Thinx uses Heap to drive growth and retention

Who is Thinx?

Founded in 2014, Thinx’s mission is to break the taboo around menstruation and rethink how people with periods deal with their period. Their signature product is “period-proof” underwear that can absorb up to two tampons worth of flow while keeping the wearer dry and clean. They offer a variety of styles and absorption levels including absorbent athletic wear. They’ve since launched two additional brands: Thinx (BTWN) for those just starting their period and Speax for those dealing with bladder leakage.

Humble beginnings

Thinx has been using Heap since 2016. When they first came to us, they were a lean organization beginning to scale at a tremendous rate. Their growth team was looking for a tool that could help them scale their user acquisition efforts and identify areas of the site that could use UX improvement. They used a free, legacy analytics tool and had trouble keeping up to date with all the site changes and experience updates they were making. Their engineering team had just started looking for a data warehouse and BI tool to support advanced reporting and analysis.

Thinx chose Heap as their product analytics tool because the low technical overhead afforded by Autocapture would empower them to be more data-driven while reducing strain on engineering resources. Additionally, Heap’s automated ETL meant that their more advanced data aspirations would be supported as well. Three years of explosive growth later (for Heap and for Thinx), Heap sits at the center of the data-driven culture Thinx has created.

We stopped by Thinx headquarters in New York City and spoke with members of three different teams about how they use Heap in their day-to-day.

Alexandra is responsible for joining data sources, centralizing them into one location, reporting, and performing complex analysis for all three Thinx brands. Heap’s approach to data collection and centralization enables her to deliver reporting and insight without the shortcomings and difficulties presented by legacy analytics tools. With other tools, an executive request for a report on something new would be met with a timeline for implementation and collection – and a report would follow several weeks after. Heap enables Alexandra to provide a report within a day and with data that looks back since Heap was first installed on Thinx. In juggling the dual responsibilities of reporting and analysis, Alexandra is able to fulfill reporting requests in minutes because Heap provides a complete dataset of on-site behavior. This affords her more time to analyze user cohorts and generate meaningful insights that drive growth and revenue for the business.

One way that Thinx utilizes product data in their data warehouse is with their BI tool, Looker. Heap’s approach to data downstream makes this process a lot easier. With Heap, Alexandra spends less time managing and moving data, and more time supporting the business and gleaning new insights. For her other data sources, Alexandra has to manage and debug ETL code to ensure that the data she needs is available, especially as tables and columns are added and adjusted. Heap’s automated ETL handles changes in schema automatically. This means her work is simplified to a single click, and the data she wants becomes available in Looker. Additionally, the standardized schema provided by Heap allows behavioral data from the website as well as revenue data from Shopify to be easily modeled within Looker. Heap helps fuel Thinx’s growth by accelerating how quickly Alexandra performs real analysis.

Dani is responsible for Thinx’s brand ambassador program. She relies on Heap to provide the data she needs to evaluate the performance of these various ambassadors, and ultimately, to determine what payouts each ambassador should receive.

Before Heap, Dani relied on a system of spreadsheets and limited information from discount code referrers. The impact of third-party discount code aggregators made it impossible for her to accurately measure performance. With Heap, Dani has a platform where she can access the data she needs at any level of granularity. This means she can see how many visits individual ambassadors are generating as well as which ambassador discount codes are being used. Heap gives her the confidence she needs to provide fair payouts to Thinx’s partners. Additionally, different ambassadors are instructed to promote specific styles or colors in particular campaigns. Heap enables Dani to drill down to that level of granularity and evaluate the effectiveness of specific campaigns. This allows her to quickly improve and adjust brand ambassador actions, meaning more effective campaigns and increased sales.

As a member of the UX team, Elise is responsible for providing the information the product team uses to optimize the digital experience across all of Thinx’s products. Qualitatively, this takes the form of surveys and focus groups to discuss and evaluate decisions. Quantitatively, product analytics with Heap takes center stage.

The product team is constantly iterating in order to build the optimal experience for all their digital products. With Heap automatically tracking behavior, Elise can easily evaluate the impact of these changes on conversion across the site without relying on developers to maintain tracking code. If there are fluctuations, either positive or negative, Elise breaks out her reports by device information, marketing campaigns, demographic information, and other user actions. This allows her to pinpoint the reason for the change, enabling engineers and designers to quickly make any necessary adjustments to course-correct or apply learnings to future design and optimization efforts.

A couple of months back, the Thinx team launched a quiz that would help users evaluate their period and provide product recommendations tailored to their needs. Using Heap, Elise identified areas to refine the quiz user experience. These refinements ultimately resulted in a 5X increase in conversion rate from the original version. Because the concept of period-proof panties is so new to most people, an improvement that increases the number of people educated on how the product works results in a large impact on the retention of new customers. The product insights Elise gleaned from Heap have resulted in a 90% retention rate with the product quiz experience.

Conclusion

From self-serve product analytics to working with user data downstream in their data warehouse, Heap sits at the center of Thinx’s data strategy. Thinx uses Heap to provide a trustworthy and complete dataset that can be used to make decisions quickly and confidently. Autocapture and retroactivity are so ingrained within Thinx’s culture that the expectation is for data to always be available when questions arise. With the agility that Heap provides, Thinx understands how to deliver the ideal customer experience quickly, ultimately building a loyal customer base and accelerating their growth as a company.