Companies that deem excellent CX one of their core values are likely to actively use AI in customer service, internal operations, and broader CX tasks: , , and so forth. Business apps based on machine learning, natural language processing (NLP), predictive analytics, robotic process automation (RPA), and other AI technologies are quite widespread.
But there's a lot going on when it comes to artificial intelligence and customer experience. New AI tools, features, and possibilities to accelerate customer support, enhance personalization, and whatnot are emerging by the month. For instance, generative AI solutions are now so diverse and multifaceted it's easy to overlook many of them.
This guide is all about these more modern AI applications improving customer experiences. We'll explain how AI can transform your CX in 2024 and down the line, discuss newer use cases, take a look at some examples, and check stats.
Table of Content
1. Five Benefits of AI in Customer Experience
Reaching high levels of customer satisfaction and turning one-time purchasers or visitors into regular and loyal clients is hardly possible without a pleasant customer experience. In turn, this feeling about the brand forms largely based on how personalized the customer journey is and how fast, quality, and proactive customer service is. Let's see how AI-enabled solutions can help.
1.1 Reaching Back to Customers Faster
The speed of reaction and customer case resolution matters like never before. In a recent survey by Salesforce of 14,000+ B2C and B2B buyers, stated they expect no less than immediate replies when they contact a company.
Having AI-powered tools alongside human agents is a surefire way to fulfill this requirement and a working alternative to expanding service teams. In another Salesforce survey of 2,000+ service professionals, said generative AI will help them serve customers faster.
In 2024 and beyond, the potential of AI-powered software to expedite customer support tasks is immense, from handing over tasks to to creating emails with the help of LLMs to implementing advanced, smarter virtual assistants.
1.2 Customizing Experiences Deeper
While each and every prospect will definitely be attracted by a plain discount, businesses understand how crucial it is not to overuse this instrument. A survey by PwC of 400+ executives showed that name personalizing the customer experience as their highest priority amongst all loyalty activators.
Integrating AI for personalized experiences takes many forms. Artificial intelligence tools excel at aggregating and analyzing all available customer data (purchase history, previous conversations, customer sentiments, real-time customer behavior) to adjust messaging and offerings or comprehensively inform CX managers taking the case.
1.3 Optimizing a Host of Workflows
Facilitating a smooth customer journey for every single person in your clientele is no mean feat! Fortunately, numerous capabilities of help fully automate some processes and significantly streamline others.
But if almost all companies use tools leveraging ML models for all sorts of customer data analysis tasks, DL models, e.g., powering content creation, are still relatively new and even doubtful for many businesses. The same is true for complex solutions like AI copilots in CRMs and other business apps.
It's definitely high time to learn more about these opportunities and tap into them. AI can sum up the info, craft emails or chat messages, and create knowledge-base articles for human agents to review, edit, and send. With the proportion of routine manual work reducing and the quality of insights rising, customer success teams will perform far more efficiently.
1.4 Working Genuinly Proactively
AI-powered predictive analytics tools process "everything everywhere all at once," spotting opportunities for proactive moves. Based on recent customer activities, lack of activity, or some milestones (birthday, membership anniversary, etc.), managers receive prompts for the next best actions.
In practice, it feels like a whole new level of personalized support for customers. They can get reminders on the subscription renewal date or the need to reorder consumables, emails with discounts on relevant items for their special occasions, and so on.
1.5 Increasing Company's Efficiency
Even theoretically, a CX team relieved from monotonous, trivial, repetitive tasks is able to deliver better customer experiences because it simply has more time and drive to resolve more complex cases. AI-powered tools, therefore, increase staff productivity and decrease burnout.
At the same time, active AI evolution and a growing number of AI tool providers make the tech more affordable for businesses of all sizes. If you operate an SMB, you might think it's too costly to implement AI in the first place, let alone save costs with it. Now, it's not the case, with so many ready-made apps, subscription-based solutions, and powerhouse models available for fine-tuning. For instance, explore our page to get acquainted with some options.
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2. Four Modern Ways to Enhance Customer Experience with AI
So, it goes without saying that artificial intelligence is getting better at facilitating a customer journey and CX in multiple aspects: communication across channels, email send-outs, product recommendations, troubleshooting, and more. Let's see what the core components of your AI for customer experience system could look like.
2.1 All Sorts of Content-related Tasks
The emergence of gen AI was a real breakthrough, making it possible to expedite numerous content-related business processes. Many still don't even realize how many applications there are for LLMs in both day-to-day workflows and strategic tasks. Here, we'll focus on how customer-facing specialists can utilize newer AI features for content generation.
- Respond to customer queries quickly and comprehensively. When digital agents (chatbots) escalate cases or support teams get emails they need to handle manually, AI embedded in CRMs and other business tools (like Einstein AI in Salesforce) can be of great assistance. Artificial intelligence can analyze, sum up, and present customer data as well as generate a first answer draft, helping to address the issue faster and type less.
- Manage knowledge bases. Gen AI helps customer service teams create and update content for FAQ pages, self-service portals, and knowledge bases. With an LLM fine-tuned on your business data, it takes a brief prompt to write a full-fledged help center article in line with the brand voice.
We need to add a caveat, though: artificial intelligence inevitably makes mistakes, hallucinates, and gives biased or redundant answers, no matter how powerful and up-to-date the model is. Therefore, human supervision, with exceptional reasoning, empathy, and common sense, is a must to live up to customers' expectations.
2.2 Intelligent Case Escalation
Oftentimes, customer questions require human intervention, and AI is indispensable in organizing the whole process. Features such as intelligent triage, routing, and sentiment analysis rely on machine learning, NLP, and other AI technologies to understand what the request is all about and what to do with it next.
First, AI identifies customer needs, intents, and emotions. Then, issues are escalated to corresponding service agents. These tools can also direct tickets to the most relevant managers experience-vise and prioritize queries by prevailing customer sentiment (simply put, serve angrier clients first). See the example of this functionality in the Zendesk customer service app.
Sentiment analysis can go beyond the current case. By examining data gathered from previous interactions (chats, emails, socials, records in call centers) as well as reviews and purchase history, AI can draw conclusions on the prevailing customer sentiments. Having these valuable customer insights, CX managers are well-prepared for future conversations.
2.3 Smarter Human-Chatbot Conversations
A classic form of augmenting and reinforcing CX teams is AI chatbots, and the advancements in this area are impressive. Now, round-the-clock availability, instant answers to FAQs, and cheapness aren't the only arguments in favor of AI-powered chatbots. Rule-based and conversational AI bots are gradually replaced by sophisticated gen AI ones, with previously unimaginable levels of comprehension, accuracy, and helpfulness. See the example of a convo with Delta Airlines's virtual assistant.
Integration capabilities are also improving. Businesses can deploy a web of chatbots across multiple channels: on social media and messengers, implement a chatbot on the website and app, in email and live chat.
2.4 Accurate Predictions and Relevant Personalization
Being able to process big data, AI models are the best option to identify patterns in customer behavior, but their work doesn't necessarily end there. Let's take customer churn predictions. AI can not only anticipate the outcome but also prevent it from happening by suggesting actions: contacting clients, offering discounts, etc.
With thousands and thousands of buyers or subscribers, we physically can't come up with ideas and execute them for each person or org at risk. But AI can do it for us: constantly analyze the incoming data, notify us about the cases demanding attention, provide suggestions, and craft personalized messages. is an excellent example of such AI-powered features.
Modern AI solutions hugely enhance recommendation systems. Based on historical and real-time customer interactions with the site or app, they can correctly anticipate customer needs and showcase similar/complementing items and promotions on product pages, in the cart, in the chat pop-up, in emails, etc.
AI and Customer Experience: Seize the Opportunities
We're all getting increasingly demanding and impatient when it comes to any B2B or B2C brand interaction, be it online shopping, emailing a company for a quote, or writing via a chat because of an issue. Being customers themselves, we know first-hand that it's fast, convenient, and seamless CX that drives customer satisfaction. And now, creating real omnichannel customer experiences is more than possible, given today's level of artificial intelligence evolution.
Of course, it's easier said than done. Firstly, there are indeed too many AI models, AI tools, AI-driven solutions, and providers. What you need is a well-defined, solid, and cost-aware AI customer experience strategy to make it all work really efficiently and not overshoot the budget.
Secondly, business leaders can't rely on AI algorithms only when they want to keep customer experiences flawless - because AI is flawed. The best AI customer experience strategy is to augment your teams with AI in the optimal proportion.