The Truth About AI in Customer Support: What Works and What Doesn’t

Consumers are still not entirely at ease with AI technologies. It still makes mistakes, which is annoying. Take a look at these results from our yearly CX and customer service research (supported by RingCentral):

•70% of consumers stated that they preferred using the phone over self-service options, such as voice recognition software or AI-powered tools like ChatGPT. • When utilizing ChatGPT or AI technology, 63% of consumers express frustration. • 56% of consumers acknowledge that they are afraid of ChatGPT and AI.

It’s improving despite consumers’ fears and anxieties about communicating with voice recognition software or chatbots powered by artificial intelligence. Certain solutions are nearly flawless. The issue is that not all businesses have embraced the newest and finest technology, which is sometimes significantly superior to that which is only a year old.

As a result, customers are unsure of what to anticipate from one brand or firm to the next. Because of this, a lot of customers would prefer to call a business rather than use digital self-service customer care to fix difficulties, because it undermines trust and confidence in the system.

Pros of AI-Driven Support

1. 24/7 Availability Chatbots and virtual assistants powered by AI never go to sleep. They may respond to simple customer questions at any time of day, providing prompt answers and cutting down on wait times.

2. Scalability and Cost Efficiency Businesses can manage a large number of client interactions at once using automated help, frequently at a reduced cost. This ensures that routine questions are answered quickly and frees up human agents for more complex work.

3. Personalized Interactions Sophisticated AI systems combine machine learning (ML) and natural language processing (NLP) to deliver personalized responses and recommendations. By looking at a user’s demographics, browsing history, and past purchases, AI may swiftly generate customized insights.

4. Consistent and Data-Driven Fatigue and mood swings do not affect AI support systems. They ensure accuracy and consistency in customer contact by providing consistent responses and being able to be centrally updated with new data or policy changes.

Cons of AI-Driven Support

1. Limited Understanding of Context Even with advanced NLP models, AI chatbots may find it difficult to understand tone or context in some situations. AI may falter in difficult, uncommon, or emotionally nuanced requests, frustrating both the consumer and the company.

2. Risk of Inaccuracy AI is great at responding to requests that are expected, but when presented with questions or situations that are not part of its training data, it may provide irrelevant or inaccurate answers.

3. Lack of Empathy Emotional reassurance is a common aspect of customer service. No matter how sophisticated, AI lacks the true human empathy needed for delicate situations. Consumers may believe that their issues are not adequately addressed by automatic responses.

4. Data Privacy and Security Concerns Data is essential to AI systems, but collecting and storing consumer data carries concerns. Businesses run the danger of data breaches and a decline in client trust if they don’t implement strong cybersecurity measures and comply with regulations.

Case Studies: Successful AI Implementations

1. Bank of America’s “Erica” For millions of clients, Bank of America’s chatbot “Erica” acts as a virtual financial advisor. Erica uses predictive analytics to give advice on improved money management, assist with bill payment, and provide insights into spending patterns. Bank of America has improved customer engagement and satisfaction ratings by smoothly incorporating AI into an already-existing mobile banking service, freeing up live representatives to concentrate on complicated questions. Key Takeaway: AI can become a reliable advisor if it provides a seamless user experience based on a large dataset, particularly when it addresses typical problems like bill reminders and budgeting.

2. H&M’s Conversational Chatbot H&M, a global fashion store, launched an AI-powered chatbot on messaging platforms to assist consumers in tracking deliveries, finding products, and checking the status of their orders. The chatbot improves its style advice and product recommendations by “learning” from every user contact. This system gave busy shoppers a convenient conduit and drastically cut down on response times. Key Takeaway: Successful AI implementations are excellent at transactional questions, such as order tracking and product information, and they can also gather data to enhance personalisation.

AI isn’t just for customer support

In order to process client orders in the drive-through lanes, McDonald’s has been testing an AI voice recognition system. McDonald’s stated that it was discontinuing the technology because of an order accuracy issue in a recent RetailWire report. Consumers complained about things like getting a bacon-topped ice cream cone and being charged for nine sweet teas when they only requested one. But people also make mistakes. A staff member at a McDonald’s in Lakeland, Florida, messed up a customer’s order. The staff intervened after the customer became irrationally irate. But instead of calling the police for assistance, she pulled out her revolver and fired a shot as the client drove off. (The original story can be found at this link.)

The idea is that while both humans and AI will make mistakes, AI won’t locate a pistol and shoot a customer. The majority of businesses should make the same effort to develop a generative AI customer experience as they do to build a positive experience driven by human-to-human interactions. Acknowledge that both could make a mistake. Employees should be adequately trained and prepared to handle Moments of Misery, whether they are caused by technology or human error. By doing this, you can guarantee a more reliable and satisfying consumer experience.

Read the full article here: https://medium.com/@MsquareAutomation/the-truth-about-ai-in-customer-support-what-works-and-what-doesnt-53de9f502461