The Real Benefits of Artificial Intelligence

For this reason, and because some ill-intentioned people might be inclined to try to sabotage chatbots by testing their skills or deliberately feeding them bad information—as was the case with Microsoft’s Tay—these technologies often cannot work on their own.

Jezierski agrees. When it comes to chatbots, she says, there have been “a lot of failures.”

As a result, she says, it is “really important for us to ensure that when there is a failure, there’s an easy way for a customer or agent—or whoever the user is—to move to another level of support, which may be assisted.”

Also important is continually monitoring the quality of unassisted interactions, she says. Currently, “we’re missing a lot of valuable information about how customers feel about those interactions—whether they like them or not.”

FIGURING OUT WHERE AI CAN ADD VALUE

Companies that are considering applying smart tools to their technology stacks would be well advised to figure out where AI can add the most value.

Samsung, one of several companies that piloted Augment’s AI platform before its official release in September, was able to more than double traffic to its website by adding a chatbot.

But the benefits don’t stop there, according to Swanson. The same AI technology that powers chatbots can help service agents find the information they need, but it also has tremendous potential to open up more opportunities for revenue. Using machine learning, the technology can sift through available data contained within companies’ CRM systems and other data repositories to surface recommended answers to chat-based questions. It can also use natural language understanding to read and interpret customer questions and then retrieve responses recorded from previous agent-customer interactions. Agents are then free to edit and personalize the responses before sending them to customers.

If a customer is in the market for a television and wants to know about the size, weight, and dimensions of a particular model and whether it can be mounted on the wall, for instance, Augment can make sense of those questions and save the chat agent some time in having to look up the information, without the customer ever realizing that the interaction was being fueled by a bot.

Further down the line, the technology will be able to surface product recommendations, drawing conclusions about which items people are likely to buy based on the queries they ask.

In Samsung’s case, the company identified the need for support agents to quickly answer common questions about products that come in via its website. Because the chat format is convenient for visitors to a website, it might make sense for companies to first invest in that area.

Customer journey mapping can also help companies determine where AI might be of use, says Jezierski. “If you’re mapping your customer journey—whether it is a sales journey, or a purchase journey, or a service journey—as you map those and identify pain points for customers, you also need to look at those in the context of which ones we can automate, and you need to understand the source of the pain point,” she says. “If the source of the pain point is related to issues in the assisted channel, it may be a perfect opportunity to move it into some type of unassisted channel with some type of AI.”

Leggett suggests starting small and identifying the areas where support organizations can get quick wins with AI. Reducing call volume and call handle times and upping customer satisfaction rates are common starting goals.

Jeffrey Wartgow, senior director of product management at Oracle, agrees, noting that many Oracle users set out on their AI journeys aiming to reduce call handle times and volumes.

He points to StubHub as an example. The ticket seller implemented a basic system with an intelligent assistant that walks customers through a FAQ section on its website to reduce the number of callers. If the questions are more complicated, the AI directs users to live agents. “It dramatically deflects all those very simple questions that customers can probably self-serve on so that the contact centers can focus on the more complex stuff,” Wartgow says.

For now, such technologies can answer simple questions, but in the long term, they will be able to tackle more complicated issues. If, for example, a customer wants to know if his car is still under warranty, the answer could depend on a number of factors, including whether the person used factory-authorized replacement parts, kept up with the preventative maintenance plan, and other data that might not be stored in a CRM system. In those cases, the system would have to mimic a live agent’s line of questioning, guiding customers through sequenced and branched interview questionnaires to get the answers.

REDUCING TRAINING EXPENSES

Intelligent technologies can also reduce agents’ need to memorize every little detail, instead enabling them to look up information on the fly, which could cut down on training costs.

In fact, according to Kelly Koelliker, director of product marketing at Verint Systems, some customer service organizations have been able to lower training costs by up to 52 percent after applying advanced knowledge management tools to their contact centers.