We will probably never know who handled the first customer service inquiry, but we do know who accelerated the growth of that service and that was Alexander Graham Bell when in 1876 he invented the telephone. No longer did a disgruntled customer have to jump into his carriage and travel back to the shop that sold him the defective goods. Thanks to Bell, the customer had immediate access to someone far away to reach out to.
That was the origin of the now taken for granted Customer Service (CS) model. Over the years, as telecoms invented new and cheaper ways to contact manufacturers, the industry has grown and evolved into a highly sophisticated element of any company. And these days it is clearly the one, and often the first, part of a company to adapt Artificial Intelligence as the go to solution.
In 2018 the Salesforce’s Chief Digital Evangelist, Vala Afshar predicted that: “The line-of-business that is most likely to embrace AI first will be the customer service – typically the most process oriented and technology savvy organization within most companies.” (Source: https://emerj.com/)
And time has proven him prescient as more and more companies have discovered the value of an AI-driven customer service model. According to a report by Oracle, 78% of companies surveyed claimed to have implemented or are planning to implement AI in the customer service department by 2020.
According to a recent PWC survey, 77% of customers expect their problem to be solved immediately upon contacting customer service. What’s more, many customers interact with brands digitally – not occasionally, but exclusively. That means that technology is more central to the customer journey than ever before. Just as it has become easier for customers to get in touch with companies, it is becoming more challenging for companies to upscale to service this growing demand. This challenge of scale and timing are two tasks that AI can meet head on and win. The sophistication of the latest CS technology design guides users to relevant touchpoints along the pathway to a solution. The technology also has the added advantage of being able to capture a plethora of data and customer sentiment that companies can use to further refine their CX model.
The Language Challenge
However, with the success in CS technological sophistication comes a challenge: many companies rightly see their market as one spanning the globe, and with that reality comes the question of native language communication. They now find they are expected to deal with multiple markets and in the vernacular of those markets. In today’s world, most customers expect instant contact and in their native language. Thankfully, AI-enhanced machine translation is now available at a quality level that can help companies meet these customer demands. Machine translation technology can deliver an excellent multilingual service, and one that prevents human agents being overwhelmed by customer demands.
The adaption of AI-enhanced MT means that progressive companies that deploy this technology are able to shift their hiring focus from that requiring scarce language expert candidates to one where they can hire agents with a technology expertise and augment their skills with language technology. This fusion of human and machine model empowers companies to deliver a top-quality, language-specific and rapid customer service response. Fred Arens – Director, Gamer Support, Keywords Studios had this to say about the importance of such a model: “Actioning multilingual tickets improves user experience and the quality of our support services”.
Thanks to Alexander Graham Bell, customer service is a reality and is something that has snowballed in size since that first CS call. It is now predicted that the use of AI-enhanced customer service will increase by 143% by 2021. The reality of such a challenge cannot be ignored. The fact is most companies cannot afford to supply unlimited multilingual human agents working 24X7. That is why so many have turned to AI as an essential complementary aid to enable customer services to become more efficient. Customer service technology, when assisted by the abilities of machine translation, can provide a 24×7 multilingual solution. Customers are serviced in their native language in real time by MT-supplied translations.
Using MT technology tools like FAQs can be quickly updated, further reducing the need for agent interaction. In addition, the intelligence fed in through AI-driven technology provides a wealth of data that can also be quickly and cheaply translated into other languages so that head office can parse it to glean the information needed to improve their business intelligence. The ability to do this with speed can often give a company an edge over their competitors.
Multiple surveys have demonstrated that most customers are willing to spend more money on products if they are confident of a good customer service backup. As a result, for forward seeing companies an AI-driven, multilingual customer service model makes sense. As more product channels and markets emerge for these companies, additional scalability and language challenges will be needed. These challenges will test the flexibility and efficiency of Customer Service Centres. It can only be met by employing a robust, scalable, multilingual AI solution. And thankfully, that solution does now exist.
Aidan Collins is Marketing Manager at KantanMT.com