Six ways AI can improve customer experience

Artificial intelligence (AI) is being used to chart a customer experience journey that fits the demanding expectations of digital consumers. Here are six new approaches businesses can take to boost customer engagement, experience and success

1. Frontline customer self-service

Artficial intelligence (AI) can be used in the frontline of customer service, helping customers get instant answers, fast outcomes and consistency.

The infuriatingly long wait for a phone call with a live agent, just to receive an over-simplistic answer, is now being replaced with chatbot technology, powered by AI, for an immediate solution.

“Chatbots are capable of sourcing data at a much faster speed than an individual working behind the scenes,” explains Bernd Gross, chief technology officer at Software AG. “This not only speeds up the time taken to deliver a service, but it also frees up employees’ time to focus on more value-added tasks.”

This frontline revolution is in its early stages, but there are a number of industries that have already embraced self-service customer experience.

Financial services, travel and hospitality are “leading the pack”, according to Ryan Lester, director of customer engagement technologies at LogMeIn, “because they get a lot of similar questions all of the time”.

AI in customer self-service will help reduce these repetitive, low-value interactions; the frequently asked questions will be handled by the tech, instead of being sent to a live employee or agent.

2. Enhancing automation

Businesses have been automating laborious, mundane tasks for years now. But instead of a human managing this process, AI has become good at enhancing the automation of repetitive tasks; it can become the layer that monitors and manages these automated processes.

It does this in two ways, according to Rufus Grig, chief technology officer of Maintel. The first is that AI can start to replace the conversations customers currently have with automated systems “with technology that will understand natural language input, whether typed or spoken”, Mr Grig explains.

“That’s the difference between saying ‘Alexa, play Radio 4’ as opposed to fiddling around with the tuning settings on your digital radio,” he says.

The second area in which AI can enhance automation involves the integration of internal processes.

“We have been using robotic process automation for some time now, effectively using software agents or ‘bots’ to automatically drive computer systems to save the need for human workers to carry out multiple repetitive tasks. This works very well without the use of AI, but AI can add some value, for example enabling image recognition, or inferring emotion or intent from a customer’s text-based input,” says Mr Grig.

3. Customer acquisition and retention

There’s a really great opportunity with AI for organisations to be more proactive and predictive in how they interact with both new and existing customers.

“AI can help with delivering more personalised interactions in real time,” says Mr Lester of LogMein. The prime example is Amazon. If you go on its website and you’re looking for a new kitchen appliance, the AI can look at what you’re searching and your previous search terms, and suggest potential products that might be of interest.

This capability can be run out at a very low cost. Rather than putting the onus on a customer to search through a website, the AI can start engaging with that customer proactively, asking them some discovery questions to help find the best, most relevant product. Importantly, because it’s AI, the more data you feed into it, the more it knows about the customer, or as it interacts with more customers, the better it gets at providing the right suggestions.

However, organisations should not be proactive for proactive’s sake. A consumer will not want to be recommended a TV if they’ve just bought one, for example. To overcome this, the technology needs to be made contextually aware. There are good and bad applications, but it comes down to how you’re applying the AI, rather than the algorithm itself.

From an existing customer perspective, AI can help organisations master cross-selling by providing relevant products and services based on granular personalisation and prediction models. “Personalisation will act as a catalyst in winning over existing and potential buyers,” says Anu Jain, executive vice president, general manager of LiveArea.

4. Co-pilot

AI is increasingly being used behind the scenes to help live agents and employees deliver better customer experience.

At the moment, according to LogMeIn’s 2018 AI Customer Experience report, 25 per cent of an agent’s time is spent looking for relevant information to help a customer.

Acting as the co-pilot, however, AI can gather information on the customer in real time, informing the agent of who they are talking to, the customer’s history with the brand, their preferences, the potential problem the customer is having and how to solve it. Having this information during the interaction provides agents with more time to spend on resolving the issue.

As with the adoption of any technology, there is some hesitancy, perhaps even a fear of job losses. But once implemented, employees embrace these new ways of working because it helps them do their job better, in an easier way.

On a related note, customer experience can also reflect on employee experience as the application of AI internally can boost productivity and job satisfaction.

5. Personality matching

This emerging trend involves understanding how the consumer likes to engage and matches that persona with the best agent or communication tool available.

“Some consumers like to be short and to the point; they just want the immediate answer with no small talk, while others like to have a bit more of a social interaction,” explains LogMein’s Mr Lester.

The speed and power of the technology produces new ways to look at existing data in real time. As such, AI is becoming more capable of capturing information about sentiment with behavioural analytics. It can then build up a personality profile of a customer, which will come to define the agent-routing process.

Natural language processing has a role to play. “The technology can process reams of customer data coming in through a variety of channels, phone, social media or email, for example,” says Tiffany Carpenter, head of customer intelligence at SAS UK and Ireland. “The AI engine rapidly picks out valuable information, including overall sentiment, instances of complaints and regularly repeated questions, to help the company address common issues and get an early warning if customers are becoming more unhappy.

This unification of customer data is crucial for improving customer experience. “To this end, AI is beginning to be used for data infrastructure tools,” says Ben Lorica, chief data scientist at O’Reilly Media. “This means that tools for data-gathering, like mobile apps and sensors, to data-ingestion, data-integration and data-preparation are all being augmented with AI.”

6. Reducing customer friction

AI can help navigate the whole customer experience journey, and identify where friction points occur and where experience levels fall down.

Compared to a human, reading through endless transcripts, AI can easily find the most frequently asked question where customers aren’t getting the result they want. “This helps you go after that low-hanging fruit faster,” explains LogMein’s Mr Lester. Businesses can then identify problems quickly and amend the customer journey appropriately.

“AI enables real-time customer engagement, as well as instant identification and remediation of service-level issues,” says Mr Gross at Software AG. “With its ability to help companies understand their data and prioritise areas of the customer journey quickly, it becomes possible to improve and enhance these services, with more informed decision-making.”

O’Reilly Media’s Mr Lorica believes businesses would be foolish to overlook the use of AI technologies in customer experience.

“It’s a no-brainer,” he concludes. “With the ability to process large-scale data, to understand and process customer feedback, the benefits to a business are second to none.”