In a post on its corporate blog on Monday, eBay explained how it uses machine learning technology to drive innovative new approaches to search experiences. But while that may sound good to the rest of the world, sellers may be wary of marketplaces that tinker with search, which is key to getting exposure to shoppers. Even before eBay started touting its skills in artificial intelligence and machine learning, sellers were concerned over eBay's use of an algorithm to influence which listings would appear higher on the search results page, something known as Best Match - the default sort order of listings. And that's exactly where eBay is concentrating its testing. In Monday's post, eBay wrote, "The largest scale application of machine learning technology at eBay is currently Best Match, the algorithm used to optimize relevance for buyers during their shopping experiences.
Before it deployed a Hadoop cluster five years ago, retailer Macy's Inc. had big problems analyzing all of the sales and marketing data its systems were generating. And the problems were only getting bigger as Macy's pushed aggressively to increase its online business, further ratcheting up the data volumes it was looking to explore. The company's traditional data warehouse architecture had severe processing limitations and couldn't handle unstructured information, such as text. Historical data was also largely inaccessible, typically having been archived on tapes that were shipped to off-site storage facilities. Data scientists and other analysts "could only run so many queries at particular times of the day," said Seetha Chakrapany, director of marketing analytics and customer relationship management (CRM) systems at Macy's.
AI is revolutionizing so many aspects of our lives. From the way we operate appliances in our homes to the way that children play with toys. AI is also starting to have a significant effect on the way e-commerce businesses attract and retain customers. In fact, a survey by Gartner predicts that by 2020, 85% of a client's relationship with a business will be managed without interacting with any human. For a better understanding of how AI is shifting e-commerce, check out the five applications below.
"If you're not doing AI today, don't expect to be around in a few years," says Japjit Tulsi, VP of engineering at eBay, "It really is that important for companies to invest in -- especially commerce companies." Tulsi will speak next week at MB 2017, July 11 and 12 in SF, MobileBeat's flagship event where this year we've gathered more than 30 brands to talk about how AI is being applied in businesses today. It has focused on the potential of AI for the past ten years. The company's approach to AI has been built on a platform of research and development, Tulsi says, plus decades of insights and data about consumer behavior, making even the simplest applications incredibly valuable. As an example, Tulsi points to the merchandizing strip at the bottom of every item page, which shows similar items that a shopper might be intrigued by, and often leads them down a positive rabbit hole of shopping and buying.