Customer service is vital to business growth and consumer loyalty. But since the advent of social media, which has endured multiple large market disruptions, there are those who posit whether the Golden Age of customer service is dead, as so many companies have offshored these departments, leaving consumers less satisfied than ever.
One way companies can provide better CS and satisfy customer needs, while reining in costs, is through advanced technologies, including generative AI. CS-oriented generative AI systems can help agents cut time spent on e-mail and chat responses, help customers quickly narrow down their issues to ensure quicker action, and power chatbots to make them more responsive and humanlike. All that can add up to big savings for businesses, while increasing satisfaction levels for CS representatives as well as customers.
On the consumer side, surveys show that some 4 out of 5 customers consider shying away from doing business with companies that have a poor CS reputation. But on the other hand a comprehensive consumer survey shows, nearly 100% of customers say that pleasant exchanges with customer service make them feel valued and more likely to remain loyal to a company.
So fostering a good CS approach – and hiring top quality CS staff – should be a no-brainer for companies. But in many companies, CS costs can reach as high as 10% or even 15% of revenues, with high turnover and constantly training new agents a big part of this burden. The temptation to cut costs on such a high-priced component of business is too great for many companies to resist. Thus many companies offshore their CS to save money – to the chagrin of many customers, who complain about language issues, a script-driven conversation process that often leads nowhere, a lack of knowledge and resources on the part of agents, seemingly limitless nested phone menus until they reach a live person, and interminable waiting periods. And while studies consistently show that bad CS hurts a company’s reputation – and future sales – the savings they can realize from offshoring CS can cushion those losses.
Thus the dilemma: High costs for good CS, versus customer dissatisfaction and potential sales losses for poor CS. For years, consultants, advisory companies, and industry experts have provided suggestions on how to improve CS, yet dissatisfaction levels among customers remain high. Perhaps it’s time to try something new – in the form of advanced technology, featuring generative artificial intelligence.
Using machine learning and AI-based analytics, companies can quickly produce appropriate scripts that their staff can utilize in response to specific situations. These scripts, based on AI-compiled and analyzed results of millions of calls about the same and similar issues, provide talking points that utilize the most effective presentation and the most relevant answers to questions and issues. Thus agents are able to respond effectively, directly – and quickly – to customer concerns, significantly increasing efficiency, as well as customer satisfaction.
Responding to emails is also a major component of a CS agent’s workday, and generative AI tools can help here as well. The average email contains about 10 sentences. Out of these, anywhere from 50–80% are rewritten in the course of responding to a customer. AI can help agents get the message right the first time – again, utilizing a large database of previously written messages, with algorithms analyzing which elements of messages were most effective. Of course, the algorithms will also ensure proper spelling, grammar, syntax, etc. – ensuring that the message is professionally written, to the point, and effective. Our data from Wordtune users shows that agents can save over 2 hours per day using an AI writing tool. That translates to 10 additional tickets per day or a 25% increase in efficiency.
Generative AI is also remaking chatbots. For years, chatbots have relied on very basic data sets and language models, enabling them to answer only the most basic questions, usually the kind of questions customers can figure out on their own. Anything more complicated often proved to be a challenge for chatbots. Now, advanced generative AI can provide companies with top-flight scripts for their chatbots, enabling them to handle incoming requests, while helping customers quickly and efficiently drill down to their specific issues. AI technology has improved to the point where algorithms can effectively decide how to handle a discussion with a customer. The generative AI algorithms used in these advanced chatbots are much more accurate than their predecessors, and utilize databases that include millions of chatbot conversations. This produces much more sophisticated scripts, increasing efficiency and customer satisfaction – and enabling companies to get the most benefit out of their chatbots.
With advanced AI technology, companies can save a significant amount of time – translating to a significant amount of money, as much as $5,700 per agent per year – on their CS costs, according to our data. And with those savings, they will be able to afford to hire the top-flight human CS agents they need, the ones who are intelligent, are able to understand and relate to customers, and can provide solutions to problems that are “off-script” – the ones that actually require human intervention.
Generative AI can thus help companies boost their CS reputations, with all the attendant benefits. No longer just a necessary evil, CS can actually become a centerpiece of a company’s persona, fostering a better reputation among customers, encouraging more return business, and providing opportunities for higher profits.
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