How AI impacts digital transformation digitization

How digital transformation is changing customer experience

Digital transformation and customer experience go hand in hand as organizations look to provide self-service options, highly personalized experiences and easier ways to query data.

When organizations talk digital transformation, customer experience is nearly always the subtext of the conversation.

"It's pervasive," said Glenn Landmesser, vice president of digital transformation at RiseNow, a supply chain management consulting firm based in Leawood, Kan. "With the digital transformation programs I've been involved in, I can't tell you how many times executives say, 'I want our users to have the Amazon experience.'"

How does digital transformation play into customer experience?

Businesses can embark on digital transformation efforts for several reasons. They might want to modernize the technology stack, improve operational efficiency or accelerate their response to changing market conditions. But Landmesser suggested all those roads eventually lead to customer experience (CX) -- whether the customer is an external client or an internal user.

"You could argue everything else rolls up into that," Landmesser said. "The root of why we go through the pain and effort of digital transformation is to improve the customer experience."

A digital transformation strategy focused on CX also opens opportunities for organizations to reimagine how they engage with clients and users. Transformation initiatives can revise business models along digital business lines and, when infused with artificial intelligence, add an extra dimension to personalization and customer support.

Digital transformation and CX, across industries

The link between digital transformation and CX surfaces in different ways, as evidenced by a close look into digital transformation efforts in financial services and healthcare.

Community banking: Arvest Bank's cloud journey

Arvest Bank, a community bank based in Fayetteville, Ark., is tapping cloud technology as it reinvents its banking experience.

The root of why we go through the pain and effort of digital transformation is to improve the customer experience.
Glenn LandmesserVice president of digital transformation at RiseNow

The cloud shift stems from evolving customer interactions. People usually visit one of Arvest's 200-plus locations to open a new account. But after that transaction, customers expect more of a digital relationship, noted Ninish Ukkan, CTO at Arvest.

With that in mind, Arvest selected Thought Machine's cloud-native core banking system to support its transformation. The bank earlier this year announced its first offering available through the Thought Machine platform: an equipment finance lending product. The product lets customers manage commercial loans via self-service.

In addition to providing digital banking services, Arvest's cloud approach helps it shield clients from fraud -- another aspect of CX, Ukkan noted. The cloud makes data available in real time as opposed to legacy systems that revolve around batch-oriented processing.

"Having real-time data enables us to protect customers by having full visibility," he said.

Arvest's cloud strategy also includes a five-year pact with Google Cloud, which kicked off in July 2022. At the time, the bank said the digital transformation partnership will use Google Cloud's AI and machine learning tools "to enhance customer experience" and simplify banking services.

Retail banking: Capital One investigates self-service data

Many businesses pursue self-service features with the goal of boosting customer experience. But the path isn't always easy. Capital One Software commissioned market researcher Forrester to study self-service data, a strategy that lets non-technical as well as technical professionals access data without a centralized IT group acting as the intermediary.

Graphic showing core elements of digital transformation.
Customer and employee experience are intertwined in transformation.

The resulting report, published in October, revealed that 86% of the 150 data science and analytics decision-makers surveyed considered self-service data as critical to business success. But less than a quarter of respondents reported success in engaging business-focused roles. Cultural barriers are one issue in deploying self-service data, with 75% of the respondents citing the need for a more collaborative culture.

For Capital One, encouraging self-service called for "driving the importance of data culture, data literacy, data enablement and making data a key part of your business," said Patrick Barch, senior director of product management at Capital One Software.

Another important step: forging closer ties between data producers and consumers. Barch cited the hypothetical case of an application engineering team that publishes an extract of their data to a central location, where a data engineering team picks it up and prepares it for analysis. The application team's job would seem to end with publishing the extract. But a self-service environment requires a bit more.

"If you really want to enable self-service, you have to make that application team more accountable for the quality of the data that they're producing," Barch said. "You have to get them to obsess about the customers of their data. That's a new mode of operating for a lot of teams."

Connecting with downstream users helps data producers understand the effects of any data quality or format changes that might arise, Barch said.

How to provide a great customer experience with digital transformation

An Amazon-like customer experience is a common goal for C-suite executives. Landmesser pointed to a few ingredients for transforming CX:

Look and feel. The sophistication of the interface is critical, whether users interact with a SaaS offering or a custom-built application.

Data products. Enterprises must anticipate user needs and make it simple for them to get what they want from a digital app. Those needs vary by customer and ultimately hinge on the data product that underlies the user experience.

Metrics. To measure CX improvement, an organization might use qualitative measures such as net promoter score and quantitative measures such as the number of orders placed through a new app versus email.

Early wins. CX transformation may take some time, so it's important to complement CX metrics with others such as cost reduction. That way, people can feel good about the project before the CX changes bear fruit.

Healthcare: Improving discharge instructions

Healthcare is another industry ripe for CX transformation. Stellar, an AI services company based in Indianapolis, is applying generative AI to improve discharge instructions for acute-care patients. Inadequate instructions can result in hospital readmissions, due to infections and other complications.

"We're working on how we can more proactively communicate with these patients upon leaving the hospital," said Brett Flinchum, CEO at Stellar.

This use case taps generative AI's ability to create tailored content for a personalized experience. Patients receive specific instructions that incorporate their lab data, medications and unstructured notes from the hospital, he said. In addition, AI lets healthcare organizations more easily and frequently communicate with patients -- via email or text, for example -- to remind them of post-acute care procedures in the weeks following a hospital stay.

"You're bringing much more aggressive personalized care, rather than having the patient reach out to a nurse or physician assistant," Flinchum noted. "Hyper-personalized care can mitigate that return visit to the hospital. I think that's what's incredibly transformative for patients -- that can really change their outcome."

Providing top-notch customer experiences: Horizontal CX transformations

Digital transformation is influencing use cases that cut across multiple industries. Examples include call centers and document processing. Improvements in those areas can boost CX.

Call center upgrades

Contact centers traditionally stand at the forefront of a business's customer service efforts, with e-commerce, travel and communications relying on such centralized help desks. Here, digital transformation, in the form of AI, is making its way into contact center upgrades. As with the healthcare example, the emphasis is on customized experiences.

"AI gives customers more specialized and specific experiences that save them time and effort," said Ricardo Madan, senior vice president of global technology services at TEKsystems, a business and technology solutions provider based in Hanover, Md.

TEKsystems is currently modernizing legacy contact centers and associated CX for several global communications organizations, Madan said. Those projects use Google's Contact Center AI platform. The contact center-as-a-service offering coordinates customer interactions, spanning voice and digital channels.

TEKsystems' contact center projects aim to streamline customer inquiry and issue resolution workflows. In addition, TEKsystems has layered in the Google-developed Pathways Language Model family of large language models (LLMs). Madan said the company uses the models to deploy TEKsystems' proprietary Hyper Automation Methodology (HAM) -- at a 50% reduction in time, effort and cost. HAM maps a customer's manual conversational processes, steps and workflow into simulated responses -- with the LLMs' help, he added.

Benefits of digital transformation in customer experience

Enterprises pursue a variety of benefits in their CX transformations. Here are few examples:

A cloud-based transformation strategy at Arvest, a community bank, bolstered CX by providing the following to customers:

  • Self-service loans.
  • Fraud protection via real-time visibility.
  • Simplified banking services enhanced by AI.

A self-service data initiative at Capital One incorporated the following principles for enhancing CX:

  • Emphasis on data culture and data literacy.
  • Close ties between data producers and consumers.
  • Broad accountability for data quality.

 A patient communication project at a healthcare provider aimed to improve CX through the following:

  • Discharge instructions customized via generative AI.
  • Greater personalization through inclusion of structured and unstructured data.
  • Proactive communication versus compelling patients to seek information.

Document processing applications

Generative AI, as an agent of transformation, also plays a role in the horizontal use case of document processing. This application lives at the intersection of employee and customer experience.

Field service provides one example. Flinchum said his company is using generative AI to ingest clients' training manuals so field technicians can query the data instead of combing through a paper document to find answers. For example, a field technician working on a leaky valve could ask whether the repair calls for a gasket replacement or an entirely new valve -- based on the specific type and brand of valve.

"They can get a very specific answer to that query," Flinchum said. "It's just so enabling for this field workforce."

The improved employee user experience translates into higher customer satisfaction since repairs can be made with greater speed and accuracy. The AI approach reduces repeat tickets or customer visits due to errors made during the technician's initial dispatch, Flinchum noted.

Similarly, Walmart aims to incorporate a 300-page benefits guide into an LLM to support its benefits help desk. The $600 billion-plus retailer seeks to equip help desk agents with generative AI to boost efficiency and accuracy when working with internal customers.

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