IBM’s Watson already has a new retail job lined up to get a head start saving for its holiday spending this season. (Hey, even artificial intelligences appreciate buying gifts.) And Macy’s is hoping its customers appreciate its “Macy’s On Call” pilot, which combines Satisfi’s communications platform and IBM Watson cognitive technology for machine learning. Macy’s On Call creates an in-store companion on mobile devices that aims to help improve the service of customers. The pilot will be in 10 stores across the United States.
According to the retailer, the Macy’s On Call app will be accessed via a mobile web browser. Customers can ask the app questions in natural language, such as where certain brands are located, and get customized answers. Customers also can learn about specific in-store services available at each test location, including personal shoppers, pickup counters or the location of restrooms. Macy’s hopes the app will also help them learn more about the services and features that shoppers want.
Since each Macy’s store is different, and consumers increasingly prefer mobile platforms, the system will evolve as it learns more about each store’s customers. “At Macy’s, we remain focused on identifying, testing and supporting new ideas and approaches that will help elevate service to our customers through technology. With an eye toward innovation, we are moving fast to test and scale up pilot programs that help enhance their experience with us,” said Peter Sachse, Macy’s chief growth officer, in this statement.
“This program, in partnership with Satisfi and leveraging the power of IBM Watson, will help us explore new ways to engage one-on-one with customers in-store, providing them another level of service right at their fingertips,” Sachse added.
“Bringing Watson into a retail store setting presents an opportunity to engage with the consumer on a variety of levels,” said David Kenny, general manager of IBM Watson. “This particular use case takes Watson beyond helping consumers evaluate purchasing decisions, and influences another, equally important aspect of the in-store experience,” Kenny said.
The first phase of Macy’s On Call recently launched and is expected to run through late fall. Of course, Macy’s has the potential to learn an extraordinary amount about its customers’ preferences through this program—preferences that otherwise wouldn’t have been so easy to learn without the aid of the Satisfi platform or Watson’s machine learning. Macy’s also may learn how to more rapidly improve its stores, manage inventory most effectively, and more quickly learn what is and isn’t working in its retail environments. That is, of course, if it can make Macy’s On Call engaging enough for customers to want to try, as well as provide enough value for them to want to use over time.
Macy’s wasn’t the only one recently to make a significant machine learning announcement and the innovative use of technology. Google said it is using software from its DeepMind subsidiary to significantly cut the costs to power its data centers. According to DeepMind co-founder Demis Hassabis, two years ago Google began applying machine learning to operate its data center more efficiently. And over the past few months, DeepMind researchers began working with Google’s data center team to significantly improve the system’s utility. “Using a system of neural networks trained on different operating scenarios and parameters within our data centers, we created a more efficient and adaptive framework to understand data center dynamics and optimize efficiency,” the Google team wrote in this blog.
According to Google, the team cut power usage in their data centers by several percentage points, which translates into a 15 percent improvement in power usage efficiency. These are exactly the types emerging technology applications CIOs and chief digital officers need to focus on if they are going to succeed, as we covered in our post, “Digital Transformation Strains Traditional IT.”
According to the McKinsey report, “Digital America: A Tale of the Haves and Have-Mores,” the United States is digitizing so rapidly that most are scrambling to adapt. The race to keep up with technology and put it to the most effective business use is producing digital “haves” and “have-mores”—and the large, persistent gap between them is becoming a decisive factor in competition across the economy, the report said.
According to the report, “Digitization is happening unevenly, and users with advanced digital capabilities are capturing disproportionate benefits. The companies leading the charge are winning the battle for market share and growth; some are reshaping entire industries to their own advantage. But many businesses are struggling to evolve quickly enough. Workers in the most digitized industries enjoy wage growth that is twice the national average, while the majority of U.S. workers face stagnant incomes and uncertain prospects.”
Clearly, organizations such as Macy’s and Google making moves want to ensure that in the year ahead they want to be the digital “have mores.” Businesses that aren’t making their own similar moves to employ machine learning to cut costs, improve customer experiences, or find other ways to advance the business may not find themselves the “haves” but the “have nots.”
Julien is a search veteran who’s been working in the search landscape for over 10 years, with work experience in Thales and Exalead. He participated in the design of three different search engines prior to co-founding Algolia with Nicolas and is the author of the different algorithms responsible for Algolia’s super fast performance.
