Feature
The Gist
- Data-Driven insights. AI automation empowers companies to gather and analyze customer data for smarter, personalized interactions.
- Customer convenience. Advanced chatbots and self-service options are drastically improving customer interactions and reducing the need for human intervention.
- Data utilization. Companies are using AI to analyze customer data for personalization, enhancing not just recommendations but also sentiment analysis and customer loyalty.
A group of customer experience (CX) leaders say there are several trends in how companies are using artificial intelligence (AI) automation as they work to establish and unify omnichannel CX: for the store, web, mobile, social, email and phone. They’re seeing companies deploy AI automation to enable customer touchpoints and improve interactions at various stages in the customer journey. The CX leaders shared details on those channel-specific trends with CMSWire:
1. AI Automation: Store
Mairead Maher, CMO for the customer and employee experience platform Poppulo, said retail CX teams are harnessing AI automation to proactively anticipate and cater to customer desires, “marking a transformative shift in the industry's customer experience landscape.”
Maher said CX teams are “gathering extensive customer data” — including behaviors, preferences, purchase history and real-time location — and then employing AI algorithms to glean valuable insights — or “data wealth” to use AI for predictive in-store purposes.
AI-driven recommendation systems offer tailored suggestions “upon a customer's store entry,” analyzing their past purchases and current location to automatically provide real-time product or promotion recommendations, she said.
“This enhances customer experiences, boosts sales, and fosters loyalty,” Maher said.
Maher also noted that digital signage is “emerging as a key tool” for integrating AI in retail spaces.
For instance, she said, “imagine digital displays tapping into a continuous stream of data sources,” including local community dynamics, social media trends, traffic patterns, weather conditions and consumer purchasing behaviors.
AI algorithms employed in such a digital signage context gain “a profound understanding” of the audience's characteristics and preferences — “effectively signaling the end of the era of generic, one-size-fits-all advertising,” Maher said.
Gaurav Jain, assistant professor of marketing at the Rensselaer Polytechnic Institute (RPI) Lally School of Management, said stores are using kiosks and virtual assistants, such as on-call chatbots, to help customers navigate through stores and find products, enhancing the in-store experience.
“AI in stores is like having an extra salesperson who knows every customer's preference,” Jain said.
Related Article: Customer Service Tasks to Be Automated — and Eaten by Generative AI
2. AI Automation: Web
Mercedes McAndrew, corporate marketing director for the Short Hills, New Jersey-based CRM platform Kustomer, said that with AI, companies are building and deploying sophisticated chatbots that deflect common customer inquiries by surfacing knowledge base content.
For instance, chatbots are processing cancellations, credits and refunds without a single human intervention, “drastically increasing productivity levels,” McAndrew said.
Suzanne Chartol, global head of customer experience for the San Mateo, California-based communications API platform Sendbird, said the chat experience is “so much easier and more rewarding” than a customer calling a company and staying on hold.
She said chatbots show how generative AI can relieve stress for both customers, who get convenient service, and agents, who get burdens relieved.
Jain with RPI said AI customer service chatbots are the new FAQ but more interactive.
“Chatbots are not just digital tools,” Jain said. “They're our first point of contact, bridging the gap between brands and consumers.
“However, there was always the question of accuracy versus efficiency while managing these chatbots — AI has answered that question. Companies can reduce customer dropout while avoiding the expense of managing a large human customer service team.”
Emily Wengert, managing director and executive creative director of experience innovation at the New York-based creative consultancy Huge, said generative AI in CX is following “more of a pull model than a push one.”
She said the pull effect happens, for example, when customers use a health care chatbot that draws on clinically approved content that “always points to the source,” allowing customers to ask the chatbot a nuanced and complex question and “trusting the result.”
“If your CX requires deeper knowledge and comprehension of a topic, it’s worth investing in gen AI that helps you showcase that knowledge,” Wengert said.
Related Article: AI in Customer Experience: 5 Companies' Tangible Results
3. AI Automation: Mobile
As more customers engage with brands on their mobile devices, such as through SMS, there’s an increase in the volume of customer inquiries, according to Nelson Haung, senior director of product marketing for the San Mateo, California-based business software provider Freshworks.
As such, companies are “determining how they can bring the self-service bot experience to messaging channels, which is a huge opportunity for generative AI,” Haung said.
Jain with RPI said retailers are leaning on AI to automatically analyze customer preferences and personalize notifications, including offers.
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“AI turns your mobile app into a personal shopping assistant,” Jain said.
Vikas Kaushik, CEO of the Agoura Hills, California-based mobile app development firm TechAhead, noted that companies are using AI to personalize their apps, such as a fitness app automatically evaluating user data and delivering individualized workout regimens and nutritional guidance.
Related Article: Connect Customer Service Reps With AI Automation for Contact Center Efficiency
4. AI Automation: Social
McAndrew with Kustomer said AI is identifying “exactly how customers are feeling” on social media, without requiring agents to read large volumes of text, to route conversations and prioritize those that need immediate attention.
“This helps to streamline conversations for customer service agents and help serve those with more urgent needs,” McAndrew said.
She said AI sentiment analysis also generates reports based on sentiment changes, which can help teams understand how their customer experience impacts how the audience “thinks and feels — so agents can deliver more proactive service and ultimately increase customer loyalty.”
Jain with the RPI agreed that AI is being used for social media listening, such as scanning social mentions and automatically replying to customer queries and complaints.
“AI doesn't just listen,” Jain said. “It understands customer sentiment.”
Ted Sfikas, senior director of digital strategy and value engineering for the San Diego-based customer data platform Tealium, said he’s seeing companies take their first-party data tranches to data clean rooms, tap AI to magnify the data’s value, and improve their social media targeting.
“Look-alike modeling for a brand has become re-energized,” Sfikas said. “Because AI can surface new prospects outside the owned and operated properties by taking advantage of the high fidelity customer data sets that the brand is using.”
Related Article: How AI for Social Media Can Help Brands Improve Engagement
5. AI Automation: Email
Companies are eliminating the “guesswork” in customer emails by deploying self-learning AI models that recommend the best responses and actions to agents based on historical conversation data, said McAndrew with Kustomer.
For example, she said, customer reps are relying on natural language processing (NLP) to automatically analyze messages and suggest the most likely shortcuts — including prepared responses and actions — that can be applied to an agent-customer email conversation.
Suggested responses populate an agent response, or the agent can draft an email and use features, such as tone enhancement or re-phrase, to “ensure a well-received response to the customer,” McAndrew said.
Haung with Freshworks agreed that with the advancements of generative AI, companies are “more efficient than ever” in responding to email inquiries.
Companies also depend on AI for automated email follow-ups and personalization, which are generated based on customer behavior and preferences, “ensuring high relevance,” said Jain with RPI.
“AI ensures that the right email reaches the right person at the right time,” he said.
6. AI Automation: Phone
McAndrew with Kustomer said companies are leaning on AI to offer automated voice support “around the clock” and efficiently identify customer queries through keyword-based filters ensuring “rapid and accurate assistance.”
With AI, organizations automatically summarize voice conversations and assign sentiment analysis scores to “determine if the customer is happy or upset” and route the conversation to the right agent, McAndrew said.
Jain with RPI added that companies employ voice recognition AI to authenticate users and direct them to the appropriate department.
He said the NLP in voice recognition AI allows for easier customer call navigation, while predictive analysis anticipates caller needs based on their history. The personalization means customers don’t repetitively provide account details, and emotion detection aids in gauging caller mood.
The results are “reduced wait times, more efficient interactions, and a significantly improved telephonic customer experience,” Jain said.
