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Harness GenAI with Unified Customer Data for CX & EX Orchestration

Stellar Elements Generative AI Series (Article 3 of 5)

We recently overheard author and evangelist David Meerman Scott explain AI this way: “AI is just data times math.” But the truth is, it isn’t “just data.” Gathering meaningful customer journey insights is about more than just how much data you have. It starts with having the right data that is comprehensive, well-organized, reliable, and easily accessible. We refer to it as a unified customer intelligence repository, and it can transform your CX from a lackluster, one-size-fits-all experience to a customized, in-the-moment interaction.

It’s Not Just About Data—It’s About Orchestrating Relevance

In our second CX Series installment, Drivers for CX Success: GenAI and Customer Journey Orchestration, we talk about real-time customer journey orchestration as the place where GenAI magic shines. 

Here, we will hone in on the backbone of successful customer journey orchestration—unified customer intelligence and interaction data. 

To succeed at real-time CX orchestration, it's critical first to get a unified, contextual view of the customer journey—when, where, how, and why customers interact with your brand and support systems, including where they encounter challenges along the way.

The main questions we look to address now are: What is the role of unified and continuously updated customer data in real-time CX and EX orchestration? How (with the help of AI) do we activate this data to power the next best customer or employee action?

The Data Complex

Let’s face it; we collectively are not at a loss for data. We are, quite literally, hoarding it. More than 2.5 quintillion bytes (that’s 18 zeros for those counting) of data is generated each day, after all. 

But, it’s deciding what we do with this data that is the real struggle.

People are so overwhelmed by the sheer amount of data that it’s actually impacting decision-making negatively—it is estimated that up to 73% of data is going unused for analytics.

Image of code streams

Now let’s put this in the context of the CX. You might have tons of data on your customers. Without proper data analysis and context, however, it’s easy to miss the nuances that occur as customers interact with your products and channels. According to the Stellar Elements CX20 Global Report, 50% of business leaders see the AI Readiness gap widening. Not having full visibility into the customer journey across your entire brand perpetuates the (very, very wrong) assumption that customers are fine with a “one-size-fits-all” journey. 

Eighty-eight percent (88%) of contact center agents say customers have higher expectations than they did in previous years. It’s table stakes for CX teams to know their customers inside and out, to the point where they can essentially predict their needs before their customers even voice them. The only way to achieve this level of customer orchestration is with the right customer intelligence.

Behold The Power of Unified Customer Journey Intelligence

We’ve already discussed the power of real-time, GenAI-powered customer journey orchestration and its impact on customer service and loyalty. Now, it’s time to dive into the foundational layers needed to make it a reality. 

Successful, in-the-moment orchestration hinges on one main thing: having unobstructed, accurate, cross-platform information on your customers. Data on how any particular customer is interacting with your brand across any product or service via any channel or device. This granular customer data is gold.  

Consider these two very different customer experiences with outsourced IT services:

Scenario 1

Diagram of scenario described in text below

Ed visits his company’s outsourced IT support site after his laptop refuses to reboot. He has to find and navigate to it from his mobile device, which takes him to a generic customer support page. Ed spends too much time searching without success, only to call a service agent. He has to rehash the entire ordeal once he (finally) gets through. No solution is in sight, and it’s been hours. Ed is fed up.

Scenario 2

Diagram of scenario described in text below

Taylor cannot connect to her company’s VPN. She is immediately redirected to a personalized customer support page on her mobile device, where a chatbot offers up a few top fixes to try based on everyday issues, service tickets, and customer history–checking in along the way. If there is still no success, the chatbot automatically connects Taylor to a service rep, who has the whole interaction history and can troubleshoot further on the spot. Taylor is back online in minutes. She’s now a loyal advocate.

These scenarios showcase the power of a dynamic customer journey fueled by intelligence—and what happens when companies don’t tap into the full power of their customer data and settle for a one-size-fits-all approach.

Building a Unified Customer Intelligence Repository

Customer journey analytics, mapping, and real-time orchestration enable you to build adaptive interactions with customers that promote positive experiences and loyalty.

But, to truly harness the power of Generative AI to transform the CX, you first need accessible, robust customer data. 

The way to achieve this is by building a unified customer intelligence repository. 

Think of it as a Customer Data Platform (CDP) that marketing departments use to gather intel on a specific individual and trigger marketing events, but on a grander, cross-channel scale. A unified customer intelligence repository aims to collect, organize, store, and analyze data to supply a detailed, multidimensional view of the complete customer journey. Not just who the customer is—but also their specific interactions and unique journey with your brand across devices or channels.

Embedded with customer intelligence and context (i.e., “This is what customers are doing,” “These are the likely ways that they're going to interact with your product and service,” etc.), CX and EX teams can then activate this unified data to provide instantaneous customer and employee assistance, when and where needed. It’s the difference between providing a templated customer journey and an adaptive, real-time journey unique to each individual customer. 

Tying a unified customer intelligence repository into your customer orchestration is powerful—and GenAI makes this even more powerful.

So, how do you build one? 
Start by understanding and aggregating your customer event data.

Abstract image of streaming lights and code

Your most valuable source will be your internal customer event data collected across all your customer systems (including Adobe DX and ServiceNow) and all your customer interaction points (including the web, mobile apps, physical interactions, and customer service experiences). There are multiple benefits to aggregating this data. It will become the foundation for the data you need to train your large language models (LLMs) or machine learning (ML) models on the next best action, which will predict and respond to customers and employees in the moment. It will also provide real-time context for the models when they are already deployed.

Next, connect your data sources to your customer journey analytics platform. This may be through tracking pixels, API calls for the various services in your web or mobile application, etc. from these systems. Organize the data around each customer based on their needs (via continuous data ingestion based on the customer actions). This contextual data setup enables you to do customer identification and matching on the fly. It can also be used for post-event analytics and real-time access via context APIs, enabling your customer support services to understand the customer's context.

And then, it’s time to activate the data through real-time customer journey orchestration. Once you have your customer intelligence unified, it’s time to activate it—with some help from GenAI. There’s no wand-waving magic; the technology is fundamentally tied to the depth, breadth, and integrity of the underlying data.

Image of woman happily looking at code

But, the potential of GenAI is limitless if propelled by a unified customer intelligence repository as its backbone.

It opens the door to some fascinating CX opportunities. It enables you to identify which event data you can turn into powerful contextual customer assistance prompts and leverage low-code orchestration tools to power the next best customer action. For example, if a customer is looking for iPhone 15 availability in their city, a code snippet can be sent automatically to the ordering system to check for availability in that region. A contextual message can then open during the customer’s browsing session that says, “Hi John, the next available shipping date for you is October 3rd. Should we place your order?”

A Quick Note on Data Privacy

You can’t talk about data without also addressing privacy. There are a lot of consumer data protection laws out there that companies need to follow to prevent data breaches and identification theft (and maintain a good reputation), including the EU’s GDPR and various state regulations within the U.S. Though data privacy compliance is not the job of CX teams, you still need to play a part in ensuring sensitive customer data is kept safe.

Don’t feed sensitive information into your GenAI tools. Work with your data or security teams to embed data security protocols into your customer intelligence repository and keep sensitive data at bay. Simple steps like creating a unique customer ID that hides or redacts sensitive details can facilitate seamless customer journeys without putting customers or your brand at risk.

And Lastly, Some Words of GenAI Wisdom

No doubt, the power of GenAI to transform customer and employee experiences is incredibly alluring. It’s easy to get starstruck at the possibilities. It’s also easy to get overwhelmed—especially when you’re not the Googles, Amazons, or Apples of the world. 

Know that it’s OK to…

Keep it simple: Jumping into creating and training a custom AI model might be unnecessary at this stage—not to mention expensive and time-consuming. Test drive free tools like OpenAI’s LLMs (from the creator of ChatGPT), which offer a secure and efficient way to store and analyze your data. Once you’ve uncovered any constraints or limitations with OpenAI, then consider building your model if resources allow.

Start slow: Hold off on deploying these tools in corporate or customer-facing scenarios for now. Instead, allow your team to explore and learn—this hands-on experience fosters creativity. 

Experiment: ML, particularly generative AI, is still uncharted territory for many. It’s unrealistic to expect innovative uses from tools we are unfamiliar with. Encourage your teams to experiment with them, not for immediate application, but to discover their potential. Let them explore. Get them to understand these tools and platforms so they can elevate your own when the time is right. 

And know that it's constantly evolving. AI technology and use cases are ever-changing. Try to think of another technology that has transformed our lives so profoundly, so quickly—and continues to evolve almost daily! So take a deep breath and try to keep your pulse on the latest AI innovations that can shape your future CX initiatives. 

In our final two articles in this series, we’ll present a few real-world use cases for using GenAI to activate customer intelligence and transform your CX and EX.

Next up on the Stellar Elements GenAI series

A look at the top use cases for powering CX and EX success with GenAI-enabled orchestration.

Sign up for the next installment of our GenAI series. Cut through the clutter and move past the hype to make the right decisions.

More about Stellar Elements

A global design and development firm with a 20+ year track record of delivering and scaling connected customer, employee, and partner experience solutions for organizations in the telecom, financial services, retail, technology, quick-service restaurant (QSR), and healthcare industries, we answer the most critical and essential questions for our clients in every corner of the world. Our customers include EE-BT, Globe Telecom, Capital One, Mercedes-Benz, Dell, and 50+ Fortune 500 companies.

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