Data and Analytics
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What's the point of a best-practices SEO program, finely tuned e-mail marketing strategy and active social media presence if your customers can't find what they want when they get to your site? That's the question BloomReach CEO Raj De Datta asks his 150 or so clients, who range from luxury department store Neiman Marcus to hip e-tailer ModCloth.
"Right now it's like walking into Target," De Datta says of most ecommerce sites. "I'm looking for toys. Someone else is looking for a fleece jacket. But we both see the same store, even though we're here for a very different reason."
From a typical ecommerce homepage, consumers can either use the search function or make their way through several levels of menus, hoping to find a specific product. But with BloomReach's SNAP software, buyers arrive at the store and see only the products they want, since the software has anonymously figured out their intents and preferences based on prior visits to the site, language they use, links clicked on the site, commonalities of the content they consume on the site, current location and what network they're on--no login or password required.
In effect, BloomReach's enterprise-level software--which costs retailers $7,500 per month or more, depending on the number of unique visitors--is tackling the last mile of ecommerce marketing. "I realized that no one was looking at the website itself," De Datta says. "Everyone was taking a one-size-fits-all approach."
Raj De Datta of BloomReach Photo © Justin Keena
With SNAP, the goal was to use big data to help consumers individually, based on their current intent, not their demographic data or buying history. "We have the ability to recognize visitors with 99 percent accuracy," De Datta says of his company's "machine learning," which works even if the consumer previously visited a site on a mobile device and is now using a web browser. If BloomReach has its way, it'll vastly shrink the number of steps between landing on an ecommerce site's homepage and clicking the "add to cart" button.
For e-tailers, the appeal of SNAP, beyond its ability to better serve up the precise products people want, is that they don't have to rebuild their websites from scratch to use it. The cloud-based service automatically indexes every page--and every new page added--on a client's site and automatically generates for visitors the appropriate content on these pages. For stores that add and remove hundreds of products per week from their sites, this feature means they can post it and forget it. Another plus: Unlike A/B testing, which can take weeks to work through, BloomReach's aggregate machine learning, drawn from constantly updated data from all its clients and more than 30 public data sources, reduces the lag time between application and positive results. For ModCloth, the core technology behind SNAP translated into a 40 percent increase in visits to individual product pages--a sign that people were finding what they were looking for.
According to De Datta, the technology behind BloomReach is complicated but serves a very simple function: It's the answer to the customer who's browsing a site for that perfect green summer dress and knows nothing about what she wants other than, "I'll know it when I see it."
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