Scroll Top

How to use AI to deliver better customer service


Customer service teams are constantly under pressure. While customers expect them to respond immediately and know all the answers, siloed teams, opaque workflows and fragmented customer data across channels add to the challenges support teams face on an ongoing basis. They need the right tools to make swift, efficient decisions and provide the kind of personalized customer care needed in today’s competitive environment.

Luckily, innovations in artificial intelligence (AI) like generative pre-trained models (GPT) and text analytics are transforming how customer care teams operate. They help you build world-class customer care by tracking and unifying messages from different channels, creating workflow transparency, reducing support times and pinpointing key insights about what customers want—or don’t—from your brand.

In this guide, we’ll give you the scoop on what AI customer service entails and how to use it to your advantage. Plus, you’ll see examples of how other companies are using it to elevate their customer service.

What is AI customer service?

AI customer service is the use of AI technologies like machine learning, natural language processing (NLP) and sentiment analysis to provide enhanced, intuitive support to current and future customers.

Graphic defining what AI in customer service means

AI customer service tools use neural networks (NNs) and machine learning to draw insights from common themes and topics in customer interactions and learn from them. This, combined with GPT capabilities, makes them increasingly intelligent with time and gives customer care teams the context needed to provide personalized, timely support.

The benefits of integrating AI into your customer support channels

AI-supported customer service helps businesses refine and scale their support functions without overwhelming agents. Here is a closer look.

Scale your customer care functions

According to The 2023 State of Social Media report, 93% of business leaders believe AI and ML capabilities will be critical for scaling customer care functions over the next three years.

Machine learning elevates support functions across channels, including social media customer service, effortlessly with intelligent automation. This includes customer service chatbots that instantly respond and resolve issues, and are available round-the-clock.

AI technologies like NLP also analyze chatbot data to identify recurring themes in customer conversations so you know what is top-of-mind for your target audience.

Deliver more proactive customer service

More than 40% of the same business leaders believe sentiment analysis is one of the most essential applications of AI and ML, specifically to understand customer feedback and respond to issues in real time.

Sentiment analysis algorithms identify positive, negative and neutral sentiments in data, while machine learning helps make sense of large amounts of disparate data from multiple channels.

Combined, you get key insights into how to plan for emerging trends and provide proactive customer service to keep customers happy. For example, with relevant data at hand, you could know when to pause targeted ads to customers with an active support ticket until their issue is resolved.

Screenshot of a customer expressing delight over Sprout's customer service

Elevate customer support with social media listening 

Per the same research, 62% of leaders say social media data is critical to their customer service functions. And 59% say they expect to rely more heavily on social data for customer support moving forward.

From trending topics to competitor insights, social media listening offers you actionable insights to improve your customer service across channels.

AI tools like Sprout analyze tons of social listening data in minutes so you can make data-driven decisions based on the conversations happening around your brand and industry. For example, customer care teams can use social listening to get ahead of product defects or service issues if they see similar complaints across social.

Improve the quality of customer support chatbots

Among the leaders surveyed, 41% feel NLP will be crucial in improving customer interactions through virtual assistants and intelligent chatbots.

Flexible and intuitive, AI chatbots are driven by NLP, natural language generation (NLG) and neural networks. They understand and identify customer requests more easily and interact with users in a natural, human-like manner, plus remember those interactions.

For example, they can direct customers to live agents in the relevant department or ask for more information to provide a solution—giving you the perfect balance between machine efficiency and human expertise.

Screenshot of the UPS virtual agent offering advise contextually to responses from a customer

5 ways to use AI in customer service

Here are five tangible ways AI customer service empowers your team and protects customer relationships.

Graphic containing the 5 ways in which AI boost customer service

1. Set up customer service chatbots

Conversational AI customer service chatbots are trained to understand the intent and sentiment behind customer queries, making them ultra-efficient. They chat with customers casually to create a more human experience and handle large volumes of messages effortlessly. Every interaction adds new words, phrases and trending topics to their neural networks for future reference, so they can get better at offering the right resolution.

Integrating chatbots into your customer service operations helps customers connect with you on- or off-business hours and get timely, efficient assistance even when your staff is unavailable.

For example, online travel agencies Priceline and are expanding their customer service offerings to include AI chatbot, Penny, in collaboration with ChatGPT. The chatbot is accessible as a 24/7 concierge, helps customers complete bookings and acts as a local guide to enhance guest experience.

If you prefer a rules-based chatbot over an AI, you can create one within minutes using Sprout’s Bot Builder on your Twitter and Facebook accounts. Just select your chatbot profile and follow the wizard for instructions.

If you choose to go with a template, you will get a decision tree with predetermined rules and script options that will automatically populate in the configuration stage. You can also add additional rules, write custom copy for your chatbot responses and add pictures and GIFs. Once it’s set up, all customer conversations will stream directly into the Smart Inbox.

2. Analyze customer sentiment

Customers are spoiled for choice and difficult to hold onto. That’s why sales and marketing teams are teaming up with customer service to understand and overcome barriers to the traditional marketing funnel.

Companies like TikTok are already attuned to this new phenomenon. By creating hyper-personalized content and engagement driven by audience sentiment, they’re reinventing how customers interact with a brand.

AI capabilities like sentiment analysis draw insights from hundreds of customer conversations on social channels, CRM tools, chatbots or customer support calls to surface hidden sentiment on a variety of topics (including your competitors). You also get metrics on customer behaviors, purchase motivations and brand health—critical to customer service teams. For example, they may use this data to monitor tickets and take appropriate steps to avoid escalations.

These insights are also essential to cross-organizational teams, like marketing and sales, so they can adapt their efforts to better meet customer preferences. Think: Tailoring ads based on customer demographics, or differentiating messaging based on competitor insights from social listening.

Screenshot of Sprout Social’s Listening tools showing active topics from a range of social networks

Sprout enables you to track and analyze the sentiment of your social mentions on various networks and review platforms like Twitter, Instagram, Facebook and Google My Business.

You can narrow sentiment search with keywords or within specific queries including complaints, compliments and specific customer experiences, all in one place. Use the sentiment analysis widget to monitor positive, negative and neutral mentions in real time or track changes in sentiment over time.

3. Quickly personalize customer interactions

Customers don’t want to be nameless—they want to have a personal connection to your brand. And empathetic, personalized customer service is essential to that end. It increases customer engagement, builds loyalty and fosters long-lasting relationships.

But writing tailored responses to every customer complaint and query isn’t sustainable especially when your team is managing customer requests from multiple channels.

This is where AI-enabled tools like Sprout level up your customer care tech stack.

For example, Sprout’s Suggested Replies help your teams respond faster to commonly asked questions on Twitter. They are powered by ML and semantic search algorithms that enable the tool to automatically understand the context of an incoming message.

These algorithms identify topics and themes, and suggest responses that are best applicable. Plus, your teams have total control over these messages to customize them for a more personalized feel and to add relevant details.

Sprout’s Enhance by AI feature, powered by our OpenAI integration, further boosts this capability. Customer service teams may quickly adjust their response length and tone to best match the situation.

Screenshot of how customer care teams can quickly customize messages and add relevant details for a more personalized feel when responding through Sprout Social

4. Increase team productivity

Employee burnout is a real issue for customer care leaders across industries, and AI customer service provides a much-needed respite. Intelligent tools make workflows transparent so team members have a unified view of all customer messages in a central location and task visibility to overcome duplicacy.

For example, ING Turkey collaborated with conversational AI company, Sestek, to develop an intelligent, conversational interactive voice response (IVR) system to manage collection calls that are automatically diverted to it. This increased efficiency, freeing up support staff for other valuable interactions.

The AI tool handles complex customer interactions effortlessly and reduces the workload of ING’s overwhelmed customer service team by half. It has also lead to increased customer payments by 60%.

5. Collect trends and insights

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 enrich your resource center with information covering what’s most important to your audience or update frequently asked questions (FAQs) from customers. This improves transparency for potential customers in the decision-making phase who are browsing products.

Sprout’s AI and machine learning capabilities enable you to extract key insights from social and online customers to give a centralized view of customers’ feedback and experiences. Your teams never miss a message and resolve queries with contextual insights for swift, meticulous service.

3 AI customer service examples

These three examples highlight how AI customer service is empowering brands in innovative ways.

1. Uber

Rideshare and transportation company, Uber, is committed to enhancing user experience and elevate its customer service with AI. The company’s in-house team of data scientists have built conversational AI that empowers Uber’s customer support teams to resolve issues swiftly and efficiently. The tool also enables more seamless interaction between drivers, partners and customer care staff for better communication and road safety.

Uber is further using AI to provide more precise locations to increase the accuracy of driver-rider matches and accurate estimated arrival times, which has lead to fewer cancellations and customer care issues.

2. 1-800-Flowers

1-800-Flowers is an online flower and gift delivery service with 93 locations in the US alone, and provides service internationally.

It collaborated with IBM to develop an AI customer service chatbot that customers access on the web or their mobile app to place orders. Built on conversational AI, 1-800-Flowers’s chatbot, GWYN (a clever play on words that’s an acronym for “gifts when you need”), converses with customers in a human-like manner and offers personalized suggestions based on different queries.

Screenshot of 1-800-Flowers’s chatbot, GWYN offering personalized suggestions based on different queries

With the virtual assistant in place, customers get service 24/7, regardless of where they are located or which time zone they are in.

3. Sensory Fitness

Miami-based health and fitness company, Sensory Fitness, provides a holistic gym experience that includes intense workouts and restorative stretching and recovery programs. To meet the needs of a fast-growing clientele, they collaborated with AI company, FrontDesk AI, to develop a personalized AI virtual assistant, Sasha, to enhance their customer service capabilities.

Customized to reflect Sensory Fitness’s brand voice, Sasha speaks to customers in a conversational manner and provides assistance in various ways—from booking and rescheduling appointments to onboarding new customers. Powered by neural networks, Sasha remembers each caller’s history and service preference, and on average, answers 160 calls that would otherwise go to voicemail.

Integrated with the company’s booking app, the AI customer service assistant resulted in operational savings of more than $30,000 in a year.

Champion better support and happier teams with AI customer service

As customer care leaders, your ultimate aim is to capture and deepen customer loyalty. AI in customer service helps you design personalized experiences to reach this goal. Powered by AI chatbots, customized messaging and intelligent workflows, it empowers your teams to support customers confidently wherever and however they interact with your brand. And social data is key to striking that balance between scalable automation and personalized service.

Learn more about how business leaders are investing in social media and the role AI will play in harnessing social data and insights across their organization, in The 2023 State of Social Media report.

Related Posts