I spy with my real I (intelligence), something risky about AI (artificial intelligence).
ChatGPT has everyone talking about generative AI. Customer experience (CX) teams are eager to start using the technology for a variety of use cases, from automating customer service and improving knowledge management to testing and converting code from one language to another. While this technology has been in existence for many years, it has recently gained widespread interest.
But generative AI is only as good as the data (content) it’s trained on. If you don’t understand how to deliver customer-centric interactions, you can’t train an AI model to do it automatically.
Before you take advantage of AI to improve CX at scale, you need to build a solid foundation. That means using “real intelligence” (real-time connected customer data with journey analytics) to understand and solve customers’ problems through journey management.
CX Isn’t Where It Should Be
What do I mean by real intelligence? And how important is it in CX? I’ll give you a personal example.
I recently had a frustrating encounter with my mobile service provider located in the UK. While I was on holiday, I exceeded the data allowance on my mobile phone, and as the bill was not paid right away—a bill I never received—I was cut off. Using my laptop to call my provider, I was told I had to set up an account to pay my phone bill online. However, I was unable to create an account with my mobile phone number because it was already used for another account (the same account, another product). My phone was disconnected for another week until the problem was finally resolved.
Within a month of my mobile plan issue, I started facing increasingly slower internet speeds. I had to make another call I did not want to make, and before I could describe the problem they created, I had to give them my number to confirm my identity. They have asked me to create two accounts using a phone number I pay them to use, yet they still don’t know who I am.
I’m not the only consumer who experiences unacceptable customer service. Across industries, CX Index scores dropped in 2023 for the 2nd consecutive year, according to Forrester Research. The study also found that more than 80% of business leaders say improving CX is a high priority, but only 20% of brands embrace great CX as part of their brand identity.
Why don’t CX professionals fix the CX challenges seen every day? I suspect it’s because they don’t know where to start. CSG commissioned Forrester Consulting to survey 484 global decision-makers in CX, and across industries, 40% of respondents said a lack of understanding or appreciation for customer journeys are their biggest challenges to delivering successful CX.
Why didn’t the mobile service provider use connected data from my customer profile to recognize my phone number when I called? Using connected customer data, the provider should have identified my interaction channel (customer service) and the products I have (internet as well as broadband and TV), and then scanned their network to detect an internet service outage in my area.
If they had used real-time intelligence (data), the customer service agent could have greeted me by name, immediately asked if I was calling about an internet outage, apologized for the inconvenience, and told me how the company was going to help me (by restoring service). Showing customers that you know them and understand their needs shouldn’t be difficult. It takes a brain—a centralized decisioning engine to make real-time decisions about how to interact with customers to help them resolve their problems.
Artificial Intelligence Alone Is Not the Right Way to Fix CX—Yet
CX teams recognize that generative AI will improve customer experience by recognizing customer needs, recommending products and services that meet those needs, and generating appropriate documents (e.g., medical reports, insurance policies or contracts). But artificial intelligence alone isn’t how to “fix” CX.
When you invest in AI and train a model, you must use the right information and data sources. According to a 2023 study of 1,000 global companies across industries, 51% of organizations are having challenges implementing generative AI due to lack of clarity on underlying data. If a business builds a customer journey solution with the wrong data—or more importantly, missing data—it won’t solve brands’ problems. Customers will wind up irritated from a disconnected experience that doesn’t reflect your brand. Automating an insufficient process doesn’t make the process better; you still have a bad process building on inadequate rules. Rubbish in, rubbish out.
For many businesses, integrating AI is like buying a Ferrari that never leaves the garage. You may be impressed by the Ferrari when you see it in the showroom, but then you can’t drive it the way it’s built to be driven. If you can’t find somewhere in London to open it up, you’ll just end up stuck in traffic and wasting money on petrol. Like AI, the high-performance car becomes a waste of money and resources if you aren’t ready for it and don’t have the right environment to use it.
Similarly, companies may build an AI system that they can’t use properly because they lack the correct data and understanding of CX challenges and solutions. For example, if the solution to every customer service inquiry is to refer people back to the website, the virtual assistant won’t solve the problem, deliver personalized service, or satisfy customers. Leveraging generative AI for CX without a strong foundation will lack an empathy-driven approach that is required for outstanding customer experience.
To improve CX, you must learn to crawl before you can walk or run. Using generative AI prematurely before laying the groundwork is like trying to sprint when you aren’t even walking yet.
Real Intelligence Is the Real Solution for Better CX
Improving CX is all about “real”—using real-time intelligence to make the right decisions about a customer journey. If the mobile service provider in my first example had reviewed my account—and noticed that I spent 120 pounds per month on bundled TV, internet, and wireless service—they could have immediately made the decision to write off the 3–pound overage charge and restore my phone service.
Many consumers crave empathy-driven experiences from brands that know and understand them, throughout their interactions with the brand (not just at the point of sale). Companies have a wealth of customer data but don’t use it to deliver personalized experiences across channels. Brands need to use the intelligence they collect (via online profiles, surveys, questionnaires, cookies and tracking) to show customers they understand their needs—in real time.
According to McKinsey research, 71% of consumers expect companies to deliver personalized interactions, and 76% get frustrated when this doesn’t happen. Many businesses are not meeting these expectations.
Use Journey Orchestration to Connect Data and Deliver Seamless Experiences
To improve CX, we need to use real—not just artificial—intelligence to solve customer problems. By using real-time customer data and a robust journey orchestration engine, you can deliver experiences that help people make real, in-the-moment contextual decisions about what action to take next.
How can you do that?
Start with a customer data platform (crawl).
Leverage a customer data platform to collect and connect real-time data from various sources (billing, browsing and purchase history, customer service interactions) to create a real-time customer data profile for every customer. This profile is the foundation of personalization.
Analyze and orchestrate customer journeys (walk).
Journey analytics tracks the paths and steps customers follow as they interact with your organization, helping you understand how they are moving across channels and touchpoints. When customers abandon their shopping cart or stop submitting documentation for a loan application, journey analytics helps you understand what happened and where the process fell apart.
Journey orchestration (JO) refers to using real-time customer data to analyze current behavior, predict future behavior, and guide customers to the next best action to resolve their problem leveraging real intelligence. A JO system connects data, systems (e.g., contact center software, CRM system), and channels (e.g., email, text, IVR, live agent), delivering personalized, consistent messages across channels through a robust decisioning engine. For example, if my mobile service provider had detected that my phone service was disconnected, they could have sent me an email (accessible via my laptop) telling me how to quickly restore phone service. I would have immediately followed their instructions to get my phone back.
When you’re ready to use generative AI after building momentum with customer journey orchestration, you can run with it.
CSG Xponent: Improve Customer Experience Today
CX is everything, but means nothing. At the moment, CX is everything that we want to do, but it’s nothing that we are actually doing. We are going to see AI become ubiquitous and be built into everything, including CX. But most companies aren’t ready to run with it—yet.
Xponent, our customer experience solution, combines a customer data platform, customer journey orchestration and journey analytics to analyze real-time customer behavior, sentiment and ever revolving preferences to guide customers towards and be context ready for the next best action, at the right time, in the right channel—through a centralized decisioning engine.
With Xponent, you’ll be walking to a better customer experience before you know it.
“For nearly two decades, I have supported businesses to drive growth and improve their customer experiences. I’ve also been empowered and frustrated as a consumer to many of these same brands. With each year there is a new channel, new technology, and a new opportunity – but creating a complex technology and interaction landscape can be difficult. CSG can support businesses translate vision to strategy, through to execution and deliver on the customer experience, that consumers have come to expect.” — Mark Charalambous
