AI can boost customer engagement if brand is open to change

Artificial intelligence has emerged as one of the most powerful tools for improving the customer experience, but retailers must be willing to accept operational change once they embark on their AI journeys. That was a key theme of a panel on driving innovation with AI during the Interactive Customer Experience Summit at the Omni Frisco Hotel in Frisco, Texas. Retailers will find themselves inundated with more data to manage, and they will likely uncover the need to make organizational changes and reassign some employee responsibilities.

"Understanding how to use your data is the biggest thing," said panel moderator Christie Rice, worldwide kiosk and digital signage segment manager at Intel.

But the panelists agreed the journey is worth the effort.

Why AI makes sense

Jeff Donaldson, founder and CEO of Intriosity, which specializes in design research for robotic and cognitive automation, said advances in camera technology are bringing new interactive capabilities to the retail shopping environment. Point-of-sale systems, meanwhile, are improving the shopping experience by removing queues as well as giving customers more information about inventory.

AI raises the bar even more, said Donaldson, as it provides a tool to help a company react to changing markets and changing customers. He added that AI has become more affordable in the last five years.

When beginning the AI journey, Donaldson said it is important to identify the core capabilities the company hopes to attain.

"Can I build a consumer experience over these capabilities in a way that meets consumer needs?" Donaldson asked.

Computer vision, voice technology and IoT sensors are all tools that — in conjunction with AI — will enable a retailer to rethink the dynamics of the shopping environment, he said.

Reduce labor costs

Both Donaldson and Panelist Laura Rea Dickey, CEO of Dickey's Barbecue, cited reducing labor cost as a catalyst for using AI. 

Dickey's Barbecue uses AI, voice recognition and machine learning to reduce labor, noted Dickey. The company has been able to reduce the pit crews in its restaurants by one person, she said. The platform automatically reminds employees what tasks need to be done, which has improved operational efficiency.

"How can they do a better job, a more efficient job?" Dickey said in articulating the reason the company invested in AI. 

Gain more insights

Panelist Dawn Dickson, founder of a software system for self-serve kiosks called PopCom, began her AI journey when she realized she needed more information about traffic around the self-serve shoe kiosks she installed in public places. She used AI to develop software that can track customer traffic outside the machines and monitor customer interaction with the machines.

"Now I can know the (customer) conversion rate," said Dickson. In addition to providing information on conversion rates, the software gathers data that helps with marketing and customer loyalty. It also provides the customers more information about the kiosks' inventory.

One lesson Dickson learned in her journey was to listen to the customers. 

"Don't assume we're building the right product," she said.

Listen to customers and employees

Where Dickson cited the need to listen to customers, Donaldson and Dickey agreed it was equally important to listen to the employees.

"The definition of the customer needs to be more thorough," Donaldson said. "Often, you have to treat the internal department as the customer. Be driven by the customer's problem that you're trying to solve."

Dickey said her company did not know at the outset of its AI journey how the pit crews would use the new software tools. The company had to be flexible and recognize how the employees wanted to use them. 

Data, data, data

Donaldson said AI is very data intensive, and companies deploying the technology should be prepared to store and access large amounts of data. He said process engineering skills are very valuable in this area.

Dickey concurred, noting that it is possible to get "analysis paralysis" if there is not the right internal structure in place. The company originally assigned centralized data analysts but has since assigned analysts to individual teams. Analysts use the data to 1) drive the consumer experience, 2) drive the operations experience, and ) drive the business.

Additional data has also been given to Dickey's Barbecue training teams in addition to operational teams, both of which have contributed to improved profitability.

The challenge of integrating legacy data was raised during the question and answer session. Dickey cited this as an area that requires having people on staff who are able to update historical data. Donaldson, agreed, saying historical data needs to be "cleaned."

"I would never say historical data isn't important, because it obviously is, but it's going to have to be cleaned and augmented," he said.

Asked for final bits of advice, Donaldson advised people interested in AI to explore creative design and "design thinking." He said there are effective design techniques that can help give insight into AI opportunities.

Dickson suggested using AI to supplement "real things happening with the customer."

As with any new investment Dickey said AI is a worthwhile providing a company has a business objective.