Customer service and customer relationship management (CRM) are essential components to a successful business. Chatbots, especially AI-enabled chatbots, have become major players in this field. Although chatbots are not an entirely new technology, the deep learning techniques available with AI have made them more efficient and even more necessary to a company than ever before.
Industry leader Mark Hurd predicted that 85 percent of customer interactions will be automated in the next year, and a company survey found that 80 percent of brands plan to use chatbots by 2020. Many companies have already begun integrating chatbots into their customer service landscape and even further into their mobile apps.
Why chatbots?
Consumers would prefer to work with businesses who use chatbots, and 53 percent of Facebook users say they are more likely to shop with businesses they can message with any questions. Chatbots offer round-the-clock assistance with more touch points for customers to interact with at every level.
Consumers are no longer satisfied with drawn-out phone calls and lengthy email interactions. Instead, they want instant gratification and answers at the touch of a button.
Chatbots are the only technology that offer these benefits.
The movement toward chatbots, especially those with AI capabilities, is the most logical way forward for customer service purposes. Not only can this technology automate many of the mundane, time-consuming processes that were previously run by humans, but it can also answer customer questions and tackle any issues in a personified, sympathetic way. With the machine learning that is built into these AI chatbots, they have become smarter with increased problem-solving abilities that allow them to produce better and better results.
How do AI chatbots work?
When it comes to customer service, chatbots have not always performed well. Although they have been excellent with routine tasks like billing, tracking and appointments, they have struggled to answer customer questions. That’s because even when the bot may have known the answer, they previously lacked the capability to interpret the question itself.
There are thousands of different ways even one question can be worded.
That’s where clustering, a deep learning technique that classifies millions of lines of unstructured conversation, comes into play. Prior to its implementation, teams had to manually input the questions that could be asked and hope they covered all their bases. With clustering technology, that is no longer necessary.
Clustering brings together all of the available customer service data from a company and sifts through it in order to pull out the common cases, frequency and urgency of requests. This allows the tech to then find the correlations between the millions of ways customers phrase a question and what is it they’re actually looking for when they do. That creates a more comprehensive variety of expressions chatbots can handle.
The AI in these chatbots is always gathering new data and is constantly adding more information to its arsenal, allowing it to continuously learn more and perform better. That means the technology can deal with a high volume of questions and can answer each one without any trouble, thus improving the customer experience.
Through the use of AI-enabled chatbots, businesses are not only becoming more efficient but are enhancing the customer experience and allowing for more in-depth customer service capabilities.