It’s time for a conversation on artificial intelligence
How The North Face uses AI to create natural conversations with online shoppers
Walk into a bricks-and-mortar location of The North Face, and you’ll likely be met by an associate who will ask targeted questions about what you’re looking for — and for what purpose.
Why shouldn’t the online experience be the same? The activewear/outdoor sports gear retailer has partnered with Fluid to incorporate IBM Watson technology into its e-commerce. Fluid’s Expert Personal Shopper platform uses artificial intelligence to create natural conversations with online consumers, rather than relying on keywords and less intuitive search.
Digital assistants such as Siri and Cortana have set the stage for a different level of conversation. Adobe reported in December that 33 percent of consumers with smartphones or tablets had used such a digital assistant within the past 30 days. In addition, Gartner has predicted that by the end of this year, more than $2 billion in online shopping will be performed exclusively by mobile digital assistants.
As such, the time is ripe for a two-way conversation tone in e-commerce.
“What we’re doing is turning personalization on its head,” said Neil Patil, president of Fluid’s software products group.
“What we’re doing is turning personalization on its head.”
The North Face started a beta test late last year, following a year’s worth of “really hard effort,” said Cal Bouchard, senior director of e-commerce for The North Face. In 60 days, 50,000 consumers tried the personal shopper platform, adding an average of two minutes to their time on the site. A post-test survey with more than 1,200 respondents rated the experience an average of 2.5 out of 3, and 75 percent of those who tried the platform said they would use it again.
Those who rated it highest were consumers who had previously had challenges on the site and been handpicked to try a new approach.
Though there’s still room for growth, Bouchard said, “I think this tells you that consumers are ready for some type of AI experience.”
75 percent of those who tried the platform said they would use it again.
For every response typed in, the system further calculates the consumer’s needs, gathers scores from each item across the catalog and runs algorithms to determine the next question. The benefit, Patil said, is that it allows customers to speak of their needs in their own language, rather than using search as “a one-way static representation of choice.”
It keeps customers from missing out on other options by showing high, medium and low matches to search criteria. And it clearly demonstrates why the items were matched as they were.
Bouchard took the audience through an example. Starting with a jacket search, the conversation began with, “Where and when will you be using this jacket?” to set context. The response: “I want a jacket for a skiing trip to Vermont in December.”
The next question concerns whether the jacket is for a man or woman; others include what activity the jacket will be worn for and what color is desired. The system is able to cull typical weather data for the area mentioned.
Fluid and The North Face have learned much along the way. First, Bouchard said, the system requires a lot of teaching. Second, such an effort needs partners across the organization, because it requires diving deep into the product catalog.
“The bottom line is that AI needs to know your product, and it will never know your product unless you really know your product,” she said.
This story originally appeared in print as part of STORES Convention Daily on January 18, 2016. Download the digital edition and see more coverage of Retail’s BIG Show 2016.
