D2C mattress retailer increases checkout rates 20% by moving off Google Analytics

This D2C mattress retailer is revolutionizing the $14 billion dollar mattress industry by developing the perfect sleep environment and delivering it directly to your door. The company has stuck to one core value as they’ve grown into a near-billion dollar business: provide the best customer experience possible.

As part of this mission, Scott Breitenother, VP of Data and Analytics, ensures that the company is poised for hypergrowth by optimizing the product experience and surfacing key data insights to the entire organization. Since the team started using Heap, they’ve increased their checkout conversion rate by 20% for key audience segments.

Today, the company uses Heap to grow every corner of their business, tackling everything from site optimizations and marketing attribution analysis to predictive modeling and beyond.

“Sorry, we don’t measure that.”

Prior to turning to Heap, the company had sparse and brittle event measurement in place. Growth efforts to date had been focused solely on increasing customer volume rather than optimizing the customer journey. In Scott’s words, “we were focusing on growing more oranges before squeezing more juice from our oranges.”

At first, the team turned to tools like Google Analytics, which helped monitor high-level session and pageview data. When attempting to understand more granular user engagement, the Data team quickly recognized that manually implementing analytics was too engineering resource-intensive, which made it impossible to get data and answer questions quickly. Time and time again, when another team member wanted to understand a particular user behavior, the Data team responded with, “sorry, we don’t measure that.” Without control over the analytics process, the team was stuck.

With sales volume growing by the day, it was imperative for the company to optimize their analytics process—more sales meant that small changes to the product could generate huge revenue gains. That’s when they turned to Heap.

Today, Heap provides the foundation for their analysis by collecting user behavior without any instrumentation. Thanks to Heap’s automatic data collection and retroactive analysis, the team can now answer questions as they’re asked, without having to worry about writing any analytics code.

In the words of Optimization Analyst Michelle Ballen words, “we used to find ourselves having to de-prioritize analytics or even put deployments entirely on hold in order to make sure analytics were set up prior to launch. With Heap, we make no sacrifices when it comes to the robustness of our data.”

Extending A/B test data in Heap

One of the main ways that the team continually moves the needle is by running A/B tests on every piece of site functionality and measuring test effectiveness in Heap. By integrating Heap and Optimizely data, they can see how all A/B and multivariate tests influence any user interaction

“For every test, we set a standard goal in Optimizely, but we always want to dive deeper to see how a test influences other activity beyond just our checkout conversion rate,” says Michelle Ballen.

Given that every event in Heap includes all information about the tests users were exposed to, the team can segment any activity by experiment variation to understand which versions influence a customer’s lifetime value rather than just their likelihood of completing a single goal.

Improving customer experience with immediate delivery

One of the team's most impactful A/B test experiments was around courier delivery, which lets customers in an increasing number of markets receive same-day mattress delivery fulfilled by bicycle messenger.

When the team evaluated their checkout funnel in Heap, they found that, given the option, over 80% of users choose courier delivery over standard UPS delivery. Historically, the team hadn’t mentioned their courier offering until checkout. But based on these observations, they wanted to see if mentioning courier earlier in the process would improve the customer experience.

When considering where best to feature the courier messaging, the team used Heap to identify areas of high engagement on the mattress product detail page. What they found was that engagement with shipping info in the mattress shop module was more than 5X greater for buyers compared to non-buyers.

They tested adjusting their Ready to Ship CTA to read Want It Today? to highlight their courier offering. The impact was significant: engagement with shipping info increased over 100% and conversion rate increased.

Analytics infrastructure that powers it all

At the company, the data team uses Heap Connect as the backbone of their analytics infrastructure. With retroactive data warehousing via Amazon Redshift, the data team can join raw Heap data with other datasets to perform complex analysis.

Like other eCommerce companies, their data resides in different tools. The team works with a variety of services to power their product, including Salesforce for customer records and email marketing data as well as Solidus for order transaction data. By combining the raw data from Heap and their other services in one database, the team can accomplish things that they never could before. This includes creating attribution models to understand the performance of different marketing channels and creating user personas based on behavioral data to personalize in-product experiences.

Empowering Everyone to Analyze Data

Even though Data team members are power users of the platform, Heap’s easy BI tool integration and point-and-click analysis features empowers all teams to answer questions immediately and independently.

The company capitalizes on Heap’s out-of-the-box integration with Looker to visualize key aggregate performance metrics that are used everyday by everyone in the company. With Heap and Looker, everyone can access and interpret critical company data around marketing effectiveness, sales volume, and conversion rate over time, broken down by any dimension.

For members of the team who want to explore more detailed data, Heap makes it easy for anyone to dive in. Customer Experience Representatives can take advantage of Heap’s list view to identify specific customers who experience issues or bugs in the product and proactively reach out to them. Front-end developers, who never had insight into the magnitude of customer-facing issues before, can now use Heap to help prioritize their workflow based on measuring how certain problems influence the bottom line.

Software as a Service

In the eyes of this company, one of Heap’s core differentiators is not part of the software, but rather the service provided by the Heap Customer Success team. Compared to other SaaS companies, the team at Heap doesn’t just answer questions, but actually serve as an extension of their Data team.

As Scott says, “Heap is the standard that I hold all vendors to and they never live up to it. I feel like we talk to Heap as a peer—someone who is operating at the same level of knowledge and sophistication as we are.”

Helping the World Sleep Well

Ultimately, Michelle puts the impact Heap has had on her team simply: “It’s really a no-brainer for us to use Heap at this point. It’s a game changer.” With their powerful new analytics infrastructure and months worth of insights, the team is now expanding overseas, using Heap to give everyone around the world a better night’s sleep.