VentureBeat’s MobileBeat 2017 took place July 11-12 in San Francisco. The star of last year’s conference, MobileBeat 2016, was the chatbot, reflecting the explosive interest in conversational user interfaces. This time around the dominating topics manifested as the power couple that combine artificial intelligence (AI) and machine learning (ML).

In listening to individual presenters and group discussions, it became readily apparent that the top use cases for AI and ML in the mobile realm are closely aligned with the core tenets of intelligent assistance (IA) as Opus Research defines. The terminology being used may be different, but the underlying goals and technologies are the same.

Walmart Labs, for example, showcased its use of AI to bridge the online and offline shopping experience. Using data about available inventory and store locations makes it possible for a dad to order items for his toddler on the Walmart app or website, drive to the closest store, and pull up to the curb to have the items loaded into the back of his SUV. But more importantly, Walmart Labs uses machine learning to personalize each shopper’s experience.

By analyzing data patterns and customer reviews, Walmart can recommend more relevant products to each shopper. The retailer employs algorithms to check for authenticity of customer reviews to ensure product rankings are accurate. Its goal is to provide truly advanced intelligent assistance by anticipating what a shopper is looking for and providing targeted information even before the shopper begins a search.

Another example comes from Coca Cola which announced the use of AI to add both personality and flexibility to the once static vending machine. Lauren Kunze of Pandorabots spoke about how her company partnered with Coca-Cola to add a conversational interface to the vending app. A chatbot interface enables Coca-Cola to interact directly with the customer and acquire data about their vending machine usage and habits. This data can be applied to personalize future experiences and recommendations. The new app even enables a customer to order a drink in advance, or a drink for herself and a friend, and get the beverages at a designated vending machine.

Diane von Furstenberg, in partnership with Qubit, is using AI to address the issue of poor purchasing follow-through on the part of its mobile app users. Data shows that many consumers use the brand’s app to discover products, but only a small percentage make purchases in the app, or go directly to the brand’s website to buy the product. Machine learning enables the company to better understand each customer’s preferences and improve product recommendations. But Diane von Furstenberg’s real goal is to optimize the customer experience and offer tailored suggestions for each individual shopper.

MobileBeat 2017 offered more examples of the growing trend towards AI-powered intelligent assistance at companies such as Kelley Blue Book , The New York Times, and TUMI. The most successful companies are all seeking to build a personal relationship with their customer. They’re leveraging intelligent assistance to offer curated product selections, streamlined experiences, and an omnichannel approach. Call it what you will, but Intelligent Assistance (IA) nis at the core of today’s online and offline commerce.

Categories: Conversational Intelligence, Intelligent Assistants