Feature
The Gist
- AI Boosts independence. AI reduces effort via self-service and predictive tools, improving customer experiences.
- Resolution revolution. AI accelerates resolution, analyzes interactions and supports agents for better efficiency.
- Conversion & retention. AI increases conversions, targets at-risk customers and improves retention rates.
A group of customer experience (CX) and artificial intelligence (AI) execs have observed companies deploying AI to address and improve several key CX performance indicators (KPIs): customer effort, resolution, satisfaction, conversion and retention. They report the ways that CX teams turn to AI for the automation, personalization and dynamic service that are critical to meet customer expectations and drive their core KPIs. The group of AI and CX execs shared details with CMSWire on the role of AI in each of these KPIs:
1. AI for Customer Effort
Michael Ramsey, VP of customer workflow products at the Santa Clara, California-based digital workflow company ServiceNow, said AI fully exposes the services that customers are “entitled to so they can solve requests on their own” through various self-service channels, making the customer experience easier.
For instance, Ramsey said generative AI-powered search “swiftly handles complex queries” to deliver precise, conversational answers, and AI virtual assistants offer “human-like aid” 24/7 with step-by-step guidance — giving customers “greater independence and ensuring their inquiries are resolved satisfactorily on their own terms.”
Abhishek Shah, founder of the Bensalem, Pennsylvania-based talent assessment company Testlify, agreed that AI is streamlining customer interactions by “providing personalized self-service options.”
“Through AI-powered chatbots and virtual assistants, customers can find quick answers to their queries, reducing the effort needed to navigate through support systems,” Shah said. “Furthermore, AI-driven predictive analytics anticipates customer needs, enabling businesses to proactively address concerns, minimizing customer effort even further.”
The reduction of friction is “a North Star for many CX professionals and often a key component of a digital transformation exercise,” said Frank Schneider, AI evangelist at the Melville, New York-based customer engagement platform Verint.
Schneider said CX leaders are “leaning into AI within digital transformation programs to offer quicker checkout journeys with AI automation,” which improves the customer effort score (CES) and reduces abandoned carts.
“Once a customer has authenticated, instead of numerous qualification workflows and an escalation to a human, seamless checkout journeys are now offered,” Schneider said.
Deven Lindemann, chief customer service officer at the Minneapolis, Minnesota-based M&A platform Datasite, added that AI provides multiple channels for “on-demand support.”
“A good customer experience includes giving customers a choice on how they want to engage with support,” Lindemann said. “Providing customers with options allows the business to meet customers where they want to work.”
Related Article: AI Customer Experience Ushers in a New Era of Engagement
2. AI for Customer Resolution
Zac Sprackett, chief product officer at the San Francisco-based CRM platform SugarCRM, said AI is helping CX teams address consumers that “now expect lightning speeds for every business interaction.”
AI puts companies a step ahead so they don’t “fail to address customer needs,” including proactively monitoring customer sentiment to identify issues “before they escalate,” Sprackett said.
Olusegun Obafemi, customer experience leader at the consulting firm EY Americas, said companies are using AI to analyze customer interactions, cross-channel feedback, and sentiment data to improve issue resolution rates, such as first contact resolution (FCR), average handling time (AHT), escalation rate and ticket re-open rate.
“AI recommends next best actions and in complex cases supports human agents in customer interactions,” Obafemi said. “AI can predict unnoticed issues as tickets, revolutionizing organizational knowledge management.”
AI is enabling overall agent productivity and “speeding time to resolution,” said Ramsey with ServiceNow. For example, Ramsey said AI can distill essential details from customer interactions — such as previous touchpoints, actions already taken, and case details — into a summarized case document for quicker agent hand-offs and resolution.
Ramsey also noted that process mining coupled with AI acts as a “strategic playbook, analyzing operational workflows to streamline processes.”
“This optimization accelerates resolution times, ultimately heightening the customer experience and bolstering overall efficiency,” Ramsey said.
Schneider with Verint agreed that CX leaders are deploying AI to “optimize the chance for success” when a human agent is required, such as providing “concierge-like guidance as part of a complex task or need within a customer journey.”
Related Article: How to Pick the Right Flavor of Generative AI
3. AI for Customer Satisfaction
Obafemi with EY said CX teams are implementing AI for “quick and seamless support” throughout the customer journey to improve customer satisfaction metrics, such as the Net Promoter Score (NPS), customer satisfaction score (CSAT) and loyalty indexes.
For instance, Obafemi said AI can predict and resolve network service issues, provide around-the-clock support for customers through chatbots, and offer personalized recommendations, such as for products and account management.
Ramsey with ServiceNow agreed that CX pros are depending on AI to personalize interactions and the customer journey to enhance both engagement and loyalty.
“The era of tailored experiences has arrived,” Ramsey said. “AI examines individual customer history and preferences to craft responses uniquely attuned to each interaction and suggests recommended actions and responses. This personalized touch, acting as a virtual concierge, establishes a deeper rapport between the customer and services.”
With AI voice assistants, companies can turn a “potentially frustrating support call into a pleasant, even enjoyable one” and save “all parties time and hassle,” said Nikola Mrkšić, co-founder and CEO of the London-based voice assistant platform PolyAI. Trained AI voice assistants have access to the most up-to-date company information and can answer questions “quicker and more accurately than many live agents,” Mrkšić said.
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Lindemann with Datasite added that satisfied customers want a “human, personalized, and relevant experience that saves them time by minimizing complexity and anticipates their needs.”
“This means building relationships from the very first customer interaction and using data and automation powered by AI, plus intelligence from every interaction, to make that user a customer for life,” Lindemann said.
4. AI for Customer Conversion
Obafemi with EY said CX teams are deploying AI to see higher conversion rates throughout the customer purchasing journey, such as in ecommerce and lead capture, through the dynamic optimization of digital interfaces, guided selling and pricing optimization.
Sprackett with SugarCRM agreed that companies use AI to “increase adoption and improve customer lifetime value” by identifying and targeting whitespace or opportunities.
“By analyzing customer behavior, preferences and historical data, these businesses deliver more targeted product recommendations, promotions, and offers,” Sprackett said.
AI, however, isn’t necessarily a stand-alone solution in customer conversion strategy, according to Sisi Zhang, EVP of data science and analytics at the New York-based marketing agency Razorfish.
“It's important to recognize that AI on its own is not a tool to improve any of these CX KPIs,” Zhang said. “Usually, AI's impact is felt when it's applied within out-of-the-box products or built on top of existing tools. In general, AI can improve conversion KPIs, but those results aren't isolated to generative AI specifically.”
Jure Leskovec, co-founder and chief scientist at the Mountain View, California-based predictive AI company Kumo.AI, is seeing companies use AI to improve cross-sell conversions by “discovering which new product lines will be most effective with existing users” as well as improve conversion rates with AI-driven personalization.
For mobile, Leskovec said marketers use AI to understand the frequency and content of notifications to improve order rates and active usage “while decreasing opt-out rates.”
Related Article: Top Conversational AI Metrics for CX Professionals
5. AI for Customer Retention
Sprackett with SugarCRM said CX teams turn to AI to proactively identify and reach at-risk customers through “churn prediction models.”
“These well-timed, personalized customer interactions improve customer experience and reduce churn rate,” Sprackett said. “It’s about retaining customers and ensuring those customers succeed and grow.”
Shah with Testlify agreed that AI predictive analytics is helping companies “identify potential churn risks.”
“By analyzing customer behavior and historical data, AI models can predict which customers are likely to leave and why,” Shah said. “Armed with this information, companies can proactively engage with at-risk customers, offering personalized solutions to improve retention rates.”
To efficiently address negative reviews at scale and retain customers, CX professionals are relying on AI. They automate the time-consuming task of crafting intelligent, on-brand responses that are unique to each location, according to Monica Ho, chief marketing officer at the San Diego-based marketing platform for multi-location brands SOCi.
Responding to reviews and resolving customer issues in near real-time are “critical elements of successful CX,” Ho said.
Ashu Dubey, founder and CEO of the Pleasanton, California-based AI customer support platform Gleen, added that CX pros are employing the latest AI chatbots to “reduce customer churn” by efficiently performing support functions, which “delights customers.”
“Previous chatbot iterations would put customers in an endless loop and not satisfy their request, which contributed to higher churn rates in nearly every industry,” Dubey said. “A poor experience with a customer success chatbot can steer customers to competitors, but a positive one will keep customers engaged.”
