Five Ways AI Could Transform Your Customer Service in 2021

Five Ways AI Could Transform Your Customer Service in 2021

Feb 5, 2021

Artificial Intelligence (AI) is having a massive impact on the way businesses operate across the board.

From ‘smart’ robot-led automation to the incredibly precise (and predictive) business intelligence that can be gleaned from machine learning algorithms, AI is credited with creating new paradigms of efficiency and agility that are changing our thinking about what is possible.

Another area where AI is having a transformational impact is customer service. The likes chatbots and automated voice assistants are well established as mainstream technologies in online self-service and contact centres. According to research from PwC, 86% of businesses are already reaping the benefits of better customer experience thanks to AI.

As the technology evolves, so the opportunities to revolutionize customer experience using AI continue to multiply. In the wake of the rapid acceleration in digitisation triggered by the COVID-19 pandemic, those businesses that are able to develop exemplary models of digital service first will have a major competitive advantage.

Here are five applications of AI in customer service that are expected to grow rapidly in 2021.

Conversational interfaces

Customers are already well used to talking to ‘robotic’ assistants when they call a contact centre. Interactive Voice Response (IVR) has been around for a number of years now, taking the form of automated menu systems where selections are triggered by the caller’s voice.

But while they are a step up in convenience and efficiency from the even older ‘press X for’ type menus, there is only so much of the call journey these simple rule-based systems can reliably automate. Conversational interfaces, on the other hand, use advanced AI language processing technology to interpret a far wider range of instructions or requests, however they are phrased, and therefore can be used to handle much more of a call.

Conversational interface technology has been pioneered by now-popular ‘voice assistants’ like Amazon’s Alexa and Apple’s Siri. It is anticipated that natural language processing technologies like GPT-3 are now reaching such a stage of sophistication that AI platforms will soon be able to comprehend and imitate human conversation more or less completely, opening up the prospect of customers having their entire interactions handled by a robot – perhaps without even being aware they are not speaking to a human agent.

Augmented self-service

One of the great customer service revelations of the internet age has been that most people prefer to resolve issues for themselves, if provided with the right resources to do so, rather than contact a company for help. Hence why businesses these days invest a lot of time and effort stocking their websites with user guides, video tutorials, FAQs, opt-in workshops and more.

Chatbots and on-page avatars are deployed as a substitute for ‘live chat’ with a human agent, but they are also an example of AI being used to augment self-service. As with conversational interfaces, natural language processing has a role to play in improving interactions via chatbots to achieve more efficient, effective outcomes.

At the same time, other AI technologies like machine learning can be used to track and analyse things like search terms and on-page navigation to make accurate suggestions to help browsers find what they are looking for more quickly.

Hyper personalisation

AI-powered personalisation can be seen as another example of augmented self-service. Again, the aim is to smooth the online service experience by presenting helpful suggestions, solutions and tailored pathways in real time, but this time drawing on data held on each individual customer in the CRM or in their personal accounts.

For example, service for a particular customer can be greatly sped up if the system knows what product they own, how old it is, what the previous service history is and so on, and can therefore immediately narrow down the options and suggestions.

And this doesn’t just apply to digital self-service. The same principle can be used to automatically route calls to the contact centre to the right team. Moreover, all of the data from previous calls, as well as emails, web searches and live chat conversations, can be instantly processed so the caller doesn’t have to keep explaining what the issue is over and over again – each successive instance of contact picks up seamlessly from the last.

Dynamic service team support

The above example of AI helping customers ‘jump the queue’ in terms of not having to input the same details or repeat the same information every time they re-initiate contact also illustrates a key sticking point human agents face in delivering fast, efficient, consistent service. When calls or emails or live chat messages are being picked up by different people, each successive agent goes into the interaction cold, without all the relevant background information on each ticket or each customer available to them.

AI can have a transformative impact in this regard, by making relevant information available to human agents in real time.There are sometimes concerns that increased use of AI and advanced automation in customer service will end up forcing people out of work. But rather than replacing people, what businesses want is to free them from lower value, repetitive tasks and instead divert them to higher value activities, including aligning customer service more closely with sales and marketing. Businesses after all recognise the importance of the human touch in forging strong relationships with customers, which is important for reducing churn and therefore the relatively high costs of customer acquisition.

Rather than viewing AI and human-led service as an either-or choice, forward-thinking companies are instead looking at how the two can complement each other. This is already well advanced in the form of Robotic Process Automation (RPA) helping to automate repetitive tasks and improve the IT interfaces agents have to work with. But the next step forward is using AI to help make agent-led service more efficient, personal and dynamic through dynamic information sharing and process support.

Life assistance

Finally, and perhaps even more futuristic vision of how AI can transform service delivery is the notion of using smart assistants (e.g. Alexa, Google Home and so on) to proactively deliver ‘life assistance’ in the home. There is already a big rush by businesses to integrate their digital channels with smart assistants to take advantage of growth trends like voice search.

But another fascinating opportunity this opens up is that, instead of waiting for customers to ask a question or contact a company with a request, businesses can use smart assistants to get in there first with proactive prompts. This might be to tell a customer that a bill is due, for example, and perhaps make the necessary arrangements on their behalf once authorised. Or as we see more and more networked IoT-ready devices come on the market, diagnostic reports could be used to report a potential fault to the owner, and maintenance check-up arrangements made.

It’s much the same principle as the age-old practice of sending reminders through the post or by email, just powered by AI and made immediate via a conversational interface.