from specific pages and site features to purchase. Then we’ll try to segment across different marketing channels.”

“We also use Heap to measure the long-term impact of A/B testing. In A/B testing tools, the reporting is short-term and based on a single goal; they let you know the “winner” of a certain test, but it stops there. With Heap, we can understand the longer-term impact of A/B tests.”

With Shopify, A/B testing, and Heap data all in one place, we can evaluate the impact of A/B tests on metrics such as repeat purchase rate, average order value, customer lifetime value, and conversion rate.

- Brain Kim, Senior Director of Data Science

“We can also join the testing data with the rest of our customer data set in a way we can’t do within our A/B testing platform by itself. It’s been interesting to use Heap to track our A/B testing.”

“One key insight we’ve seen is that sometimes the new variant will underperform initially and then do better over time as customers get used to the new interface. It’s changed the way we look at A/B tests.”

“We use Heap + Shopify to connect order data from Shopify to onsite behavior in Heap. This allows us to understand how different shopper behaviors, demographics, and marketing channels correlate with conversion, average order value, repeat purchase rate, and more.”


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