AI Customer Service: All You Need to Know + Examples

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. 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. By creating hyper-personalized content and engagement driven by audience sentiment, they’re reinventing how customers interact with a brand.

This includes customer service chatbots that instantly respond and resolve issues, and are available round-the-clock. The customer service and support function is vital to maintaining customer loyalty and influencing brand perceptions. Leaders in AI-enabled customer engagement have committed to an ongoing journey of investment, learning, and improvement, through five levels of maturity. At level one, servicing is predominantly manual, paper-based, and high-touch.

Choosing AI: The smart decision for customer service

It collaborated with IBM to develop an AI customer service chatbot that customers access on the web or their mobile app to place orders. 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. 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. Lyro is operated by a powerful machine learning algorithm that makes it a very effective chatbot.

• By leveraging tools like CallRail’s conversation intelligence software, customer service teams can operate with heightened efficiency, ensuring improved customer experiences.
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• Miami-based health and fitness company, Sensory Fitness, provides a holistic gym experience that includes intense workouts and restorative stretching and recovery programs.
• When used effectively, chatbots don’t simply replace human support so much as they create a buffer for agents.

Working in customer service is notoriously stressful—it was named one of the world’s top 10 most stressful jobs—and companies see turnover rates of up to 45% of agents every year. That has led to a massive talent shortage and is costly for companies to continually recruit and train new employees—all of which affects the customer and employee experience. At present, the most suitable approach includes building a customer-facing application based on a combination of traditional AI, such as machine-learning systems, LLMs, and prompt engineering. This final element involves developing and optimizing the information and constraints provided to LLMs to improve the accuracy of the answers—defining company-specific keywords within the prompt itself, for example. This process allows companies to achieve better levels of control, moderation, and personalization. And when the data on which they are trained is adjusted, these algorithms can be fine-tuned to better suit specific industry and company needs.

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This powerful technology has the potential to disrupt nearly every industry, promising both competitive advantage and creative destruction. Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. Today, we work closely with clients to embrace a transformational approach aimed at benefiting all stakeholders—empowering organizations to grow, build sustainable competitive advantage, and drive positive societal impact. Companies have yet to proceed through all of these stages, but many are already imagining how a fully AI-enabled customer care center might work. Sprout Social helps you understand and reach your audience, engage your community and measure performance with the only all-in-one social media management platform built for connection.

When you see a certain word or phrase keep repeating, this could mean that there’s a constant problem with a particular aspect of your product. We all make mistakes—but AI-based models are trained to be accurate and precise. This makes problem-solving much faster and improves the overall customer experience.

How to get started with AI in customer service

The honorees demonstrated extraordinary advances toward the future of trusted communications and customer engagement and proved the real promise of generative AI. In fact, the share of service decision makers who report using AI has increased by 88% since 2020 — up to 45% from 24%. The impact of these converging forces cannot be overstated, because a multiplier effect causes the technologies’ disruptive potential to become exponentially higher as they operate collectively. What’s more, as customer demands intensify, it will be critical for companies to understand how users embrace these evolving technologies. For example, if you have automated text analysis, you can process a number of customer messages.

It all depends on your needs and processes, and your desired use for AI customer support solutions. Getting started with customer service automation is a straightforward process when you’ve got the right tools. With automation tools, you can detect languages and provide a response in your user’s preferred language.

Use cases for AI in customer service

Chatbots can answer common questions with canned responses, or they can crawl existing sources like manuals, webpages, or even previous interactions. When it comes to customer service, companies use AI to enhance the customer experience and enrich brand interactions. Instead of spending all of their time responding to client queries, service personnel have more flexibility to focus on activities that truly require human-to-human interaction.

As the demand for an improved and personalized customer experience grows, organizations are turning to AI to help bridge the gap. You can scale your customer service with the power of generative AI, paired with your customer data and CRM. See how this technology improves efficiency in the contact center and increases customer loyalty. Increased efficiency and quality of your customer support processes lead to happier customers. They become brand advocates and boost the reputation of your business—good testimonials attract more customers and lead to higher revenues. Using AI for customer support automates many processes and saves you a lot of time and money.

One of the primary challenges enterprises face today is delivering the highest level of service. With the ever-increasing clients’ demands, businesses have to continuously seek more efficient tools and technologies. The initial version of the tool will provide support on the relatively simple requests that make up about 30% of total support tickets, such as how-to guides and basic product configuration information. As the technology matures, the company hopes to expand the range of use cases to cover more complex requests such as fault finding and fixing. But LLMs have the power to significantly expand what can be automated, performing critical customer service tasks that are far beyond the capacities of earlier technologies. These models are trained on vast amounts of data and can recognize, classify, and create sophisticated text and speech with speed and precision.

It started with piloting its first chatbot, Lionel, which was quickly followed by Marie, and, finally, Inge. Myntra, a leading e-commerce platform owned by Walmart, has recently revolutionized the online shopping experience by introducing MyFashionGPT, a feature powered by ChatGPT. Netflix uses AI to streamline the production of its original content, ensuring they create movies and TV shows that resonate with its viewers. A crucial feature was Dynamic Content, which translated website text based on location and other attributes, effectively supporting their multilingual customer base. With the help of tools like HubSpot’s ChatSpot, which harnesses the power of Generative AI, the possibilities extend beyond mere conversation.

AI customer service: key takeaways

There are plenty of advanced tools, and many systems are also able to learn from each conversation they have with visitors. AI swiftly analyzes vast customer data, empowering businesses to gain profound insights that escape the naked eye. By utilizing the analysis power of artificial intelligence customer support AI, you can extract information from siloed customer touchpoints, process raw data into actionable insights and detect patterns in customer behavior, market trends and recurring issues. Before we discuss these use cases, let’s understand what AI in customer service is.