Trunk Club, the Chicago-based retailer, mixes the best elements of e-commerce and personal shopping to serve more than 200,000 customers. The company, which was acquired by Nordstrom in 2014, has revolutionized personal shopping by enabling people to share clothing preferences via a mobile app or its website and then connecting them with a personal stylist.
To keep up with a growing customer base, Trunk Club used Segment to unify their data across the diverse toolsets each team uses, giving the analytics team more time to run powerful new models and analyses.
Trunk Club employs more than 500 stylists who build special relationships with their customers, taking inventory of their personal tastes, preferences and measurements. Stylists peruse the Trunk Club inventory with help from a machine-learning-powered recommendation engine and recommend items for their customers. Customers receive a trunk full of items and pay for whatever items they keep. Communication between stylists and clients takes place by phone, by email, and through the Trunk Club app.
The company was using a small number of software applications to review its data, but it didn’t have a consistent strategy to take advantage of the enormous trove of data generated by shopping and purchase behaviors, which could contribute insight for building personal clothing catalogues.
"As our inventory grew, we had hundreds of thousands of products that stylists could shop on behalf of their members," said Jason Block, one of Trunk Club’s senior front-end developers. "We wanted to be able to create programs to better manage the shopping process, like organizing a product catalogue that could recommend a set of clothes for particular members given their purchase history and sizes, depending on what’s in-stock. But that data wasn’t available to us."
We had some basic tools that allowed us to do rudimentary tracking of pages and we could raise some metrics to get bits of data for specific features. But on the whole, there wasn’t a useful data warehouse.
To track shopping and purchase behaviors, which could contribute insight for building personal clothing catalogues, Trunk Club needed to develop a customer data collection strategy.
The company was using a small number of software applications to review its data, including Kissmetrics for tracking a limited number of events, Bright Tag to track marketing events, and Google Analytics to collect pageviews. "But there was no consistency in how the events were captured, where they went, or whether our business intelligence team could do anything with them," Block said. "We had no direction or strategy when it came to client-side event tracking."
In addition, Block’s team couldn’t leverage all the data in its warehouse to develop new features based on Trunk Club’s stylists’ behaviors.
"We really just didn’t have any great insight on the whole universe of activity when it came to our web and mobile clients," Block said. "We had some basic tools that allowed us to do rudimentary tracking of pages and we could raise some metrics to get bits of data for specific features that we’ve implemented. But on the whole, there wasn’t a useful data warehouse."
Segment allows Trunk Club to track customer behavior across their mobile app and website. Routing that data to multiple tools that different teams rely on, Trunk Club turns that data into recommendations stylists use to select the right items for each individual customer.
Block’s team tried Segment and found that through its API, they could track data once across their mobile app and website, and easily route that data to multiple tools their entire team needed. Segment also loads all of the company’s customer data into Amazon Redshift, giving analysts and developers access to a single repository of all the company’s data with zero additional work. "The idea of creating a consistent developer experience for tracking data resonated with us," Block said. "There was nothing else like it."
The idea of creating a consistent developer experience resonated with us. There was nothing else like it.
Segment allows Trunk Club to track customer behavior and turn that into data-driven recommendations the stylists use select the right items for each individual customer.
"For example, we can a track a stylist-customer relationship so we can see what the stylist adds to the member’s trunk, and whether the member keeps those items," Block said. "All of that data is augmented by the events that we were capturing through Segment."
Segment has enabled Trunk Club to access data, answer questions, and make faster changes than ever before.
"Segment’s interface has allowed non-technical people to adjust our integration configurations without the need for any developers," Block said. "Almost 100 people, including product managers, engineers, and people working in business intelligence, design, finance and marketing are making decisions with data collected by Segment."
Trunk Club analysts and developers now use data to develop compelling new shopping features, Block explained.
"If we have an engineer working on a program, they can get the data they need from the data warehouse immediately," Block said. "Or if a product manager wants information about when customers usually press a particular button on the website for a particular service, the engineers can easily get that information so that changes can be made if necessary."
Segment has had a tremendous impact on the way we plan our business.
"Segment has had a tremendous impact on the way we plan our business," Block said. "It improves our workflow because it standardizes how we give information to our stylists and how we train them, how we structure teams, and how we set expectations for billing. We’ve become much more thoughtful about our processes. We can continue to adjust to the customers’ needs by seeing what they are doing on our sites. Segment has significantly affected and improved Trunk Club as a service."