Sur La Table uses Heap to increase product page views and overall conversion rate

Since its inception over 40 years ago, Sur La Table has grown into one of the largest cookware retailers in the world by offering an unsurpassed selection of exclusive and premium-quality products and cooking classes. Over the last decade, the brand has built on its success with a strong eCommerce strategy around both its products and its classes and is ranked number 245 on the Internet Retailer 2017 Top 500.

Sur La Table’s success has been driven by creating an amazing customer experience. As part of that mission, the Company has built a culture of conversion rate optimization and rapid iteration on the eCommerce team to build the best customer experience possible. Heap has enabled the team to become more iterative, flexible, and nimble in its approach to improving the customer experience. We spoke to Walter Euyang, eCommerce and Marketing AnalystChadwick Radaz, Merchandiser; and Kevin Tsao, Director of eCommerce about their experience using Heap.

Before Heap

When Walter joined Sur La Table, their eCommerce teams were using a combination of Adobe Analytics and Google Analytics. Their current systems did a good job of delivering high-level metrics, but they had no ability to dig into the behavioral questions that really mattered.

We couldn’t answer our primary business questions: What’s driving purchase behavior? How can we better engage our customers? How can we improve our purchase funnel? All we could see was how many orders we had that day.

- Walter Euyang, Su La Table

Adobe Analytics proved to be far too inflexible and cumbersome to solve this issue. Adobe wasn’t built from the ground-up to support the constant iteration and testing they were doing on the Sur La Table website. Every time they shipped new landing page changes or changes to the purchase funnel, they needed to wait for the developer team to implement additional tags in Adobe Analytics. Walter and his team began searching for an analytics solution to complement Adobe that would allow them to move faster.

Their criteria were straightforward: they needed an analytics tool that allowed business owners to focus on day-to-day operations rather than being bottlenecked on developer resources. Heap fit the bill. “Our developers sat with the Heap solutions team and got it right away. It was a totally different approach.” By tracking user behavior automatically, Heap enabled Walter and the eCommerce team to move quickly while the development team could concentrate on other initiatives.

Our developers sat with the Heap solutions team and got it right away. It was a totally different approach.

- Walter Euyang, Sur La Table

Wins with Heap

The digital marketing, eCommerce analytics, and merchandising teams now use Heap to make quick, real-time decisions. “Now that we have Heap, we have visibility into everything,” says Chadwick. “We’re making constant changes to our merchandising slots, content, design–and with Heap we can keep up.”

Heap’s flexible analysis modules and user-friendly virtualization layer have enabled a culture of exploratory, ad-hoc analysis. “We can slice our funnels at the category level, SKU level, page level, and more. We’re regularly comparing checkout flows and different categories of products. We’re even able to ask complex questions about how users who book our culinary classes interact with our product offerings.” Sur La Table also uses Heap dashboards, which are “perfect for us to share on TV screens around the office. Dashboards have brought forth a lot more awareness around how our website is performing.”

One of the early insights they found via Heap’s dynamic user cohorting was that the more products someone views, the more likely they are to convert and the higher the revenue per visitor. This led to a follow-up question: how should we optimize our email newsletter to drive more product page views, and consequently more revenue? Specifically, did it make more sense to drive people to category pages or directly to specific product pages via the email newsletter?

The team at Sur La Table found that driving people to category pages led to a 12% increase in total views of product pages as well as a 6% increase overall in conversion rate.

Another big win was around cross-product merchandising. The prior insight about product page views led the team to ask if it made sense to more prominently display similar or complementary products on product pages. When they tested this change, the results were huge: the improved cross merchandising on the product page for one of their most popular products resulted in a large lift in co-purchase and average order value.

Merchandising successes on Black Friday

The Sur La Table team used Heap for lots of real-time optimization leading up to and on Black Friday. They had a marketing campaign for a special insider program, and used Heap to see how many people were joining, and how the insider segment was behaving. They found interesting insights about how the insider segment performed after acquisition vs people who didn’t join the insider program, and used this to make tweaks to further personalize the insider experience over time.

On the day of Black Friday itself, Chadwick and the merchandising team kept a close watch over which products were converting best. They had setup detailed purchase funnels for each of their highest-viewed products prior to Black Friday, and monitored these closely throughout the day. They were able to optimize in real-time and push the highest and best-performing products to prominent places on the website. Because Heap was automatically capturing everything happening on, and they could ask any question of that data in real-time, they didn’t have to wait until after Black Friday was over to act on these results.

Overall, Heap has helped Sur la Table build a culture of iterative, data-driven decision making with a focus on customer experience. “Heap has empowered us to make decisions based on data around the UX and design of our site in ways that we were never able to before. We have such granular info about our users that we never had before. We are able to just do so much more and provide really strong recommendations with high confidence.”


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