February 02, 2022

Article
3 min

How Chatbots Can Help Retailers Meet Customer Expectations

Retailers can use artificial intelligence to bolster customer service and improve employee productivity.

Nathan Cartwright

Chris Cushman

While some retailers are using chatbots powered by artificial intelligence to handle their customer service inquiries, the retail industry has generally lagged sectors such as healthcare and finance when it comes to chatbot adoption. This technology is likely to become pervasive in retail customer service in the coming years. As it does, retailers will find that effectively implementing AI chatbots will unlock many benefits

How Chatbots Can Improve the Customer Experience

One simple and obvious (yet powerful) benefit to AI chatbots is that they work around the clock. Customers who need help after putting their children to bed for the night don’t have to wait until the call center opens again the next morning — they can simply start chatting with an AI bot to solve their problem on their own schedule. 

Although the technology is becoming more sophisticated, AI bots are especially helpful for walking customers through simple processes that have specific, repeatable steps to follow, such as initiating a return. Some retailers use bots to issue refunds under a certain dollar amount. This keeps customers happy and may even save the retailer money, considering it might cost more to engage customers in a traditional customer service interaction than to give them their money back for an item or service.

How AI Can Increase Employee Productivity

Instead of considering AI chatbots as mere replacements for human customer service representatives, retailers should think of them as a force multiplier to help agents be more effective at their jobs. 

Chatbots can help store associates better assist customers in person. For example, no single worker can be expected to be knowledgeable about the entire inventory of a big-box store, but chatbots can give employees the information they need to serve customers in real time. 

Or, in the contact center, a human agent can monitor several chatbot conversations at once, watching out for indicators that the chatbot is running into trouble, and then step in to bring a human touch to the interaction.

Finding Value Through Data Analytics and Reporting

Chatbot logs are treasure troves of information about what customers want, what problems they experience and their level of satisfaction. Companies can run transcripts through analytics programs that utilize natural language processing to determine what customers are talking about. They also can use sentiment analysis programs to measure how customers are feeling, instead of asking them to take a survey. 

Data from chatbots also can help retailers make decisions about sales and inventory. For example, if a car dealer’s chatbot receives several inquiries about a specific color and model of pickup truck, the dealership may opt to exclude that model from upcoming promotions due to high demand.

How AI Can Lead to Continuous Improvement

The more retailers use chatbots, the more they’ll learn about their customers, their employees and even about themselves. Inevitably, customers will ask questions that retailers haven’t thought to address, and companies can refine their chatbots over time to handle these inquiries. Some retailers might choose to leverage their chatbots to funnel customers into special services, such as one-on-one chats with live experts or installation services. 

Chatbot technology is coming to retail fast, spurred by economic drivers that include the “Great Resignation” of employees leaving the workforce during the COVID-19 pandemic. To succeed in this space, retailers need to get in front of the trend and continue to improve their tools and processes. 

Story by

Nathan Cartwright, has been a part of CDW's Cisco collaboration practice for 9 years and has been in the industry for nearly 15 years. He started in CDW's ACE program and is now a technical lead providing mentoring/support to CDW engineers as well as subject matter expertise to sales teams. Prior to CDW, Nathan worked for a small IT consulting firm as his first job and later as a systems and network analyst as part of an internal IT department.

Chris Cushman