Forbes contributor Jennifer Kite-Powell predicts that the rise of artificial intelligence and machine learning has the potential to transform the customer experience over the next five years by improving the speed, efficacy, and outcome of myriad customer service interactions. There’s no doubt that the potential is there—but without incorporating reward and recognition elements to provide a differentiated experience for best customers, will brands be missing a trick?
By Rick Ferguson
Kite-Powell offers evidence that, far from remaining in the ethereal realm of “future potential,” AI-assisted customer interactions are already providing demonstrable impact to brands. Money quote:
“According to Juniper Research, chatbots will create a cost savings of more than $8 Billion annually by 2022, up from $20 Million in 2017. In the enterprise, 31% of business executives believe virtual personal assistants will have a substantial impact on their business, more than any other AI-powered solution according to a PwC report in 2017. And 34% of business executives say that the time saved that was generated from using digital assistants allows them to focus on deep thinking and creating. And this is the big reveal, in that same report by PwC, 27% of consumers said they weren’t sure if their last customer service interaction was a human or a chatbot.”
The AI revolution will not be without rough spots, Kite-Powell cautions, with one of the primary risks being the “institutionalization” of bias as AI trainers feed data to systems that may already incorporate bias systemic to human interactions—imagine the risks of an AI system designed to provide mortgage approvals, for example, and the risks will become clear. Leveraging experts in the field, she predicts that the role of human customer service agents will evolve to more strategic, senior staff tasked with guiding and training AI systems to make the right decisions. She uses the example of AI provider Zendesk to illustrate how this evolution will unfold. Money quote #2:
“Zendesk says they developed a technique to train their Answer Bot algorithm to only replicate positive customer interactions. They have millions and millions of interactions where a human agent has sent a knowledge base article to a customer, but dozens of times that agent didn't get it right and submitted an article that didn’t resolve a customer’s issue. ‘We only wanted train our AI on positive customer interactions, so we developed a two-stage learning approach where Answer Bot first learns to identify interactions where a customer-validated that they received a helpful article, and had a great experience. The algorithm only learns from interactions that fit that profile. This effectively created an algorithm that “learned” to remove the bias introduced by human error,’ said [Zendesk GM Jason] Maynard.”
With AI-driven customer service platforms and digital assistants becoming the new norm, the risk for brands is that all of this investment becomes amortized across the entire customer base, from your most valuable to your least valuable customers. To provide a differentiated experience, brands will need to incorporate elements of reward and recognition into their algorithms. An AI chatbot who identifies a best customer, for example, might be trained to provide a surprise-and-delight reward, to authorize a more liberal returns policy, or even make an upsell offer via predictive analytics. If AI is to become more than the new cost of doing business, marketers will need to train these systems to enhance customer relationships, rather than focus solely on efficiency and cost-reduction metrics. That’s how AI will truly transform the customer experience.
Rick Ferguson is Editor in Chief of the Wise Marketer Group and a Certified Loyalty Marketing Professional (CLMP).