Gilt uses analytics to pioneer a new way to shop for high-end luxury goods

Gilt Groupe started as an invitation-only website devoted to selling luxury women's goods at insider prices that were once available only in exclusive New York trunk sales. Today, it is one of the fastest-growing online retailers selling a broad range of upscale women's fashion and accessories, men's apparel and lifestyle, home, children, travel and gourmet food items through flash sales. SAS® Analytics have helped drive membership engagement by allowing the firm to rapidly analyze data to better understand what its customers want.

Customer Success Video

Check out this video to learn more about Gilt Groupe and its successes with SAS.

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Customer Viewpoint
You have questions; our customers have answers. Check out this video Q&A.

Tamara Gruzbarg
Senior Director of Analytics and Research

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A new sale starts every day, usually at noon. It's first-come, first-served, so if you want the best pick of the offerings, you'd better act fast. "Our audience is very engaged and looking forward to discovering what is new every day, and they make repeat purchases at a high rate," explains Tamara Gruzbarg, Senior Director of Analytics and Research.

Gilt paints portraits of its online customers and delights them with inspired selections
The company realized early on that it needed to intimately understand the customers drawn to the site in order to understand what merchandise would appeal to these customers. Gruzbarg shares the story of a head merchandiser who had worked at a high-end brick and mortar retailer. "She came to me and said, 'It was much easier when I worked for the (designer) boutique because I knew all of my customers when they came in. I knew their size. I knew their needs. I knew where and when and how they will be wearing a certain outfit."' So Gilt set out to know online customers as if they were meeting them face to face.

The data was there. There was demographic data gathered when new members registered, browsing and shopping history gathered from the website, mobile apps and the transaction platform, plus marketing history (such as acquisition source, referral connections and campaign response). Gilt had what it needed to answer questions about what brought customers to the site, and what brands they viewed but didn't purchase. Data alone does not equal customer insight. "From the analytics perspective, the amount of information that is theoretically available to us is unprecedented," Gruzbarg says. "But that doesn't mean it is readily available."

Gilt Groupe chose SAS because the solution could access and combine information from any number of sources and help Gilt quickly produce reports relevant to marketing, operating, finance and merchandising. The solution enables business users to manipulate, manage, store, analyze, visualize and report on data – all from a single environment.

Gilt also wanted the option to move to more sophisticated analytics – such as predictive modeling and segmentation – with just one vendor. "We needed a solution that would allow us to turn information into knowledge and then do in-depth analysis. SAS enabled us to do all that," Gruzbarg says.

With basic information more readily available and easy for business users to manipulate, Gruzbarg could turn her attention to more complex analytic questions such as customizing marketing messages, finding the best customers for cross-sell promotions and helping Gilt's partners understand their shoppers. "We started with straightforward analysis and can now do complex segmentation and clustering."

The right message to the right customer
Gilt Groupe members get an 11:45 a.m. email previewing the daily sale: "When we have more than 30 sales starting, obviously we are not going to fit all of them on one email," Gruzbarg says. Using SAS, the company took all its data sources and created an algorithm that customizes the emails. The effort led to:

• Increased engagement from customers browsing in new merchandise categories where they had not purchased before.
• A 100 percent lift in conversion for women who were likely (top 30 percent) to shop the men's site (as identified by predictive model) but had not yet purchased men's merchandise.
• A significant positive impact on new member conversion rates. This is a measure of customers who join but haven't purchased.

More effective cross-shopping promotions
"With all of these different businesses and verticals within Gilt, we want to make sure that we cross-promote in the most effective and efficient way," Gruzbarg says. When it launched its Home division, Gilt used SAS to build a predictive model to identify the key characteristics of women shoppers who are likely to shop Home as well. "Once we identified the target audience, we sent an email with a specific offer – in this case, 10 percent off their order from Gilt Home. We increased conversion on the Home tab from this target audience by almost 100 percent and saw an immediate and very positive incremental return on investment as well."

Deeper customer insights for Gilt's brand partners
Brand partners don't always know much about their most loyal customers. Gilt shares the knowledge it gains from using SAS with partners. "One of our value propositions is that we can provide a lot of information and insight about the people who are shopping their brands," Gruzbarg says. "What else are these customers interested in? Do these tend to be our more loyal customers, or less loyal? What other brands are they interested in?

"This kind of information is very interesting to retail brand partners, because we have the luxury of tracking our customers and understanding important aspects of their lifestyle and life cycle, due to the registration aspect of our site."

Next steps with SAS®
Gruzbarg is looking to use SAS next to help with pricing decisions. "That's very critical to our business," she says. In addition, she wants to incorporate more forecasting now that the company has a data track record.

Gruzbarg is happy, though, to have been able to start with basic analytics. "It is never too early to start with analytics, even if you don't have full-blown capabilities right away," said Gruzbarg. "Simple segmentation based on one or two key variables, implemented at the right time, could go a long way in helping to move the business forward. Those initial insights can then be incorporated into future comprehensive strategies."

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.

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