As AI ushers in an era of hyper-personalized digital experiences, it’s hardly revolutionary to say no two customers are truly alike. But if there’s one thing they do all share, it's an expectation that companies anticipate their needs—and design service experiences accordingly.
A recent ServiceNow study of customer expectations in the AI era uncovered a striking reality: 47% of customers would switch to a competitor due to poor or slow service, and nearly half rate their current service experiences as average or worse. Meanwhile, 50% cite lack of empathy as their top frustration—yet fewer than one in four executives recognizes this as a problem.
Understanding who your customers are—and what drives them—is the first critical step in closing the gap.
Using data and interviews from our research, we created snapshots of four unique personas that reflect distinct customer mindsets and behaviors. Each snapshot includes insights on how to meet the persona’s expectations. You’ll also hear directly from real people who fit these archetypes through quotes gathered in our research. The result is portraits from the front lines of customer experience (CX) in the age of AI.
The Frustrated Advocate knows exactly what she needs. She's already tried basic fixes before seeking support—so when she finds herself answering an endless series of circular troubleshooting prompts from a chatbot, her frustration spikes. Finally, buried in a menu, she finds a way to connect with a support rep who solves the problem in minutes.
Her frustration isn't with the outcome—it's with being forced through a channel that was never going to work for her situation. She walks away feeling angry and unheard.
The Frustrated Advocate represents the 46% of customers who say current chatbots don't understand their questions, and the 87% who still rank phone calls as their preferred communication channel. Yet only 7% of executives plan to prioritize phone support over the next three years—a channel mismatch that has measurable consequences.
Here’s how CX leaders can take care of their Frustrated Advocates:
- Match your channel to their preferences. No one wants to be stuck with ineffective AI when they know they need human help.
- Perfect the handoff from chatbot to human.
- Start measuring what matters, from empathy and effort scores to trust indices.
Human or AI? The Efficiency Expert doesn’t care. If he can take care of his problem quickly via an app, he’s all for it. Just don’t waste his time or make him repeat himself. Give him the right tool for the right job, and you’ll have a customer for life.
The Efficiency Expert represents the 72% of customers who cite complexity as the key factor in preferring human versus automated service, and the 75% who prefer self-service first. What earns his loyalty is the absence of friction across all interactions.
Here’s how to keep the Efficiency Expert happy:
- Unite data to eliminate repetition. Every interaction should build upon the last.
- Deploy strategic customer relationship management (CRM) as an experience platform. Right now, only 52% of respondents have end-to-end CRM supporting the full life cycle, and that translates into customer frustration.
- Free your service reps from busywork. Let AI handle the admin so that humans can problem-solve the complex stuff.
The Delighted Early Adopter walks into a service interaction with low expectations and leaves as an advocate.
For example, let’s say a customer is shopping for a product and doesn’t know which one to choose. She clicks on a chat option expecting a generic sales pitch. Instead, AI reads her browsing history, asks the right questions, and leads her to the appropriate product—saving her money in the process.
The Delighted Early Adopter represents the 40% of customers who already report experiencing improved speed and efficiency from AI, and the 53% who expect it to be AI's top benefit going forward. What she experienced is still the exception: Only 32% of organizations have made meaningful progress improving responsiveness through AI.
Here’s how to create more Delighted Early Adopters:
- Deploy trustworthy, autonomous AI for self-service. Seventy-five percent prefer self-service first so long as it is effective and honest—not just optimized for conversions.
- Enable personalization at scale by integrating your data across silos. This will allow you to treat each customer as a “demographic of one.”
- Be proactive, not reactive. Use predictive analysis to anticipate needs before they escalate.
When something goes wrong, the Relationship Builder isn’t looking for a policy recitation—he's looking to feel recognized.
After navigating automated menus and repeating his issue multiple times, he finally reaches a representative who sees his history, thanks him for being a longtime customer, and goes off script to make it right: free parts, installation support, and a follow-up call to confirm everything worked.
The Relationship Builder represents the 87% of consumers we surveyed who prefer phone calls, and the broader customer population that values emotional connection above all else—responsiveness, trustworthiness, security, human understanding.
Here’s how to support the Relationship Builder:
- Use AI to enable human empathy at scale by freeing up your reps’ time to focus on person-to-person customer support.
- Prepare your teams to use AI effectively through effective training and the right tools.
- Reorient your service rep role from reactive case processor to true customer advocate. Let AI handle the tasks while they handle customer connections.
Taken together, these four customers reveal the core challenge of modern service: The experience each one needs is different, but the infrastructure required to deliver all of them is the same. It demands unified data, intelligent routing, seamless transitions between AI and human support, and service representatives who have both the tools and the time to actually connect.
That's the shift. And the customers who experience it become the ones who stay.
Get more insights in our latest research report: The CX Shift.
