- February 3rd, 2017
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Using Artificial Intelligence Both In Apps And In The Aisles
If the basics of retail are elementary, then it should be no surprise that a technology named Watson is leading what may be one of the biggest trends in 2017.
Watson is the name of an artificial intelligence technology (AI) by IBM; many may remember Watson for its $1 million winning streak on “Jeopardy.” Today, several major retailers — from Macy’s to 1-800-Flowers.Com — are using or testing the supercomputer’s cognitive computing capabilities to more acutely predict (and serve) customer wishes.
Most recently, Staples announced plans to implement Watson technology to bring to life its Easy Button. Infused with the technology, the button can now take Staples orders by voice, text, email, messaging app or mobile app.
The marvels of AI capabilities are wide-reaching, as is evidenced by the Amazon Echo and Google Home smart speakers. It’s no wonder retail is a great fit. The technology can understand and interpret customer preferences to make more accurate product suggestions, manage inventory based on predictive modeling and even identify ideal store locations. The industry, valued at $126 billion in 2015, is expected to reach $3 trillion by 2024.
Many merchants have adopted some form of AI in the past year. But are they in jeopardy of being too late?
I suspect online merchants are better equipped to get up to speed; they cut their teeth on clickstreams and piles of customer interaction data. But what about brick-and-mortar players?
They do collect data, often via loyalty programs, but putting those insights to action can be a complex endeavor with so many store-related distractions at hand. And in many cases, their data hierarchy and retention capabilities need significant work.
Enter a host of new AI applications, which are now more targeted to suit specific retail needs and therefore more approachable. In this context, perhaps late is better than never.
The key to faster adoption is the ability to see tangible results, said Emily Bezzant, head analyst at Edited, a retail analytics company with offices in New York, London and Melbourne. Brands are expanding the amount of data they have outside their core businesses, she said.
“All retailers have data within their business; the question is how can they best get actionable insights from it,” said Bezzant, who predicts AI will be a major retail trend in 2017. “AI and machine learning aren’t a fad; they’re a new technological innovation that means huge sets of data can be leveraged into decisions that could formerly only be made by people.”
Many of those decisions are now being made by a technology with a human name: Watson.
Watson’s Many Partners
I singled out Watson because so many merchants are testing and using it, and not all are online-exclusive. In addition to Staples, the following merchants have partnered with IBM:
- Macy’s: Though it’s a traditional brick-and-mortar retailer, Macy’s has invested heavily in online and omni-channel merchandising. This includes the Macy’s On Call app, which combines Watson’s cognitive computing with location-based software to answer shoppers’ in-store questions, such as where a specific clothing brand is located. The program was tested in 10 stores through fall 2016.
- Under Armour: The maker of high-tech activity apparel recently partnered with Watson to create an app that helps customers track their health and fitness activities, including sleep and nutrition. It in turn provides the users with coaching based on their data, as well as the results of other people who have similar health/fitness profiles. It also pulls from nutritional databases, physiological and behavioral data.
- 1-800-Flowers.Com: The digital florist and gift company tapped into Watson to create GWYN, a virtual gift concierge. GWYN “intuitively guides customers through their shopping experience to help them select the perfect gift,” according to a company press release. GWYN can interpret questions such as “I am looking for a gift for my wife” and then ask related questions about the occasion and sentiment to make reliable suggestions.
- The North Face: The outdoor-gear chain launched a Watson-powered digital shopping tool that presents online coat-shoppers with a series of questions, such as “Where and when will you be using this jacket?” The answers are used to generate relevant coat suggestions. Shoppers who use the tool are more likely to buy than those who do not, The North Face told Adweek. The retailer is exploring different ways to use the technology.
- Sears: The 124-year-old department store chain is using Watson to boost one of its tried-and-true categories — tires. The AI-enabled app, called Digital Tire Journey, prompts the shopper with questions and matches the most appropriate tires with driver preferences. The app identifies the shopper as a Comfort Warrior, Value Seeker, Off-Roader, High Performer, Safety Seeker or Winter Warrior and presents several purchase options (buy online, schedule an appointment or reach a call-center employee).
Embrace the Algorithms
Based on these examples, it’s evident that brick-and-mortar merchants certainly have the ability to adopt AI technology. The trick is having the required data and the ability to blend it with the in-store experience.
They certainly can take a lead from online merchants. Bezzant points out that many retailers are already using big data analytics to track the competition and hone their retail strategies.
“However, it’s the savviest and most forward-thinking brands that are looking more deeply at machine learning, analytics and AI across all aspects of their businesses,” she said. “Embracing self-learning algorithms gives retailers the ability to sell more products with less discounting, understand competitors’ pricing, have correct product assortments and minimize gaps, spot key trends early and capitalize on them with maximum efficiency.”
Indeed, retail’s AI adoption is not all happening online. Nor is it all relying on the power of IBM’s Watson. The robots being tested at Lowe’s, called LowBots, come to mind. They can process natural language to respond to customer questions, and can even tell the difference between people and objects.
That may seem elementary to you and me, but in retail it represents a graduation of sorts. Where do the humans fit in? That’s a topic for another article.