Chatbots Powered by Artificial Intelligence: The Future of Customer Engagement
The future of customer engagement is chatbots powered by artificial intelligence. Many companies have already seen significant returns from implementing this technology, and the global conversational AI market is expected to grow at a CAGR of 22% during 2020-25. Chat Bot adoption rates are doubling over the next two - to five years, so businesses must start preparing for this shift now.
According to researchers, industry executives, and analysts, customer service chatbots are on a path to improve significantly over the next several years, pulled along by advances in artificial intelligence. They will become more intelligent, conversational, humanlike, and most importantly, more helpful. Gartner estimates that "25% of all customer service and support operations will integrate virtual customer assistant or chatbot technology across."
"Even now, there are times you sort of can't tell it's not a human," said Bern Elliot, an analyst at Gartner, a technology research firm. "It's not as good as you'd like, but it is moving in that direction. And innovation is occurring at a rapid pace."
Conversational agents are among the leading applications of AI
Conversational AI technologies, such as chatbots, virtual agents, and voice assistants, have gained in popularity in recent years, especially over the previous year. COVID-19 has promoted its usage. Many companies are using these technologies to interact with their customers. The goal is to improve customer engagement and satisfaction while decreasing support costs.
Customers appreciate that AI improves the efficiency, processing speed, and transaction volume of consumer interactions. Over 80% of firms say AI improves call volume processing, and over 90% claim faster complaint resolution. Between 25% and 50% of all inquiries are now completely handled through automated channels, freeing agents to focus on more complex work.
Why are chatbots so effective?
The benefits of AI-powered chatbots are many and varied. Here are some of the most important ones:
- Chatbots never get tired: They can work 24/hours a day, 365 days a year. This is great for businesses that operate internationally or have customers in different time zones.
- Chatbots can handle large volumes of inquiries: This is another big plus for businesses that receive a lot of customer queries. Chatbots can quickly and efficiently manage large numbers of requests, leaving human agents free to deal with more complex issues.
- Chatbots are consistent: Unlike human beings, chatbots will always give the same answer to a question. This is great for ensuring consistency and accuracy in customer service.
- Chatbots are fast: They can reply to customers quickly, which is another plus for businesses that want to provide a high level of customer service.
- Chatbots learn over time: As they gain experience, chatbots get better at responding to customer queries. This means that the more they are used, the better they provide customer service.
Marcus, Goldman's digital consumer bank, significantly "cut down on costs and expenses in terms of people" at call centers by using the tech, Abhinav Anand, an MD and head of lending for consumers at Goldman Sachs, said at a recent industry event.
"That itself, at the scale at which we are growing, is a massive saving and a good way to measure the return on our investments," said Anand, who was speaking at the Ai4 Finance Summit in New York.
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Goldman Sachs Marcus is not eliminating call center work but rather utilizing intelligent AI-enabled chat services to manage expansion. As customers move more of their banking to mobile - where they are more likely to use chatbots - the company is automating services like account origination and fraud prevention.
The bank has also decreased client wait times, rerouted calls, and fewer employees per customer number. The same type of AI technology is being used in the customer journey, where the bank is betting on consumers wanting greater flexibility when it comes to how they engage with the bank.
Customization for improved performance
To get the most out of chatbots, it is essential to customize them according to the specific needs of your business. This involves tailoring the bots' conversation flows and responses to match the tone and style of the company's customer service. Brands also need to ensure that the bots can handle all of the different types of queries they are likely to receive.
It is also important to integrate the chatbots with the company's existing customer service infrastructure. This includes things like CRM systems and knowledge bases. Doing so will allow the bots to provide more accurate and helpful customer responses.
Customization drives performance and improves client results. Companies that grow quicker generate 40 percent more of their revenue from personalization than those that don't. According to McKinsey's studies, 71 percent of customers want personalized interactions from businesses. And 76 percent become frustrated when this isn't provided.
Even basic queries need customized answers that the software must search for in a database. At the start, the chatbot called Nanci (developed by IBM and General Motors Financial Company) was resolving less than 10 percent of customer inquiries. Within two months, the success rate rose to 50%, and it's now at 60%. During the COVID-19 epidemic, when many GM owners lost their jobs and temporarily suspended payments, Nanci's implementation was particularly beneficial. The chatbot provided personalized advice and explained how deferrals would affect their account to those consumers.
From conversing to engaging - increase conversion, reduce churn
Conversational agents have their limitations, but many have already shown their benefits. And the technology is becoming more advanced. With new technological advancements on the way, it's vital to remember that success with conversational AI is more than just about technology; good experience design informed by behavioral science is critical.
The HSBC Intelligence Hub is a group of data scientists, engineers, and architects that migrate HSBC Bank data and analytics processes to Google Cloud and use AI and machine learning to extract value from the data. This group utilized AutoML Natural Language and Speech-to-Text to train machine learning algorithms to identify, isolate, and detect consumer sentiment. The bank used cloud computing services and BigQuery as a data analytics warehouse to convert spoken Cantonese and English phrases, accurately interpreted by Speech-to-Text powered by Google's AI technologies.
By leveraging chatbots, HSBC bank solved the crucial challenges. In a market like Hong Kong, where many individuals speak a combination of Cantonese and English (often combining literal translations), that requires a considerable amount of expertise to handle high call volumes efficiently and effectively. Quality assurance for this style of speech tends to be a particularly cumbersome and manual process.
Conclusion
The chatbot market is snowballing and will continue to do so in the coming years. By 2025, it is expected to be a $14B industry. To get the most out of chatbots, businesses need to tailor them according to their specific needs and integrate them with their existing customer service infrastructure. Doing so will allow the bots to provide more accurate and helpful customer responses. Customization is key to success with chatbots, and businesses that focus on it are likely to see better results.
Endnotes:
Machine Learning Engineer/Data Scientist , with experience in Project Management and IT Service Management
2yJust a comment to : "Chatbots are consistent: Unlike human beings, chatbots will ALWAYS give the same answer to a question. This is great for ensuring consistency and accuracy in customer service". I do not agree with always, depending on how the question has been asked, if the NLP model is greatly programmed and trained, can be nearly zero, but the use of always here is (in my humble opinion) not fully correct. Nice article. 👍