Clothing Chain Bon Ton Taps Celect To Predict Shopper’s Choices
The partnership of the two New England brands comes as the MIT incubated retail analytics company raises $5.15 million.
Shopper analytics company Celect has raised $5.15 million to support the release of a retail inventory software program that promises to help store managers determine “what to put where” to drive traffic and sales.
The Boston-based company was founded by two MIT professors, Vivek Farias and Devavrat Shah, and relies on machine learning programs to help retailers better understand their customers’ buying patterns.
This technology, dubbed the Celect Choice Engine, enables merchandisers, retail planners and inventory analysts to know, not only what products they should be stocking more of, but also where it should be placed to inspire more purchases.
The company’s software is currently being tested in 10 outlets belonging to fellow New Englander, Bon-Ton Stores, which runs 270 locations across the US.
The Right Choice
“The Celect Optimization Platform is the core product, and is powered by the Celect Choice Engine,” says Celect CEO, John Andrews. “The two MIT professors [who founded Celect] have had a line of research for the past decade or so around the concept of Customer Choice Modeling.”
That concept is plainly simple: what a customer purchases is both constrained and influenced by what they’re offered, Andrews says.
“For example, if you choose the blue jacket when you are offered the blue, the red, and the white jackets, you prefer the blue jacket to red or white,” he says. “Celect learns from every single customer transaction, and uses this information across all customers and all transactions to learn a choice model over at scale and accurately that can then be used to help retailers optimize over a very large number of options in near real-time.”
One Size Fits All Retailers
Celect’s platform is geared towards all shapes and sizes of retailers and essentially all retail segments, Andrews says. The company works with some of the largest retail chains in the US, and it has also worked with a small boutique with only four retail storefronts.
The primary benefit of the Celect is to help customers understand how their customers choose at a much more precise and granular level, Andrews says.
“With our scientific breakthrough in customer choice modeling, we are able to give retailers forward-looking insights in to how their customers will react to an assortment of products, which products they are more likely to buy,” he says. “With this information, retailers can deliver optimized assortments in each store based on the foot traffic of customers who shop at that store, or ensure they are always presenting the right assortment of products to each individual customer online with each and every click.”
The results from doing this right appear clear — Andrews claims that Celect has seen improvements of in-store revenue of up to 7 percent and online increases in revenue per unique visitor of up to 20 percent.
Celect’s timing certainly appears right. The connected issues of online-to-offline attribution, the need for clearer success metrics, and the state of data quality is one of the primary areas of focus of analytics companies, particularly when it comes to the way location influences store-visitation and in-store sales conversions. Rather than offering ways of looking back to see if a campaign “worked,” companies working in the retail/tech space are increasingly being asked to predict outcomes and help ensure results.
Investors are paying close attention. Proceeds from Celect’s funding will go toward adding members to its support teams working with those early retail customers who are trying out the platform. In Celect’s case, the company is being backed by August Capital with additional investment from Activant Capital.
“All areas of the team will be expanded, including engineering, sales, marketing, and customer success teams,” Andrews says.