AI in Customer Experience: Business Impact & Signs to Look For

May 2, 2024 8 min read

Robert Pleasant

Robert Pleasant

AI-powered Customer Experiences

Artificial intelligence (AI) has grown exponentially over the past few years and has quickly become prevalent across several industries. Nowhere is this more evident than in customer service, success, and support, where AI is used in everything from giving customers self-service options to supporting agents during calls.

It’s impossible to overlook the impact AI has had on the customer experience (CX). Let’s explore how contact centers use AI technologies (like generative AI), the impact on CX, and whether you should invest in AI for CX.

How Can AI Impact CX in Contact Centers?

Let’s examine the CX and uses of AI in a contact center environment. AI can be used across customer touchpoints and in every step of the support journey, and it can also assist with essential behind-the-scenes processes.

Some of the most impactful use cases of AI for contact centers are:

Intelligent virtual assistants and chatbots

One of the most popular ways of using AI for CX is the deployment of AI-powered chatbots and virtual assistants. These can be used to handle routine inquiries and transactions, allowing customers to get help quickly and agents to focus on more complex issues.

While older self-service menus may have limited responses based on specific options, AI-powered chatbots can provide a better range of responses and support capabilities, based on natural language instead of a dialogue tree menu. These tools can provide fast, uninterrupted customer service around the clock, without needing a human agent.

Enhanced personalization

Today’s customers want a personalized experience based on their history and past service interactions. With AI, that kind of experience is now possible.

AI-powered tools can analyze customer data and interaction history, enabling agents to give responses and solutions tailored to the individual customer. This can significantly improve customer satisfaction and help ensure customers get the exact help they need.

With the right AI-powered solutions, you can even predict customer issues based on their support history and proactively offer solutions or assistance. The customer journey becomes a lot easier when they receive support before they even need to ask.

Improved agent assistance and productivity

AI can help agents as well as customers. While AI cannot and should not replace human agents altogether, by using AI-powered solutions, you can support and assist agents to improve productivity across the board.

AI customer experience tools provide agents with prompts, scripts, and information in real time during customer interactions, which can help improve response speed and quality. AI can also automate repetitive tasks like call logging, data entry, and ticket classification, lightening the agent’s workload and helping them to be more efficient. Generative AI is increasingly used to provide interaction summaries and wrap-up, reducing the time spent on post-call work.

Quality assurance and training

Monitoring interactions and providing feedback is essential, as it keeps agents fully trained and compliant with quality standards. This is another area where AI-powered tools can help improve efficiency and CX.

AI-powered QA tools can monitor interactions and provide automated feedback to agents, identifying areas of improvement and success. If an agent needs extra training or assistance, you can use insights from these QA tools to develop targeted training programs.

With this combination of monitoring and training, you can ensure your contact center agents are meeting quality standards and providing great CX.

Sentiment analysis and emotional intelligence

How can you be sure your customers are truly getting a great experience? Customer sentiment analysis tools can use AI technology to gauge customer emotions during calls and provide feedback, allowing agents to adjust their approaches and achieve better results.

With training, AI-powered sentiment analysis systems can recognize and respond to emotional cues, giving agents insights and suggestions. This can help ensure interactions are not just efficient, but also empathetic.


Predictive analytics for workforce management

One of the biggest challenges any contact center faces is staffing. Having too few agents available results in overly long wait times, fatigued agents, and frustrated customers, but having too many agents means you’re wasting resources.

AI-powered customer experience tools can predict call volumes based on historical data, enabling more accurate staffing and resource allocation. Contact center managers can use this information to optimize agent schedules and breaks, ensuring the contact center is always staffed appropriately.

Fraud detection and prevention

Fraud is a major issue for any business, but AI can help detect and prevent it. Customer management tools can analyze patterns and flag potentially fraudulent activities, quickly alerting fraud prevention teams and agents. This helps protect not only the organization but also its customers.

Seamless omnichannel experience

Today’s customers expect to connect with businesses across multiple channels, including email, phone calls, and social media. Contact centers that want to provide a great experience need to embrace omnichannel communications with seamless communication across each channel.

Contact centers can use AI to integrate data across channels, including all the customer’s touchpoints in their personalized experience. This helps ensure a consistent experience, whether the customer is using a phone, web chat, email, social media, or any combination thereof.

Additionally, AI tools can analyze customer behavior, helping you understand what channels your customers prefer. This allows you to tailor your customer engagement strategies accordingly, ensuring that customers can interact through their preferred medium and always get the help they need.

omnichannel vs multichannel

7 Signs It’s Worth Using AI in Customer Experience

Given all the benefits of AI, it can be an appealing prospect to many contact center managers, regardless of their industries. If you’re facing any of the following challenges, then integrating AI technology or switching to an AI-powered contact center may significantly improve both your operations and CX:

1) Handling a high volume of customer inquiries

If you’re receiving a significant volume of questions from your customers, then AI automation can help. Adding AI-powered self-service options, task automation, and agent assist features can help reduce both the number of calls agents have to handle and the average time each call takes.

2) Facilitating personalized experiences

Customers expect an experience tailored to their needs. Can your contact center provide that? If your customers have ever complained about calling multiple times but the agents have no records of their previous calls, or if they have to repeat themselves each time they interact with a different agent, then AI-powered tools can help.

The right tools can deliver personalized experiences at scale, enabling you to give your customers the unique service they deserve.

3) Scaling your sales and support operation

As your business grows, your contact center will need to grow along with it to keep up with the influx of customers. However, scaling contact center support alongside business growth can prove more difficult than anticipated.

AI solutions can often help with scaling customer support, both through the flexibility of the platform and with the workforce management capabilities they provide. These can help ensure your contact centers are always properly staffed.

4) Tapping into existing customer data

Every customer interaction is a treasure trove of data, but there’s often too much information to sift through properly. AI-powered solutions can address this, as AI tools can analyze vast quantities of unstructured data and generate actionable insights.

5) Increasing customer customer retention

If you’ve been losing customers, it’s important to understand why. Poor CX can decrease customer satisfaction and loyalty, driving customers towards your competitors.

However, using AI to improve CX can boost customer retention by ensuring support experiences are efficient and helpful. The efficiency, accuracy, and speed of AI-enhanced customer support will keep loyalty high and churn low.

6) Fixing operational inefficiencies

If you’re spending too much on operations and processes, yet still moving slowly, AI-driven automation may be the solution. AI can efficiently automate repetitive manual tasks, making agents and teams more efficient while keeping operational costs low.

7) Improving customer service response times

Many issues can slow down response times — too many customer calls, too few agents, complex issues that require extra time to resolve, and so on. AI can help address all these problems by letting customers access immediate self-service tools and chatbots, assisting agents on calls, and helping with workforce management and scheduling.

Nextiva Contact Center AI for Improving CX

It’s clear that AI can improve CX in several ways, from helping customers with self-service to improving agent productivity. AI technology has had such an impact on contact centers that it’s hard to find any element of CX that it hasn’t enhanced in some way, and those who ignore AI risk falling behind the competition.

If you’re ready to integrate AI into your contact center as part of your CX strategy, Nextiva is a top-ranked AI-powered contact center platform.

Nextiva’s AI-powered features include:

Upgrade your customer experience.

All conversations in one platform. Empowering agents. Satisfying customers.

FAQs on Using AI in Customer Experience

What are AI and ML, and how do they improve CX?

AI is a technology designed to simulate human intelligence. Modern AI-powered tools can take different forms, including technology that analyzes vast quantities of data to develop actionable insights and conversational AI that uses natural language processing (NLP) to understand speech and create responses.

Machine learning (ML) is a branch of AI and computer science that uses data and AI algorithms to “learn,” identifying patterns and improving the accuracy of the generated responses over time.
Used together, AI and ML improve CX in several ways, including understanding and responding to user queries, providing valuable insights into conversations, and automating manual tasks for agents.

How many companies use AI in customer service?

Research from Forbes shows that over 56% of businesses use AI to some extent in their customer service. As the technology continues to develop and the benefits AI brings to customer service become more evident, that percentage will continue to rise. In fact, around 73% of businesses already plan on using AI-powered chatbots, while others intend to use AI to optimize emails or provide personalized services.

Organizations are also using AI for fraud management, customer relationship management, and personalized product recommendations. The percentages vary across industries, but a comprehensive 2023 study by Capgemini found that 63% of retailers use AI in customer service.

What are the risks or disadvantages of using AI?

AI is still a developing technology, so it is not without risks. To ensure your customers and agents receive proper assistance, you need a contact center platform with reliable, proven AI-powered tools and a track record of quality and accuracy.

Generative AI, for instance, is often prone to “hallucinations,” where it essentially makes up information based on patterns, making it wildly inaccurate. As such, using generative AI to communicate directly with customers is risky. A human element is still essential to ensure everything remains accurate and helpful.

Robert Pleasant


Robert Pleasant

Robert Pleasant is an experienced content writer, having begun his career as a freelancer for BCStrategies before moving on to work for several tech and unified communications companies, including ShoreTel and Dialpad. He currently works as a freelance writer, bringing his experience in UCaaS, CCaaS, and AI to news sites and blogs across the communications…

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