Retailers are expected to spend 7.3 billion dollars on AI annually by 2022, according to a CapGemini Research Institute report. This investment is largely motivated by companies’ interest in improving customer experience across all engagement points, including marketing, buying, and after-sales service.
Eugenio Cassiano is the chief innovation officer for the SAP Customer Experience organization. He talked about three ways AI can deliver great customer experiences for retailers and other types of organizations.
According to Cassiano, conversational AI is moving into the mainstream. For example, Meteo France provides weather information to citizens across the country. But to reach more people, Meteo decided to create a chatbot — powered by SAP Conversational AI, formerly recast.AI — that allows people to ask about the weather condition via Facebook messenger and receive real-time responses.
Cassiano believes that conversational AI can act as a sort of virtual concierge for retailers. For example, a bot on the front end of an ecommerce site can help provide customers with smart service.
“Say someone ordered a pair of jeans online that don’t fit. They can talk to a bot, which can access the customer’s order and profile, then offer a refund or new item that’s tailored to that person’s style and purchase history,” he says.
Because SAP C/4HANA connects the bot to the operational back end, the bot “knows” which products that are in stock and how long delivery will take.
SAP had already been working on using conversational AI to improve customer experience when it acquired recast.AI. “Now that we’ve brought recast.AI into the product, we can support many different languages, which is a big differentiator,” says Cassiano.
SAP offers a predefined, trained model so companies don’t need to spend time on complex implementations. Bots are available for customers now, and can be up and running in as little as a few days, assisting customers across multiple languages and channels.
Systems like Alexa and Google Home are great if you want to play the latest Rihanna song. But as Cassiano explains, these are relatively closed ecosystems. “If you’re Adidas, it’s hard to access the home. You can’t ask Alexa to add things directly to your Adidas shopping cart,” says Cassiano.
Cassiano and his team want to help retailers reach customers directly through voice-activated AI systems like Alexa, and make it seamless for customers to buy products from their living room. “The goal is to bring content marketing into those systems so that obtaining information about a particular brand is as easy as getting information on the last song you might have heard.”
Emotional AI extracts sentiment from people’s facial and vocal express expressions. It works like this: Machine learning algorithms are trained to recognize what these expressions mean, and then trigger the appropriate action, all of which can be used by companies to provide a better customer experience.
For example, if someone calls into a customer service hotline and is angry because something arrived broken, the system can alert service agents that there is a potential problem.
“If you are already aware of the customer’s mood and sentiment before you get on the phone with them, you know how to treat them,” says Cassiano. “For example, you probably won’t want to try to upsell an upset customer.”
Still in its early days, facial recognition helps retailers understand the customers’ mood while visiting stores and their response to particular products. But Cassiano admits there are ongoing privacy concerns with this technology, so the team is looking at ways to use this technology at the store rather than the individual level.
The goal for Cassiano? “We can evolve customer service from just a phone call to an empathic, positive relationship between customers and agents, where customers feel understood,” he says.