Top 7 RPA Use Cases in Customer Service in 2024

The four Ps are a “marketing mix” comprised of four key elements—product, price, place, and promotion—used when marketing a product or service. Typically, successful marketers and businesses consider the four Ps when creating marketing plans and strategies to effectively market to their target audience. Although there are many other “marketing mixes,” the four Ps are the most common and foundational to creating a successful marketing strategy. Pega provides a powerful platform that empowers the world’s leading organizations to unlock business-transforming outcomes with real-time optimization. Clients use our enterprise AI decisioning and workflow automation to solve their most pressing business challenges – from personalizing engagement to automating service to streamlining operations. Since 1983, we’ve built our scalable and flexible architecture to help enterprises meet today’s customer demands while continuously transforming for tomorrow.

The quicker the response, the more satisfied a customer is when compared to businesses that take much longer to respond. With stiff competition across sectors, businesses go to great lengths to gather feedback from their customers to identify areas for improvement. In fact, statistics show that 3 out of 4 customers will likely spend more money on businesses that provide them with a good customer experience (CX). While customer service analytics is a broader term, there are several specific types based on the information or analysis they provide and the data they need to offer them.

Contact Routing Intelligent contact routing uses AI to automatically direct customers to designated representatives based on their queries. This time-saving AI use case is especially beneficial for contact centers with multiple departments and/or customer service options. Put together, next-generation customer service aligns AI, technology, and data to reimagine customer service (Exhibit 2). That was the approach a fast-growing bank in Asia took when it found itself facing increasing complaints, slow resolution times, rising cost-to-serve, and low uptake of self-service channels. But done well, an AI-enabled customer service transformation can unlock significant value for the business—creating a virtuous circle of better service, higher satisfaction, and increasing customer engagement.

Discover how this Shopify store used Tidio to offer better service, recover carts, and boost sales. Document processing – Digitize paper documents and extract text through OCR and data extraction techniques. Chatbot rehearsals – Hone patience and understanding with bots that exhibit challenging behavior. Channel optimization – Determine the best channel or agent for resolution based on issue and history.

The market for artificial intelligence (AI) is expected to grow to almost 2 trillion U.S. dollars by 2030, and AI in customer service has become a focus area for many businesses. It’s obvious that if you don’t know about some of the features that the chatbot provides, you won’t be able to use them. But you would be surprised by the number Chat GPT of businesses that use only the primary features of their chatbot because they don’t know any better. So, if you want to be able to use your bots to the fullest, you need to be aware of all the functionalities. Finance bots can effectively monitor and identify any warning signs of fraudulent activity, such as debit card fraud.

Voice bots facilitate customers with a seamless experience on your online store website, on social media, and on messaging platforms. They engage customers with artificial intelligence communication and offer personalized solutions to shoppers’ requests. And it won’t harm the customer satisfaction your online store provides as our study on the current chatbot trends found that over 70% of buyers have a positive experience using chatbots.

Customer engagement analytics

Using historical data of production, generative AI can predict or locate equipment failures in real time—and then suggest equipment adjustments, repair options or needed spare parts. AI can power tasks and tools for almost any industry to boost efficiency and productivity. AI can deliver intelligent automation to streamline business processes that were manual tasks or run on legacy systems—which can be resource-intensive, costly and prone to human error. Here are some of the industries that are benefiting now from the added power of AI.

• Chatbots offer a variety of notifications you can set, such as minimum balance notifications, bill pay reminders, or transaction alerts.
• By focusing on sports stores over shoe stores in general, you target your efforts to a specific place that best fits your marketing mix.
• As per research, the participants who used the chatbot were 26% more likely to meet or exceed personal fitness goals compared to participants who didn’t use the technology.
• Teachers and trainers can use AI analytics to see where students might need extra help and attention.

Whether checking order status, resolving product-related issues or providing troubleshooting tips, these voice bots leverage machine learning to deliver prompt and accurate responses to customer inquiries. Machine learning in customer service analyzes customer feedback, social media posts and other textual data to analyze sentiment and identify emerging trends. This enables you to understand customer sentiment in real time, identify areas for improvement and tailor responses to individual needs. BPO providers use AI in customer service to improve the user experience and design meaningful interactions.

The banking chatbot can analyze a customer’s spending habits and offer recommendations based on the collected data. In fact, nearly 46% of consumers expect bots to deliver an immediate response to their questions. Also, getting a quick answer is also the number one use case for chatbots according to customers.

Analyze Customer Feedback & Suggestions

Offer personalization As more organizations adopt a customer-centric business strategy, offer personalization will become an increasingly attractive customer service AI use case. The EVA bot has been configured to handle queries on more than 7,500 FAQs, along with information on the bank’s products and services. With an accuracy level of over 85% and uptime of 99.9%, EVA is boosting customer experience using various conversational interfaces. Today, many bots have sentiment analysis tools, like natural language processing, that helps them interpret customer responses. Using chatbots as an example, you can automatically respond to a customer’s live chat message within seconds. And chatbots can help you educate shoppers easily and act as virtual tour guides for your products and services.

When prioritized and deployed correctly, this type of business process improvement can save customer service companies millions of dollars each year. Machine learning, a subset of artificial intelligence (AI), utilizes algorithms and statistical models to analyze data and make decisions or predictions without explicit programming. In the customer service domain, machine learning integrates with various tools such as chatbots, virtual agents and contact center CRM systems, augmenting their capabilities.

• It can answer frequently asked questions, provide product information, assist with troubleshooting and even process simple transactions.
• While chatbots are great at troubleshooting smaller issues, most aren’t ready to tackle complex or sensitive cases.
• Rather than using the same approach for every situation, Culliton and Borden recognized that successful executives instead mixed different methods depending on variable market forces.
• If all that information gets stored in handwritten notes, laptops, or inside the heads of your salespeople, there can be serious cost implications.

Machine learning in customer service acts as a mighty co-pilot for your team of live agents. You can foun additiona information about ai customer service and artificial intelligence and NLP. AI assistants, driven by machine learning algorithms, provide agents with real-time assistance during live conversations. These tools offer a range of support, from recommending relevant knowledge base articles to providing contextual recommendations based on similar resolved cases. By making resolutions faster and more efficient, they ultimately enhance customer satisfaction. At its core, machine learning is key to processing and analyzing large data streams and determining what actionable insights there are. In customer service, machine learning can support agents with predictive analytics to identify common questions and responses.

Multilingual Support

Research on the omnichannel experience shows more than half of B2C customers engage with three to five channels each time they make a purchase or resolve a request. And the average customer looking to make a single reservation for accommodations (like a hotel room) online switched nearly six times between websites and mobile channels. If these customers encounter inconsistent information or can’t get what they need, they may lose interest in a brand’s products or services. More and more, customers move across all channels—in person, online, and beyond—to get what they want. But not every customer is looking for the same thing, and omnichannel marketing acknowledges that.

Expense tracking can be done manually using spreadsheets or automated through specialized software and mobile apps. Here is how messaging platforms with chatbot capabilities can help businesses. With an increase in messenger platforms for business, one of the most important channels is social. As per a Business Insider report, “Consumers choose the main four social networks – Facebook, Twitter, Instagram, and LinkedIn”. For instance, the latest iteration of ChatGPT – GPT-4 – can analyze and classify images.

Marks & Spencer overhauled its IVR to handle millions of calls a month and get customers to the right person, at the right store, in record time without the need to repeat a request over and over. Automate basic self-service tasks

Build in the ability to confirm appointments, process payments compliantly, or retrieve information without requiring agent intervention. The latest survey also shows how different industries are budgeting for gen AI. Yet in most industries, larger shares of respondents report that their organizations spend more than 20 percent on analytical AI than on gen AI.

IDC Report: Creating an AI Blueprint for the Contact Center

At its heart, the solution contains a wealth of anonymized contact center conversation data that NICE has pulled together and used to develop sector-specific benchmarks for many metrics. When an agent types in a question, it can pop up the answer, so the agent doesn’t have to trawl through articles and documents to find it. Alongside the answer, the GenAI-powered bot cites the sources of information it leveraged, which the customer can access if they wish to dig deeper. It’s allowing users to build applications using natural language alone instead of drag-and-drop tooling.

Improve your IVR speech recognition performance with 11 best practices from our product team. And if you believe your business will benefit from an RPA solution, feel free to check our data-driven list of RPA vendors, and other automation solutions. Based on the priority level assigned, a workflow for issue resolution is created, and the customer is informed of the refund decision. By registering, you confirm that you agree to the processing of your personal data by Salesforce as described in the Privacy Statement.

As the COVID-19 pandemic forced employees into remote positions, many training teams began using AI to construct simulations to test employee aptitude for handling various situations. Previously, the training involved a blend of classroom training, self-paced learning and a final assessment — a routine that’s much harder to implement in remote or hybrid offices. However, some of the metrics discussed above can also be an indicator of overall customer experience while also providing actional insights into your business’s customer service. Start by identifying the areas in your customer service that require automation. Look for repetitive tasks, frequent customer queries, or areas where speed and efficiency could be improved.

Now, natural language processing eliminates these redundancies to create deeper and more efficient customer satisfaction. Engagement is a massive arm of understanding customer experience.Customer engagement comprises of all the interactions between a brand and its customers across various communication channels. This could be interactions social media, in customer service channels, or insights gleaned from survey results. According to Deloitte, nearly two out of three customers expect businesses to integrate customer feedback into future products and services.

No matter your industry, or even if you’re a non-profit, if you communicate with customers — and your employees rely on information about those customers — CRM tools can help. Compared with 2023, respondents are much more likely to be using gen AI at work and even more likely to be using gen AI both at work and in their personal lives (Exhibit 4). The survey finds upticks in gen AI use across all regions, with the largest increases in Asia–Pacific and Greater China. Respondents at the highest seniority levels, meanwhile, show larger jumps in the use of gen Al tools for work and outside of work compared with their midlevel-management peers.

So, for diabetic treatment, the chatbot can ask if the patient had any symptoms during the day. And for pain medication, the bot can display a pain level scale and ask how much pain the patient is in at the moment of fulfilling the survey. Bots can also track the package shipment for your shopper to keep them updated on where their order is and when it will get to them. All the customer needs to do is go onto the company’s website or Facebook page and enter their product’s shipping ID. Every customer wants to feel special and that the offer you’re sending is personalized to them. Sign-up forms are usually ignored, and many visitors say that they ruin the overall website experience.

About 60 to 70 percent of consumers research and shop both in stores and online. More concretely, over one-third of Americans made omnichannel features—think buying online and picking up in store or curbside—part of their regular shopping routines since the COVID-19 pandemic emerged. The ProProfs Help Desk Editorial Team is a passionate group of customer service experts dedicated to improving your help desk operations with top-notch content. We stay ahead of the curve on trends, tackle technical hurdles, and provide practical tips to boost your business. With our commitment to quality and integrity, you can be confident you’re getting the most reliable resources to enhance your customer support initiatives. Yes, customer analytics can boost sales as well as lead to better service strategies.

This makes a powerful AI use case for organizations looking to reduce wait times and manual agent errors. Protecting personally identifiable information (PII) In the era of high-profile data breaches, more companies are doubling down on digital security. AI can help contact centers protect personally identifiable information (PII) during interactions, strengthening compliance and customer confidence. Even before customers get in touch, an AI-supported system can anticipate their likely needs and generate prompts for the agent.

AI-powered FinOps (Finance + DevOps) helps financial institutions operationalize data-driven cloud spend decisions to safely balance cost and performance in order to minimize alert fatigue and wasted budget. AI https://chat.openai.com/ platforms can use machine learning and deep learning to spot suspicious or anomalous transactions. Banks and other lenders can use ML classification algorithms and predictive models to suggest loan decisions.

Survey&review analytics

When your customer service representatives are unavailable, the chatbot will take over. It can provide answers to questions and links to resources for further information. Commerce teams can quickly launch and scale ecommerce — from online orders to curbside pickup — for their consumer shoppers (B2C commerce) and business buyers (B2B commerce). And customer service agents customer service use cases can respond to customer needs on any channel — from the office, at home, or in the field. Each customer has their own account in a business CRM database which includes their name, customer ID, contact information, credit card information and purchase history. Customers typically create their account by speaking to a customer rep or a chatbot in a recorded conversation.

They have become data factories that are pumping out information at a breakneck pace. From customer feedback information to call recordings worth thousands of hours, the data at hand is gigantic. LeadSquared and Qualaroo are some of the best customer service analytics tools available today. While LeadSquared offers a comprehensive suite of services and end-to-end ticket management, Qualaroo is primarily a customer feedback software.

Empathizing with the customer and correctly responding to them based on customer’s state of mind will go a long way to help nurture customer relationship. Its website has a chat bot feature that surfaces FAQ and responses so users can find common solutions to their needs. It also features a Live Chat button that visitors can click to be transferred to a live agent for more pressing issues.

Zendesk’s customer analytic software comes with pre-built dashboards that are great for a high-level look at your customer data, and they can be shared with agents and administrators. For more sophisticated forays into data, it’s also possible to create custom dashboards. Customer service analytics is the process of capturing and analyzing data from customers. Data comes from all points in a customer relationship — messages, purchases, survey feedback, returns and demographics. Companies often use analytics tools to collect customer data sourced from across the business to generate valuable insights.

Omnichannel is a business strategy, while “phygital” (a portmanteau that combines the word “physical” and “digital”) refers to the integration of the physical and digital worlds. With this data, you can evaluate the performance of each member of your team, rewarding those who perform well and implementing Performance Improvement Plans (PIP) for those who need to pull up their socks. By automating routine tasks, employees can focus on more complex and rewarding tasks, which can improve job satisfaction and reduce burnout. Apart from auto-responding to messages and comments, these tools can also track mentions of your brand, schedule posts, and provide analytics.

The ticket volume refers to the total number of customer service tickets your business generates within a given period. Automated customer satisfaction surveys and feedback forms can gather customer opinions and satisfaction levels post-interaction or post-purchase. Data is vital for Dallas businesses, home to many Fortune 500 companies, making them prime cyberattack targets. This article covers strategies for data breach and ransomware protection and highlights how a Dallas BPO provider can enhance cybersecurity. Adding AI to your customer service is no problem when you partner with a BPO company like Unity Communications.

And, it serves a wide range of purposes including customer support, sales assistance, information retrieval, and task automation. To start, gen AI high performers are using gen AI in more business functions—an average of three functions, while others average two. They’re more than three times as likely as others to be using gen AI in activities ranging from processing of accounting documents and risk assessment to R&D testing and pricing and promotions. Customer service teams generate tickets for a whole range of issues or challenges their customers face. Prioritising these tickets often depends on the complexity of the issue and how strongly your customers feel about the problem.

The companies that will win at CX are those that embed AI seamlessly across the customer service workflow to create effortless, anticipatory and human-centric experiences. The opportunities are phenomenal, but realizing AI‘s full potential rests on choosing the right use cases and implementation strategy for your organization and customers. Today, many marketers use the five Ps over the four Ps because they center the experiences of customers and staff in the marketing process.

Automated systems can handle a large number of requests simultaneously, allowing businesses to easily scale up their customer service skills and operations during peak times without the need for additional staff. Automated systems for creating, assigning, tracking, and managing customer service tickets can improve efficiency and ensure issues don’t fall through the cracks. To ethically use ML in customer service, focus on transparency, data privacy and bias prevention. Inform your customers how their data may be used when interacting with your AI-driven systems and ensure that the data used in training ML models is free from biases. Conduct regular audits and system updates to maintain ethical standards and comply with relevant regulations. Integrating machine learning into customer service can be challenging for many businesses due to the need for specialized coding skills and deep AI expertise.

Like price, finding the right place to market and sell your product is key to reaching your target audience. If you put your product in a place that your target customer doesn’t visit—whether on or offline— then you will likely not meet your sales target. The right place can help you connect with your target audience and set you up for success.

Expert systems can be trained on a corpus—metadata used to train a machine learning model—to emulate the human decision-making process and apply this expertise to solve complex problems. These systems can evaluate vast amounts of data to uncover trends and patterns, and to make decisions. They can also help businesses predict future events and understand why past events occurred. From customer satisfaction to resolution time, these are the key customer service metrics that measure performance and drive revenue. Predictive customer journey analytics can help managers understand which patterns are currently driving success, so that their efforts can be emulated, iterated on, and optimized. This kind of customer data can also fill information gaps that customer experience analytics — which may be drawn largely from support data — might miss.

These may include making payments, scheduling appointments, or updating their personal information. The weblinks and contact center knowledge sources that the conversational AI platform integrates with inform the response – helping to automate more customer queries. It understands customer intent, assesses how agents and supervisors have successfully handled such queries, and uses that information to develop a new knowledge article. Many CCaaS providers now offer the capability to automate quality scoring, giving insight into all contact center conversations.

They can provide a clear onboarding experience and guide your customers through your product from the start. Social Listening – Monitor brand mentions across social media to detect customer pain points through natural language processing and sentiment analysis. There are many ways that customer relationship management software can make a big impact on your business. CRM products and services are made for businesses of all sizes and to meet needs across all areas of a company. Whether you’re a small business or a large enterprise, it’s easy to get started. This information can be invaluable, especially since 70% of customers expect every representative they contact to know their purchase and issue history.