This article has been reviewed according to Science X's editorial process and policies. Editors have highlighted the following attributes while ensuring the content's credibility:
fact-checked
peer-reviewed publication
trusted source
proofread
How AI can boost service for vulnerable customers
![AID framework, identification and prediction process of consumer vulnerability. Credit: Journal of the Academy of Marketing Science (2023). DOI: 10.1007/s11747-023-00986-8 AI can boost service for vulnerable customers](https://scx1.b-cdn.net/csz/news/800a/2024/ai-can-boost-service-f.jpg)
Artificial intelligence has become the Swiss Army knife of the business world, a universal tool for increasing sales, optimizing efficiency, and interacting with customers. But new research from Texas McCombs explores another purpose for AI in business: to contribute to the social good.
It can do so by helping businesses better serve vulnerable consumers: anyone in the marketplace who experiences limited access to and control of resources.
"AI is widely recognized for its operational and financial benefits, but it also holds promise for harnessing social good and helping businesses adopt socially responsible practices," says co-author Gizem Yalcin Williams, Texas McCombs, assistant professor of marketing.
With Erik Hermann of ESCP Business School in Berlin and Stefano Puntoni of the University of Pennsylvania's Wharton School, Williams devised an AI framework that businesses can use to identify vulnerable consumers, address their specific needs, and mitigate potential discrimination and inequalities.
By making customer service more accessible, more interactive, and more dynamic, Williams says, AI can help vulnerable consumers improve their understanding of specific information so that they can make better decisions for themselves.
For example, there are already AI tools businesses can use to analyze consumer voices and reactions while providing real-time feedback to customer service representatives, along with tips to improve the interaction. Key concepts of the framework include:
We're all vulnerable (sometimes)
Rather than always being an ongoing condition, vulnerability may be a dynamic state that can come and go. Cognitive and physical limitations can compromise a person's judgment, but so can emotional distress, such as suffering a layoff, breakup, or death in the family.
"Vulnerability can differ in duration and intensity, but literally every consumer can be vulnerable," Williams says.
This revised definition of vulnerability opens new doors for AI technologies to do social good, she adds. "With advancements in machine learning and natural language processing algorithms, AI is uniquely positioned to identify vulnerable consumers and to help employees better serve and empower these customers."
Rating risk
Recent reports indicate that customer service agents are often unaware when they interact with vulnerable consumers. However, AI can perform real-time analysis of consumer chat responses and use cues to build a risk score for agents.
Targeting extra support
When AI detects a vulnerability, it can offer customer service agents customized tips and suggest special measures. For example, if a consumer shows signs of being overwhelmed or having trouble processing information, AI can recommend that agents explain options in simple terms, along with their pros and cons.
Positive ripple effects
Designing and integrating AI into customer service requires investment. But by detecting vulnerability and guiding consumers through vulnerable times, businesses can harvest both financial and reputational benefits.
"Doing good often pays off," Williams says. "When effectively implemented, businesses utilizing AI to empower their vulnerable customers can expect a positive spillover, fostering increased loyalty, improved customer satisfaction, and boosted profits."
The work is published in the Journal of the Academy of Marketing Science.
More information: Erik Hermann et al, Deploying artificial intelligence in services to AID vulnerable consumers, Journal of the Academy of Marketing Science (2023). DOI: 10.1007/s11747-023-00986-8
Journal information: Journal of the Academy of Marketing Science
Provided by University of Texas at Austin