23 Best Chatbot Use Cases for Customer Service & More 2024

Generative AI can produce high-quality text, images and other content based on the data used for training. Not only does automation directly influence how many people actually end up speaking to an agent, it makes everyone’s lives easier once they do speak to an agent. Automation can make sure the inquiry is routed to the right person and the ticket is filled with information that’ll help resolve cases faster, driving down labor costs. Say No to customer waiting times, achieve 10X faster resolutions, and ensure maximum satisfaction for your valuable customers with REVE Chat. In your business, you need information about your customers’ pain points, preferences, requirements, and most importantly their feedback. FitBot is the way trainers communicate with clients, both onsite and remote coaching.

To delve deeper into how generative AI has changed customer service – check out the 20 new use cases below. Such innovation has changed how many contact centers build bots, self-service applications, and proactive campaigns forever. Netflix’s use of machine learning to curate personalized recommendations for its viewers is pretty well known. Duolingo Max has generative AI-powered features that allow users to learn from their mistakes and practice real-world conversation skills. The popular language learning app, Duolingo, recently released a new learning experience powered by GPT-4. This approach leverages AI and machine learning to forecast ingredient and cooking quantities based on demand.

With its easy-to-use interface, customer service managers can get hold of important reports and insights in just a few clicks. First contact resolution (FCR) is an important customer service metric that reflects your agents’ ability to resolve customer problems on the first attempt. When there is no need for customers to keep contacting you for that same issue, again and again, customer happiness is bound to go up. The average response time denotes the average time taken by your agents to respond to customer queries or complaints. Therefore, the goal should be to significantly reduce the average response time and share faster responses irrespective of the channel.

Its “expanding agent replies” solution allows agents to type the bare bones of their response and then fleshes it out for them, saving them time in responding to customers across digital channels. As an example, AI can be paired with your CRM to recall customer data for your service agents. Your customer success team can use this feature to proactively serve customers based on AI-generated information. We’ve mentioned chatbots a lot throughout this article because they’re usually what comes to mind first when we think of AI and customer service.

Some people want more services for certain transactions; others prefer low-touch, 24/7 interactions. Effective omnichannel marketing, then, happens when companies provide a set of seamlessly integrated channels, catering to customer preferences, and steer them to the most efficient solutions. Customer service analytics can not only point to past performance but also show you a reflection of the future. For instance, after proper analysis, your business can identify the support channels that are most preferred by customers to approach your business. So, if a majority of customers prefer instant resolution, focusing on live chat will be the right decision.

The best part is that your agents will have more time to handle complex queries and your customer service queues will shrink in numbers. A case study shows that assisting customers with a chatbot can increase the booking rate by 25% and Chat GPT improve user engagement by 50%. This case study comes from a travel Agency Amtrak which deployed a bot that answered, on average, 5 million questions a year. Your support team will be overwhelmed and the quality of service will decline.

Instagram bots and Facebook chatbots can help you with your social media marketing strategy, improve your customer relations, and increase your online sales. For example, marketers can use CRM tools to manage campaigns and lead customer journeys with a data-driven approach. CRM software provides visibility into every opportunity or lead, showing you a clear path from inquiries to sales. Then, commerce teams can serve up personalized offers on your website, while customer service already knows a customer’s history if they reach out with questions.

It aims to inform as many people as possible about the product or brand, and the channels are not linked, so the customer experience is often different for each channel. Sometimes the term omnichannel is used in the context of customer service or customer experience. After an in-depth analysis of customer feedback, your business can unravel important answers. Your support team would know how happy customers are with the promptness of their service.

The chatbot can also book an appointment for the patient straight from the chat. Imagine that a patient has some unusual symptoms and doesn’t know what’s wrong. Before they panic or call in to have a visit with you, they can go on your app and ask the chatbot for medical assistance. Each treatment should have a personalized survey to collect the patient’s medical data to be relevant and bring the best results. For example, if your patient is using the medication reminder already, you can add a symptom check for each of the reminders.

Automation ensures that every customer receives the same high level of service, with consistent information and prompt responses, reducing the risk of human error or variance. Advanced AI can predict when a customer might encounter an issue (for instance, based on their usage patterns) and proactively provide assistance or resources. Automation can tailor promotional messages and offers based on individual customer preferences and behavior.

These chatbots typically integrate with the business’s order management system or logistics partners to provide accurate and up-to-date information. They reduce the need for customers to reach out to support teams for order inquiries. Customers prefer prompt actions delivered by chatbots fueled with artificial intelligence for better customer engagement.

And for customers using supplier-based AI, they can better understand their energy consumption and take steps to reduce their power draw during peak demand periods. Support leaders managing data should differentiate when to use real-time and historical analytics, and the use of prescriptive dashboards shared across the organization can aid in the visibility of data. Customer service managers get the most out of descriptive customer experience analytics by recognizing trends, such as an uptick in tickets near product launches or during the holiday retail season.

Automated systems can collect and analyze customer data to derive insights about customer behavior, preferences, and satisfaction levels. This data can be used to further improve customer service and tailor offerings to customer needs. Salesforce is the CRM market leader and Salesforce Service Cloud platform designed specifically for customer service and support with AI-driven assistants. Planet Fitness, a leading fitness center franchise, has implemented the Sprinklr AI+ platform to elevate its customer service operations on social media channels. By harnessing the power of AI and machine learning in customer service, Planet Fitness optimizes its customer service processes while maintaining a high standard of customer interaction on social media.

From contextual response generation to sentiment detection, LLMs can offer significant benefits in handling customer interactions. I will walk through few examples and benefits of using LLM for customer service operation. The best bots create genuine customer experiences that are indistinguishable from an interaction with a live agent.

Whether it’s your service manager who has decades of experience, or a new intern who has just joined your department, everyone should be motivated to perform. According to a Microsoft Report, 37% of Americans believe that brands do not take action on the feedback provided by them. Behind every unhappy customer is an important pain point that a business failed to solve.

Chatbots for Customer Service

Chatbots streamline the process of gathering valuable insights from customers regarding products, services, or overall experiences. These chatbots engage users in conversational interactions to solicit feedback on various aspects of their interaction with the business. Through structured questioning or open-ended prompts, users can provide feedback in a convenient and accessible manner. Businesses already use chatbots of varying complexity to handle routine questions such as delivery https://chat.openai.com/ dates, balance owed, order status or anything else derived from internal systems. By transitioning these frequently asked questions to a chatbot, the customer service team can help more people and create a better experience overall — while cutting operational costs for the company. The machine learning algorithms behind these voice bots enable them to understand the customer’s query, analyze the context and provide relevant information or assistance conversationally.

Generally, successful products fill a need not currently being met in the marketplace or provide a novel customer experience that creates demand. For example, the original iPhone filled a need in the market for a simplified device that paired a phone with an iPod, and the chia pet provided a humorous experience for consumers that was utterly unique. Installation and ongoing management is an easy lift for IT teams, since there are no frustrating version control issues or updates to schedule. And, with cloud-based CRM, you only pay for the number of seats you use and features you need.

Q1. How customer service analytics enhances the customer experience?

If 2023 was the year the world discovered generative AI (gen AI), 2024 is the year organizations truly began using—and deriving business value from—this new technology. In the latest McKinsey Global Survey on AI, 65 percent of respondents report that their organizations are regularly using gen AI, nearly double the percentage from our previous survey just ten months ago. Respondents’ expectations for gen AI’s impact remain as high as they were last year, with three-quarters predicting that gen AI will lead to significant or disruptive change in their industries in the years ahead. Customer service analytics can help you track customer-focussed KPIs such as CSAT, CES, and NPS.

Even if you do choose the right bot software, will you be able to get the most out of it? Data privacy is always a big concern, especially in the financial services industry. This is because any anomaly in transactions could cause great damage to the client as well as the institute providing the financial services. No wonder the voice assistance users in the US alone reached over 120 million in 2021. Also, ecommerce transactions made by voice assistants are predicted to surpass $19 billion in 2023. Everyone who has ever tried smart AI voice assistants, such as Alexa, Google Home, or Siri knows that it’s so much more convenient to use voice assistance than to type your questions or commands.

For the first time, our latest survey explored the value created by gen AI use by business function. The function in which the largest share of respondents report seeing cost decreases is human resources. Respondents most commonly report meaningful revenue increases (of more than 5 percent) in supply chain and inventory management (Exhibit 6).

These tools can be trained in predictive call routing and interactive voice response to serve as the first line of defense for customer inquiries. These types of tools use AI to synthesize existing information and output copy based on a desired topic. You can then use this copy to create knowledge base articles or generate answers to common questions about your product. While chatbots are great at troubleshooting smaller issues, most aren’t ready to tackle complex or sensitive cases.

Voice Recognition – Identify customers from unique voice prints when they call for support. The seven Ps are product, price, place, promotion, people, processes, and physical evidence. Your target market is athletes in their early twenties to late thirties, so you decide to market your product in sports publications and sell it at specialty athletics stores. By focusing on sports stores over shoe stores in general, you target your efforts to a specific place that best fits your marketing mix.

What are some RPA use cases in customer service?

Furthermore, as customers interact with the voice bot and provide feedback, machine learning algorithms continuously learn and adapt to improve the quality of responses over time. Having understood the use cases of machine learning in customer service, let’s now examine some brands that are using machine learning to grow. This level of personalization improves the customer experience, fosters loyalty and increases customer lifetime value. Customer analytic software is used to create visual dashboards that update in real-time.

Chatbots can engage with your customers with immediate responses and increase customer satisfaction, which makes them happy to retain your brand. Chatbots for customer service can help businesses engage clients by answering FAQs and delivering context to conversations. Businesses can save customer support costs by speeding up response times and improving first response time which boosts user experience. Chatbots are designed to understand user queries, provide relevant responses, and perform tasks or actions based on the context of the conversation. They can be integrated into various platforms such as websites, messaging apps, and voice assistants.

For example, a supply-chain function can use algorithms to predict future needs and the time products need to be shipped for timely arrival. This can help create new efficiencies, reduce overstocks and help make up for reordering oversights. Leading companies are now using generative AI for application modernization and enterprise IT operations, including automating coding, deploying and scaling. For coding, developers can input a coding command as a straightforward English sentence through a natural-language interface and get automatically generated code. Generative AI tools such as ChatGPT, Bard and DeepAI rely on limited memory AI capabilities to predict the next word, phrase or visual element within the content it’s generating.

They are an example of a “marketing mix,” or the combined tools and methodologies used by marketers to achieve their marketing objectives. Have a look at the Salesforce pricing page to see an overview of CRM costs based on the size of your business and the products that are right for your needs. Now anyone can work from anywhere on any device, boosting collaboration and bringing down costs.

Feedback Analysis – Parse unstructured feedback like NPS surveys and reviews to understand brand perception and pinpoint issues. Response recommendation – Suggesting tailored responses to customer questions based on context and history. Top examples are Sephora‘s chatbot on Facebook Messenger and Hyatt‘s text-based Concierge bot.

Sentiment Analysis

Once you choose your chatbot and set it up, make sure to check all the features the bot offers. These chatbot providers focus on a specific area and develop features dedicated to that sector. So, even though a bank could use a chatbot, like ManyChat, this platform won’t be able to provide for all the banking needs the institution has for its bot. Therefore, you should choose the right chatbot for the use cases that you will need it for. People can add transactions to the created expense report directly from the bot to make the tracking even more accurate. Depending on the relevance of the report, users can also either approve or reject it.

You can use chatbots to guide your customers through the marketing funnel, all the way to the purchase. Bots can answer all the arising questions, suggest products, and offer promo codes to enrich your marketing efforts. Chatbots can also push the client down the sales funnel by offering personalized recommendations and suggesting similar products for upsell. They can also track the status of a customer’s order and offer ordering through social media like Facebook and Messenger.

Resolve rule-based issues

Customer interactions can now be assisted in real time with conversational AI. Voice-based queries use natural language processing (NLP) and sentiment analysis for speech  recognition so their conversations can begin immediately. Using machine learning algorithms, AI can understand what customers are saying as well as their tone—and can direct them to customer service agents when needed. With text to speech and NLP, AI can respond immediately to texted queries and instructions. There’s no need to make customers wait for the answers to frequently asked questions (FAQs) or to take the next step to purchase.

As customers are always looking to get quick solutions and personalized help that will boost their experience, chatbots are a valuable asset. AI chatbots for business enable organizations to shift 64% of agents’ focus to solving complex issues, compared to 50% without AI. Automated customer service interactions sometimes break down when customers change their intent halfway through a conversation – confusing the virtual agent. As a result, the GenAI application has something to work from – as do live agents during voice interactions –enhancing the contact center’s knowledge management strategy.

Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks. Brands are fighting tooth and nail to differentiate themselves in an innovative, hyper-competitive world. Armed with the right data and analytics strategy and the right approach to customer relationship management, raw data can be easily understood and shared. Analytics that affect and inform customer retention will help your business improve campaigns alongside overall product and support.

Help desk software empowers your team to rapidly improve response times and manage incoming inquiries. Many e-commerce businesses outsource content creation to save time and costs without compromising quality. This article explores the benefits and misconceptions of Business Process Outsourcing (BPO) for content.

Sentiment analysis and chatbots help customer service teams address inquiries faster, streamline workflow, and proactively anticipate buyers’ needs. Thanks to modern technology, chatbots are no longer the only way customer service teams can leverage AI to improve the customer experience. Advancements in AI continue to pave the way for increased efficiency across the organization — particularly in customer service.

That new LLM feature may further enhance automated customer replies by ensuring they align with the brand’s tone of voice. As LLMs become more sophisticated, expect further waves of customer service use cases for generative AI to rise up. They often engage with customers to snuff out any potentially simple fixes before making a site visit.

However, the best technological investment to achieve automated customer service is to pick a customer service software that can potentially offer most of these solutions. Also, you can consider investing in customer self service tools to help your customers solve problems on their own. However, the emergence of no-code AI-powered customer service tools, such as Sprinklr Service, is changing the landscape. These tools democratize AI implementation, allowing businesses of all sizes to leverage machine learning without specialized coding skills or AI expertise.

Ideally, these findings inform marketing, product development, and guide the overall customer experience. For instance, imagine a customer who contacts a company’s support team expressing disappointment with a recent service disruption. Through sentiment analysis, an LLM can detect the negative sentiment, lookup any past conversations and generate a response that acknowledges and empathizes with the customer’s frustration. This personalized and empathetic approach can help restore trust and loyalty in the customer, strengthening the brand-customer relationship. Also known as chatbots, chat automation provides instant support to your customer via a live chat widget on the front end of your website. On the backend, a simple chatbot can retrieve answers to FAQs and surface self-serve resources from your knowledge base.

The data can also tell a story of how a support organization is functioning, leading to optimization for ideal customer support or departmental budgeting. In conclusion, incorporating LLMs into customer service operations allows businesses to augment conventional approaches, delivering personalized, efficient, and empathetic experiences. Companies have the opportunity to revolutionize their customer service operations, elevate the overall customer experience, and cultivate satisfied customers who become invaluable brand ambassadors.

These transcriptions offer an objective record for effective dispute resolution and pave the way for personalized customer interactions, ensuring a more tailored and responsive service. By leveraging tools like CallRail’s conversation intelligence software, customer service teams can operate with heightened efficiency, ensuring improved customer experiences. AI chatbots with natural language processing (NLP) and machine learning help boost your support agents’ productivity and efficiency using human language analysis. You can train your bots to understand the language specific to your industry and the different ways people can ask questions. So, if you’re selling IT products, then your chatbots can learn some of the technical terms needed to effectively help your clients. Customer support automation is quickly becoming a necessity in today’s fast-paced and competitive business environment.

So, you can save some time for your customer success manager and delight clients by introducing bots that help shoppers get to know your system straight from your website or app. Then you’ll be interested in the fact that chatbots can help you reduce cart abandonment, delight your shoppers with product recommendations, and generate more leads for your marketing campaigns. Chatbots have revolutionized various industries, offering versatile and efficient solutions to businesses while continuously enhancing customer engagement. Virtual customer assistants (VCAs) or chatbots act as the frontline, handling common customer inquiries. Delve into product development, product launch, branding, and customer experiences in the Brand and Product Management course, Part 1 of the Marketing Mix Specialization.

A site visitor will type in all relevant contextual information in the chat, the bot will process the message for keywords, and surface the most relevant content that will meet their needs. Escalation to a live agent happens if a user isn’t satisfied with automated support. Businesses of all sizes should be using chatbots because of the advantages it provides to customer service teams. Companies can expand the bandwidth of their support teams without hiring more reps. Serving as the lead content strategist, Snigdha helps the customer service teams to leverage the right technology along with AI to deliver exceptional and memorable customer experiences. The future of AI in customer service may still include chatbots, but this technology has a lot more to offer in 2023.

What is Proactive Live Chat? [+ How to Implement It and 7 Tools]

Moreover, the model can proactively alert human administrators when updates or additions are needed, ensuring the knowledge base remains current and relevant. Cem’s hands-on enterprise software experience contributes to the insights that he generates. He oversees AIMultiple benchmarks in dynamic application security testing (DAST), data loss prevention (DLP), email marketing and web data collection.

By doing this, an anonymous site visitor becomes a lead that has shared contact information without ever being contacted by a live agent. Hyperautomation Hyperautomation involves the rapid automation of as many IT approaches as possible. AI accelerates and streamlines this process, allowing customer service to operate with greater speed and efficiency.

• Since 1983, we’ve built our scalable and flexible architecture to help enterprises meet today’s customer demands while continuously transforming for tomorrow.
• Similarly, if you price your product too low, then some might pass it up simply because they are concerned it might be of inferior quality and cut into your potential profit margins.
• While the LLM can generate a draft response, its important to realize that human review, and customization remain critical.
• For the past six years, AI adoption by respondents’ organizations has hovered at about 50 percent.
• More benefits from AI include building a more sustainable IT system and improving the continuous integration/continuous (CI/CD) delivery pipelines.

The practical applications for organizations and customer service teams are still a work in progress, but smart assistants such as Alexa, Google Assistant and Siri are an exciting avenue for personalized service. Customers appreciate and prefer when an organization communicates via their preferred platform, and for some people, that may be via their smart home device. Imagine a future where a user can bypass a phone call or email and troubleshoot any product or service concern via a simple question to their smart speaker. Simplified communications like this could be the difference between a satisfied or frustrated customer.

Many AI chatbots and conversational tools have the capacity to generate content in different languages. Also, make sure that you check customer feedback where shoppers tell you what they want from your bot. If the answer is yes, make changes to your bot to improve the customer satisfaction of the users. They communicate with your potential customers on Messenger, send automatic replies to Instagram story reactions, and interact with your contacts on LinkedIn. They can answer reactions to your Instagram stories, communicate with your Facebook followers, and chat with people interested in specific products. Chatbots can serve as internal help desk support by getting data from customer conversations and assisting agents with answering shoppers’ queries.

Bots have been used widely across different business functions like customer service, sales, and marketing. You can foun additiona information about ai customer service and artificial intelligence and NLP. With REVE Chat, start a free trial of advanced customer support software and start delivering great experiences to customers. Deploying chatbots on your website boosts operational efficiency and offers convenience to customers. Bots not only streamline customer experiences at every stage in the service process but are also aids to the support agents. The key benefit of customer service analytics, then, is to sift through this sea of data and separate the wheat from the chaff.

Given the appetite for self-service, AI-powered customer assistants–from chatbots to automated callers–are growing in popularity. This is an especially appealing AI use case for contact centers facing higher traffic with fewer agents. AI implementations–from emotional AI to conversational automation–are among the most exciting and useful customer service tools available today. With more businesses investing in digital initiatives in the wake of the global pandemic, demand for AI tools is on the rise.

It’s a great time to take advantage of the flexibility, efficiency, and speed that AI can provide for your support team. One of the use cases of chatbots for customer service is offering self-service and answering frequently asked questions. This can save you customer support costs and improve the speed of response to boost user experience.

That’s why chatbots flagging up any suspicious activity are so useful for banking. Chatbots offer a variety of notifications you can set, such as minimum balance notifications, bill pay reminders, or transaction alerts. You can improve your spending habits with the first two and increase your account’s security with the last one.

For example, if a customer wants to know what items are allowed in carry-on bags, they can simply send a message and wait for a reply while they continue to pack. As of now, chatbots don’t get paid, so management can use bots to expand the reach of their team without hiring more reps. This makes chatbots an attractive, cost-effective solution for understaffed service teams. Another benefit of adopting a chatbot is that customers would receive faster responses.