How CIOs use AI to elevate CX services

Feature
Mar 06, 20249 mins
Artificial IntelligenceCIOData Management

Generative AI can help staff answer customer queries efficiently and effectively. But that’s the least it can do, or what IT leaders expect of it. The key to unlocking its real power is to focus on business outcomes and highly refined experiences.

customer service
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IT industry researchers believe the biggest impact of gen AI this year will be in customer experience (CX), with organizations using vast amounts of data to communicate with consumers and resolve problems faster.

Technology specialist Salesforce reports that more than two-thirds of service professionals believe gen AI will help them serve their customers better, while Forrester expects it to give CX teams a huge boost through 2024. The tech researcher says companies will increase their use of AI-enabled tools to augment customer service agents’ capabilities. Rather than searching databases for information, agents will ask natural language questions using AI-powered tools and receive answers to customer questions in real time.

Some companies are already making significant progress. UK health solutions provider Simplyhealth uses Salesforce Einstein for Service to transform agent efficiency through conversational AI. Staff can reply to email enquiries with a GPT-enabled response and ensure the right information is sent to customers in a timely manner.

Dan Eddie, director of customer service at Simplyhealth, says the company’s AI-enabled email responses focus on three frequently asked questions: how do I change dentist, how do I change my direct debit date, and how do I change address or personal details? The GPT-enabled system searches the company’s databases and generates automatic responses, which service agents can use as a basis to quickly answer customer queries.

“The technology speeds up the whole process,” he says. “An email that would normally take an agent 12 minutes to answer now takes about a minute and a half, so you can see the value of having 10 spare minutes to do complex value-adding work within our business.”

So staff can use that additional time to process claims faster, ensuring money owed to customers is back in their pockets in two to three days. As a result, up to 92% of customers are very satisfied with the claims process, according to Simplyhealth data, and 84% of customer complaints are resolved within three days, which is way above average industry rates of 46%.

“On a day-to-day basis, the technology is helping our staff to focus on the work that’s of most value,” says Eddie. “That focus means we’re generating good customer outcomes more regularly than we were 12 or 18 months ago. We’re now knocking the ball out the park when it comes to customer satisfaction.”

Banking on AI

Kavin Mistry, head of digital marketing and personalization at TSB Bank, is another executive exploring how AI and machine learning (ML) can boost CX. To create what he refers to as a hyper-personalization strategy, he’s using technology and data to develop a deeper understanding of the experiences that people have with TSB.

The bank uses Adobe Automated Personalization Activity to build its data-led strategy, and is also exploring how Adobe’s Firefly tool, which is a gen AI model, can help enhance CX. As part of this work, Mistry’s team is developing a Money Confidence Hub, which will allow customers to track and trace their hyper-personalized goals via TSB’s online-banking app.

“We want to ensure we have very engaged customers,” he says. “Customers don’t think in product terms. They think about buying a house, or being able to do home improvements, or go on holiday. For every customer, we want to offer an individualized banking experience.”

Exploring your options

While the cacophonous hype surrounding all-things AI seems to suggest the potential of generative technologies is unbounded, Caroline Carruthers, CEO at consultant Carruthers and Jackson, says pioneering CX initiatives must be placed into context. She says AI is still very much a buzzword. “Few people are properly demonstrating the value from it yet,” she says.

Her firm’s recently released Data Maturity Index suggests many organizations suffer from an AI-induced paralysis. Only 5% of businesses boast a high level of AI maturity, established AI departments, or clear AI processes. And most data leaders (87%) say AI is only used by a small minority of employees, or not at all.

Carruthers suggests the key to CX success is finding the right tool from a kitbag of technologies. “I think we’re in danger of straying further from asking, ‘What’s the problem we have and what’s the right tool to solve that problem?’ The solution could be generative AI, but it might not be.”

For food and drinks giant PepsiCo, the use of emerging technology isn’t just about exploiting gen AI. The company’s use of data-led systems is focused on simply ensuring its customers are happy. Take the example of gamers eating the company’s tortilla chips, Doritos.

“Our research shows one of the most annoying things as a gamer is hearing other people eating snacks — and Doritos are crunchy,” says Nigel Richardson, SVP & CIO Europe at PepsiCo. The firm’s research shows almost half of UK gamers dislike eating sounds, so PepsiCo’s solution to the problem is an AI-enabled system called Doritos Silent, which uses crunch-cancellation technology developed in partnership with interactive design specialist Smooth Technology. The companies analyzed 5,000 crunching sounds over six months and created an app that gamers download to cancel it out.

“We’re always looking at how we can use technology to engage with our consumers,” says Richardson. “These kinds of tools build a direct connection between our customers and our products. They’re driving engagement and growth.”

When it comes to the impact of other emerging technologies, Richardson says gen AI has the potential to enable better experiences, particularly for customer-facing chatbots. However, PepsiCo is conscious of making sure all the issues around responsible AI, such as bias, copyright protection, and data privacy, are front and center of any developments.

“We’re doing things internally first,” he says. “We’ve got a big partnership with Microsoft, which we started in 2020. We work a lot with Microsoft and other technology companies, but we’re seeing customer service is an area where generative AI could dramatically improve experiences.”

Developing a strategy

Tech analyst Gartner suggests most CIOs are in a similar position: 2024 will be the year of planning for the implementation of generative AI, while 2025 will be the year of execution. Businesses that start to explore AI this year must think carefully about the providers they use.

Hakan Yaren, CIO at APL Logistics, says his firm has been exploring AI and ML for several years, particularly to refine supply chain processes. As these developments continue, and as the firm starts to explore how AI can improve CX, he expects his IT department to work with a range of partners.

As well as major technology operators such as Microsoft, Oracle, and integration specialist Axway, Yaren says APL Logistics is likely to tap into best-of-breed solutions from specialist providers. “The other area that we continue to look at, because the barriers of entry are much lower, is start-ups,” he says. “There are companies coming up that are trying to solve specific problems.”

Ben Elms, chief revenue officer at internet connectivity specialist Expereo, is another business leader whose company is looking to develop an in-depth view of its customers’ requirements.

The company’s customers can use an interface called expereoOne to analyze global network performance, and Elms is keen to bolster CX efforts further with AI. The firm is exploring Salesforce’s ServiceGPT and Einstein technologies, and they’re building a knowledge base on the provider’s Sales Cloud platform as well.

In his previous role at Vodafone, Elms led one of the first implementations of Einstein. “They used it as a global trial on my workforce, which was about 1,500 people around the world,” he says. “We went through the learning journey with Salesforce on Einstein, both good and bad. Now we’re at a place where my task for this year is getting this technology implemented at Expereo.”

While the GPT-powered knowledge base at Expereo will be used to deliver faster responses to queries, customers who prefer to speak with a human will be supported through a multi-channel approach. Across all areas of service provision, Elms wants to give customers more in-depth information.

“I’m investing heavily in applying AI to expereoOne so I can offer customers predictability in the future,” he says. “From our intelligence, we want to be able to suggest alternative network infrastructure and architectures. It’s very future-focused, but that’s the kind of investment I’m making.”

Keeping AI in check

These kinds of innovative approaches suggest AI will have a big and long-lasting impact on CX. However, Bev White, CEO at recruiter Nash Squared, says AI should not be seen as a silver bullet for CX challenges. Like Expereo’s Elms, she raises the importance of human agency.

“When we buy things online, and we interact with automated technologies and AI, we don’t always want to be handled by a chatbot,” she says. “Sometimes, we need to speak to a human being. If you’re buying a complicated or expensive thing, such as a car, you don’t want to just rely on interacting with technology.”

White says high-quality CX will always involve a careful blend of interactions between AI and human professionals — a sentiment that resonates with Simplyhealth’s Eddie. While his company is already benefiting from using gen AI across customer services, he says emerging technology only boosts CX if it’s used to augment professional talent.

“I don’t think AI is the future; I think it plays a part in the future,” he says. “Success still comes down to having the human involved in understanding the complexity of the customer requirement. We’ll continue to test and learn, and we’ll evolve the capability we have. But human expertise is always at the heart of all the great stuff we do.”

Mark is a business writer and editor, with extensive experience of the way technology is used and adopted by blue-chip organizations. His experience has been gained through senior editorships, investigative journalism, and postgraduate research. Having formerly been an editor at Computing, Computing Business, and CIO Connect, Mark became a full-time freelance writer in 2014. He has developed a strong portfolio of editorial clients, including The Guardian, Economist Intelligence Unit, ZDNET, Computer Weekly, ITPro, Diginomica, VentureBeat, and engineering.com. Mark has a PhD from the University of Sheffield, and a master’s and an undergraduate degree in geography from the University of Birmingham.

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