Artificial intelligence (AI) is everywhere, from assisting with medical diagnoses in hospitals to powering self-driving vehicle systems. One of its most prominent uses is in customer service, where AI can handle tasks like training agents, prioritizing and routing tickets and calls, and summarizing customer interactions.

Whitepaper

CallMiner CX Landscape Report: 2024

Discover how practitioners around the globe using data, analysis & AI to improve customer experience based on this landmark survey from CallMiner.

Businesses should consider implementing AI tools to remain competitive. This guide offers tips and best practices for leveraging AI to improve customer experience (CX).

In this article:

• How is AI used in customer experience?
• 25 ways to use AI to improve customer experience
• Frequently asked questions

How is AI used in customer experience?

Artificial intelligence (AI) has been used in the call center for decades. The technology has rapidly advanced, and today, many companies leverage AI in some way enterprise-wide. One area that benefits substantially from the use of AI is customer experience. Here are a few of the ways smart companies are putting AI to use in CX:

• Personalization: One of the earliest use cases for AI as it became more mainstream is personalization. AI can analyze customer behavior and interactions to provide tailored recommendations, product suggestions, or content.
• Chatbots and virtual assistants: Another use case for AI that took off early on is the AI-driven chatbot. AI-powered chatbots and virtual assistants provide 24/7 customer support, alleviating the demands on customer support teams and allowing your human call center representatives to focus on more complex customer needs.
• Sentiment and emotion analysis: AI can analyze customer interactions on the phone, email, social media, chatbots, and more to gauge customer sentiment and analyze the emotions behind what they’re stating. These insights help companies understand how customers feel about their products or services, so they can take action to resolve potential problems before they become significant issues.
• Automated customer service: In addition to AI-powered chatbots and virtual assistants, AI can automate customer service workflows such as call routing and ticketing, which can improve response times and overall efficiency.

These are just a few of the many use cases for AI in customer experience, and as the technology continues to evolve, forward-thinking innovators will develop more ways to use it to improve customer service, boost customer satisfaction, and enhance customer experience.

25 ways to use AI to improve customer experience

Let’s take a look at 25 ways you can use AI to improve CX within your organization.

1. AI can take over tasks that humans struggle with, ultimately resulting in happier customers. “CallMiner has been in the AI business for a while, a good long while, it has just not been transparent to our clients. The basis of speech recognition is a neural network acoustic and language model.

“Tools used by our customers’ analyst every day to analyze their customer interaction leverage AI techniques. These include Search QA, which leverages machine learning-based statistical phrase pattern engine and TopicMiner® for auto topic discovery which leverages NLP vector clustering to identify trends.

“On this foundation of AI, we are poised to do what humans struggle to do. Complex pattern recognition.

“In this amazing 1 trillion word set, are all the patterns in each interaction, across every interaction, are the optimal interaction paths for industries such as healthcare, to ensure accurate resolution.

“Why do consumers call back or cancel a product? The answer is based on every interaction they have had. Or a more complex question: who are our customers?

“What if you could predict who is the perfect person to interact with a customer, the list goes on. The patterns to identify these questions and answers are so close to impossible to see by humans, that it takes artificial intelligence to recognize them.

“This is what we are doing, building the complex mathematics and models to find those patterns, no matter how small, to predict the things that are relevant to every interaction, including yours.”

- CallMiner, Hear from the Experts How AI Drives Better Customer Experiences; X: @CallMiner

The 2024 CallMiner CX Landscape Report is here! One key takeaway? #AI continues to transform the contact center and #CX.

Findings reveal 👇
💡87% of CX leaders say genAI is key for their teams
💡91% agree AI will help optimize #CX strategies
💡and more!

Download the report ⬇️

— CallMiner, Inc. (@CallMiner) September 10, 2024

2. Data gathered by AI tools can deliver pinpointed experiences for each customer. “Hyper-personalization, also known as one-to-one personalization, is a marketing strategy that uses Artificial Intelligence (AI) and machine learning to deliver highly personalized and relevant experiences to each individual customer.

“In today’s digital age, customers expect brands to know them and their preferences. Hyper-personalization not only meets these expectations but also provides numerous benefits for both customers and businesses.

“AI can analyze customer data to create a holistic view of each customer, including their purchase history, browsing behavior, and social media activity. By analyzing this data, AI can make personalized recommendations for products and services, provide targeted offers, and deliver customized content.”

- Elena Gonzalez Castillo, How Can Artificial Intelligence Improve Customer Experience?, Pathmonk; X: @PathmonkTeam

3. Shopping assistants answer customer questions any time of day. “These virtual texting assistants are available 24/7 to address customer inquiries. With this tool, a business has the chance to help a customer immediately, which can make them feel valued and well cared for. It will be important to make sure the shopping assistant has the correct data to use so that the answers are as accurate as possible.”

- Gerard Szatvanyi, 6 Ways AI Can Improve the Customer Experience, Forbes; X: @Forbes

4. Data collected during contact center calls can train chatbots. “Call transcripts from your call center are a data goldmine to train chatbot interactions. Customer service agents see the value of such capabilities – 64% believe AI-powered chatbots will enable them to provide a more personalized experience to customers.”

- Tailor customer experiences with artificial intelligence, CallMiner; X: @CallMiner

5. AI can determine the best streaming experience for TV and movie watchers. “Through ML algorithms, Netflix continuously monitors network conditions and adjusts video quality in real-time to ensure a seamless viewing experience.

“By analyzing bandwidth, device type, and location data, Netflix can deliver the best possible video quality while minimizing buffering and interruptions. As a result, people are likely to stay on the platform due to high-speed performance and faster content loading.”

- Sergey Antonyuk, Netflix and Learn: How Netflix Uses AI to Personalize Recommendations, LITSLINK; X: @LitsLink

6. Analyze historical data with AI to predict the future of your business. “AI’s ability to predict what’s coming next is one of its most powerful features. With AI-driven predictive analytics, businesses can anticipate customer needs, forecast demand and even detect shifts in market trends before they fully take shape.

“By analyzing historical data and identifying patterns, AI can make highly accurate predictions — whether it’s determining which products will be most popular next season or identifying which customers are likely to convert based on past interactions.”

- Brittany Hodak, AI’s Role in Shaping the Future of Customer Experience, CMSWire; X: @cmswire

7. AI can understand complex human emotions and give relevant responses. “For the time being, AI is evolving to understand emotions. Advancements in sentiment analysis and emotional intelligence empower AI systems to gauge customer emotions and respond accordingly.

“These systems decipher nuances in tone, intent, and emotional cues, enabling them to tailor responses with empathy and understanding. By acknowledging and addressing customer emotions, businesses can forge deeper connections, defuse potential issues, and elevate the overall emotional quotient of customer interactions.”

- Venkatesan Gopal, The future of AI in customer service could see 11 significant changes. [A 2024 guide], DevRev; X: @devrev

8. Give AI routine tasks to keep space open for teams to thrive. “By automating routine tasks and providing data-driven insights, AI allows marketing teams to focus on strategic initiatives that drive real value.”

- Optimizing the Customer Journey with Artificial Intelligence, TechFunnel; X: @tech_funnel

9. Augmented reality allows agents to do more for customers. “To define augmented AI, it is the art of enhancing human capabilities using artificial intelligence. Augmented AI in customer engagement refers to the utilization of artificial intelligence technologies to enhance and improve customer interactions and experiences. Rather than replacing human agents, augmented AI amplifies human agents' abilities by providing AI support.

“These AI systems can handle multiple routine customer tasks, analyze extensive amounts of customer data, and offer real-time recommendations to both customers and agents during active customer interactions.

“Additionally, when implemented correctly it allows for an efficient transition between chatbot to agent, achieving a balance of high-speed and high-efficiency customer service with the kindness and nuanced understanding that only humans can provide.

“Augmented AI bolsters businesses' customer engagement strategy by uniting human intelligence with AI capabilities for superior customer communication and personalized experiences, preserving human control over final decision-making. The blend of AI accuracy and human judgment introduces a transformative potential to customer engagement operations.‍”

- Andrea Granados, Optimizing Customer Engagement With AI-Enhanced Platforms, Velaro; X: @Velaro_Inc

10. AI-powered voice assistants give customers quick access to brand information. “Voice assistants like Siri, Alexa, and Google Assistant powered by advanced AI voices are becoming increasingly popular. They leverage AI’s Natural Language Processing (NLP) capabilities to understand and respond to spoken commands.

“These voice assistants can answer questions, place orders, control other devices, and provide personalized assistance based on the user’s history and preferences.”

- 10 Excellent Ways AI Will Improve Customer Experience in 2024, SurveySparrow; X: @SurveySparrow

11. Omnichannel support can be enhanced with AI. “AI can support your omnichannel service strategy by helping you direct customers to the right support channels. And according to our State of Service report, omnichannel support is more a necessity for CS teams than a “nice to have.” In fact, 79% of service leaders say customer service needs to be available across every channel customers use.

“If all of your chat reps are busy taking cases, the AI can tell the customer that they should use live chat for a quicker response. Or if a customer is typing a very long question on your email form, it can suggest that they call in for more personalized support.”

- Alana Chinn, AI in Customer Service: 11 Ways to Use it [+ Examples & New Data], HubSpot; X: @HubSpot

12. Learn how your customers really feel through AI-powered sentiment analysis. “AI-driven sentiment analysis involves using natural language processing (NLP) and machine learning to analyze and interpret the emotional tone behind customer feedback, reviews, and interactions. This technology enables businesses to gauge customer sentiment – whether positive, negative, or neutral – and respond appropriately.

“By analyzing text from various sources such as social media, emails, and customer reviews, companies can gain insights into customer satisfaction, brand perception, and other areas needing improvement.

“For instance, a restaurant chain could use sentiment analysis to monitor customer reviews and social media mentions. The AI system identifies a pattern of negative sentiments regarding wait time at several locations. Using this information, the management can take specific actions to address this issue, such as staffing adjustments or process improvements, thereby directly addressing customer concerns.”

- Nidhi Lohia, 12 Ways Businesses Can Use AI in Customer Service, Hiver; X: @hiverhq

Understanding how customers feel about products, services and brand is hard. But these indicators can help you gauge satisfaction, monitor brand reputation and improve #CX.

Learn more about the importance of sentiment analysis and tips for choosing the right solution.

— CallMiner, Inc. (@CallMiner) March 20, 2024

13. Let AI give customers more options. “For many customers today, the idea of going into an actual store to make a small purchase may seem like a hassle. They could prefer to tell a voice-connected device what they want and have it ordered for them. Or they might want to browse on their laptop at night.

“They may ask a simple question to a virtual shopping assistant and then connect with a company representative for a more complex issue. AI creates opportunities for shoppers to get the information they want when they want it.

“When companies use AI for their customer service needs, employees may find they can focus on individuals and high-level tasks. Buyers might appreciate the flexibility these tools provide. Companies can provide an improved experience, which could lead to higher revenues too.”

- Gerard Szatvanyi, 6 Ways AI Can Improve the Customer Experience, Forbes; X: @Forbes

14. Have safeguards in place to determine when a human touch is necessary. “Sometimes, the last thing a customer wants is to deal with another computer bot. Many people still want human interactions, instant support, and personalized service when it comes to complex customer requests.

“Routine tasks that can be handled by using AI in customer service are fine. But if a customer has a major quality issue with a product or service, human interaction may still be desired so that the shopper is pleased with the overall customer experience.

“The Journal of Retail and Consumer Services published research indicating that customers enjoy the ease and convenience of interacting with chatbots. A bot can be then viewed as an added benefit to a company’s customer service offering because it provides faster service.

“For example, if consumers experience problems while shopping online, they can direct their queries to chatbots and follow the resulting prompts. From there, the chatbots can determine which customers need to be connected with company employees such as the members of a customer service team.

“By maintaining a personal touch in customer service, retailers can build trust, empathy, and connection with their customers. Chatbots may excel at handling routine inquiries, but complex customer issues tend to require a human’s judgment, empathy, and problem-solving skills. Human agents can also provide emotional support throughout the customer life cycle that go beyond the capabilities of AI in customer service.”

- T. Leigh Buehler, AI in Customer Service: Revolutionizing Digital Retail, American Public University; X: @AmericanPublicU

15. AI-powered data analyses can predict and prevent customer churn. “AI is used to predict churn by analyzing historical data to identify at-risk customers. These insights can help companies proactively take action to engage customers and get the chance to improve customer satisfaction.”

- Tailor customer experiences with artificial intelligence, CallMiner; X: @CallMiner

16. Let AI automate and optimize workflows. “AI in customer service can automate workflows, leading to faster support for customers and greater efficiency for agents. Here are a few ways to optimize support workflows with AI:

• Intelligent routing can send customer requests to the right agent based on intent, sentiment, and language.
• AI can analyze ticket context and suggest new pre-written responses to automate.
• AI can summarize tickets for agents so they don’t need to spend hours reading through long conversation histories.”

- Hannah Wren, AI in customer service: All you need to know, Zendesk; X: @Zendesk

17. Uncover trends to shape your customer experience strategy. “AI-driven topic clustering and aspect-based sentiment analysis give you granular insights into business or product areas that need improvement by surfacing common themes in customer complaints and queries. This includes insights on customer demographics and emerging trends—key to guiding your customer care strategy.

“For example, use this data to add more information to your resource center about what your audience cares about or update frequently asked questions (FAQs) from customers. This improves transparency for potential customers in the decision-making phase who are browsing products. It also helps brands cater to existing customers and provide support when they need it without requiring agent intervention”

- Annette Chacko, 8 strategies for using AI for customer service in 2024, SproutSocial; X: @SproutSocial

18. Agents can handle inquiries more efficiently with the help of AI-powered call summarization. “As contact centers collect more speech data, the need for efficient call summarization has grown significantly. However, most summaries are empty or inaccurate because manually creating them is time-consuming, impacting agents’ key metrics like average handle time (AHT).

“Agents report that summarizing can take up to a third of the total call, so they skip it or fill in incomplete information. This hurts the customer experience—long holds frustrate customers while the agent types, and incomplete summaries mean asking customers to repeat information when transferred between agents.”

“Generative AI is powered by very large machine learning (ML) models referred to as foundation models (FMs) that are pre-trained on vast amounts of data at scale. A subset of these FMs focused on natural language understanding are called large language models (LLMs) and are able to generate human-like, contextually relevant summaries.

“The best LLMs can process even complex, non-linear sentence structures with ease and determine various aspects, including topic, intent, next steps, outcomes, and more. Using LLMs to automate call summarization allows for customer conversations to be summarized accurately and in a fraction of the time needed for manual summarization. This in turn enables contact centers to deliver superior customer experience while reducing the documentation burden on their agents.”

- Chris Lott and Smriti Ranjan, Use generative AI to increase agent productivity through automated call summarization, Amazon Web Services; X: @awscloud

19. Monitor the performance of AI tools regularly. “Organizations should stop perceiving AI as another technological advancement. They should gauge the performance of AI projects at regular intervals. Most organizations fail to recognize the RoI from AI implementations as fail to assess the project or follow a wrong methodology for assessment.

“In customer service, AI is often replicating human behavior. Hence the performance also needs to be measured against the customer satisfaction levels and mimicking human behavior.”

- 7 Common Mistakes to Avoid when using AI in Customer Service, Saxon; X: @SaxonGlobalUS

20. Use AI to break down language barriers. “Many AI chatbots and conversational tools have the capacity to generate content in different languages. This is especially helpful if your business operates globally. AI can detect a customer's language and translate the message before it reaches your support team. Or you can use it to automatically trigger a response that matches the language in the original inquiry.”

- Alana Chinn, AI in Customer Service: 11 Ways to Use it [+ Examples & New Data], HubSpot; X: @HubSpot

21. Agents can get better at what they do with the help of AI-based training. “All talent development will benefit from personalized training built on generative AI, but customer service training will see specific benefits. As issues can vary from customer to customer, customer service reps will need to remain agile when assisting customers. By using generative AI to train unique scenarios that could occur in real situations, reps will be more adept at handling whatever customer issue comes their way.”

- Keith O'Brien, 6 ways AI can influence the future of customer service, IBM; X: @IBM

22. Let AI sort tickets to prioritize service. “Triaging refers to categorizing, tagging, prioritizing, and routing support tickets to the appropriate customer service agent or team. The triaging process is a critical part of a well-oiled support operation, as it helps ensure everything is flowing in the right direction at the right time. AI software can help you automate this process by analyzing customer data and inquiries.

“Some of the attributes AI can help identify for triaging tickets include:

• Urgency
• Customer type
• Support channel
• Service Level Agreement (SLA)
• Type of product or service
• Required expertise
• Previous contact or engagement
• Ticket type
• Area of product or service

“Once the ticket is categorized, the AI can prioritize it and ask the right agent to check on and answer it. AI tools can also escalate the ticket to the right person or team.”

- 5 ways to use AI in customer service, PartnerHero

23. AI offers proactive customer service. “Until now, AI’s role in customer service has been largely predictive. Just like a chess player predicting an opponent’s moves, AI would propose the best next action, be it a product recommendation, a beneficial article, or an enticing offer, based on predefined human outcomes. However, generative AI is revolutionizing this process, taking customer service to an entirely new level.

“Generative AI can generate completely new outputs, akin to a seasoned customer service agent who anticipates consumer needs and offers solutions even before they’re asked. It can augment the capabilities of human agents by generating personalized responses, curating relevant knowledge articles, providing instant answers, and crafting accurate case summaries.

“With such tasks handled by AI, human agents can focus on complex, higher-touch interactions that necessitate a human touch. The integration of generative AI offers a promising future, where customer service is not just more efficient, but also more personalized and satisfactory.”

- Clara Shih, How Generative AI Will Revolutionize Customer Service, Salesforce via WSJ Business; X: @Salesforce

24. AI can automate inventory management for retail businesses, in turn improving CX. “H&M, a global fashion retailer, uses AI to optimize its supply chain and enhance inventory management, ensuring that products are available when and where customers want them. AI algorithms analyze sales data, weather patterns, and local trends to predict demand and adjust inventory levels accordingly, reducing stockouts and excess inventory. This use of AI has improved H&M’s operational efficiency and customer satisfaction by ensuring a more consistent shopping experience.”

- Customer Experience (CX) with AI: How to Leverage Artificial Intelligence, Renascence

25. Give customers what they need while optimizing revenue growth with AI. “AI can drive upsells and cross-sells during support interactions by analyzing customer data and identifying relevant products or services based on individual preferences and purchase history. During support conversations, AI can suggest complementary items or upgrades in real-time, seamlessly integrating these recommendations into the dialogue.

“By understanding customer needs and contexts, AI enhances the chances of successful upselling while providing value to the customer. This proactive approach not only boosts sales but also enriches the customer experience by offering solutions that genuinely meet their requirements.”

- AI in Customer Service: 10 Ways to Implement It with Best Practices, Kipwise; X: @kipwise_com

CallMiner’s CMO, @edubble_u, shared powerful insights into the future of #AI-driven work on the @dotCMS podcast.

He discussed 👇
✅ Leveraging automation to streamline routine workflows
✅ Replacing repetitive tasks with AI solutions
✅ and more!

Listen now. 🎧

— CallMiner, Inc. (@CallMiner) November 14, 2024

AI is transforming customer engagement, from automating support to delivering personalized experiences. Businesses that leverage AI gain a deeper understanding of their customers and position themselves to better meet customers’ needs, giving them a competitive edge.

A conversation intelligence solution like CallMiner analyzes 100% of customer interactions across channels, offering detailed insights into customer sentiment, behavior, and emotion. Companies can leverage these insights not only to enhance customer experience but also to streamline business processes across departments.

Schedule a demo today to discover how CallMiner can elevate your company’s CX.

Frequently asked questions

How does Netflix use AI to improve customer experience?

Netflix is known for its highly personalized content suggestions that display on your main page as you scroll through your account. This personalization feature uses AI to give recommendations based on your viewing history and preferences. Netflix continues to gather your viewing data to keep enhancing your personalization experience every time you log on.

How is Starbucks using AI to improve customer experience?

Starbucks uses AI in several ways to enhance the customer experience, including allowing it to manage inventory by collecting data about past customer behavior and predicting future trends. Starbucks also has an AI-powered mobile app that gathers data about your past orders and offers recommendations based on the drinks and food you usually order. The app also suggests items that pair well with drinks or food you already have in your cart.

How can AI improve customer success?

AI can create happier customers when it’s used in conjunction with human agents. AI tools can automate routine tasks, direct customer inquiries to the right places, and answer frequently asked questions to give customers the information they need quickly. Predictive analysis can also support proactive customer service, like predicting what customers might want to see more of in the upcoming months or suggesting items that customers could find helpful based on their past shopping habits.