Summarize this page with popular models
Summarize this page with popular models
Live interactions have always outpaced personalization strategy—until AI could brief an agent mid-conversation.
4 minutes de lecture
Personalization is nothing new, so I’ll spare you the extensive intro. But what is new is how it’s being used. Namely, it’s moving into live interactions, opening a new world of possibilities for improving the customer (and agent) experience.
Personalization used to live in:
These are still great applications, but they’re rather unidirectional, and don’t work for the minute-by-minute nature of customer conversations. Encounters feature unexpected questions, changing needs, difficult customers, and unpredictable pivots.
We need to figure out how to adapt the most useful lessons of personalization to the place that would benefit most.
The downside (and thrill) of live interactions is that no matter how experienced you are at personalization, you still can’t predefine the perfect conversation. But you can improve how you respond. So step away from the need for full control, and instead develop a strategy for personalization that evolves in parallel with every possible conversation.
First, keep the good stuff: The human still leads the conversation. But as we expand AI use cases into CX, there’s a huge opportunity for AI to help agents be more informed and responsive, without losing that human touch.
AI-driven personalization doesn’t have to undermine authenticity when used properly. Even the luxury shopping industry, long defined by white-glove service and singular attention for every buyer, is leaning into the possibilities.
According to a piece from Boston Consulting Group, the luxury brands adapted AI only to the parts of the shopping experience that didn’t require “authenticity” as a differentiator. Rather than doing “mass personalization,” they used AI to identify leads, schedule follow-ups, and remind sales associates of crucial client information and purchase history when the shopper appeared in-store.
Knowing where AI belongs and where it doesn't is the real heart of the matter, and that concern should carry over into how personalization is delivered.
Extrapolating from the luxury shopping example, AI-driven personalization works exceptionally well when it’s used as a driver for human decision-making. “Agentic AI is about allowing a customer to pull the solution to their problem instead of a brand pushing a solution toward them,” says Mark Abraham, managing director, senior partner, and personalization lead at Boston Consulting Group.
Instead of focusing on “what do we show the customer based on their browsing and purchase history?” organizations need to move to asking “how do we lead the customer to where we want them to go.” It’s a much more active approach.
It’s also more likely to succeed. “CMOs must pivot toward active, course-changing personalization that reveals customers’ hidden needs, validates their decisions and pulls them from pitfall to purchase,” says Audrey Brosnan, Senior Director Analyst at Gartner. According to further Gartner research, guided, adaptable personalization that targets inflection points in the customer journey largely outperforms static “next best action” style tactics.
We tend to think personalization is for the customer, but in practice, the beneficiary of improved personalization is also the agent.
AI personalization delivers:
The best way to personalize an interaction is to better equip the person running it. For example, a McKinsey article from the past year highlights how a major US airline used AI to enable its customer service team to better serve high-value or churn-risk customers. By differentiating customers by context, agents could adapt how they engaged with them.
For example, a customer who was generally happy with the company would be identified as more amenable to an upsell than an unhappy customer, who probably shouldn’t be immediately shunted into a sales funnel.
This strategy resulted in a 51% reduction in churn intent among at-risk customers and a staggering 800% increase in customer satisfaction.
It’s important to note that over-personalization can absolutely go wrong in the agent experience as well:
More isn’t always better. The same tools that build trust can just as easily erode it if pushed too far.
Marketing wisdom is all about learning to tell when to use personalization and when not to use it. A 2024 Gartner survey found that customers who experienced personalization in the purchase process were twice as likely to feel overwhelmed by it as to feel helped.
There’s a balance to be struck between guiding a customer exactly when they need a helping hand and being near-omnisciently creepy by referencing data the customer didn’t expect you to have, or by sending overly specific recommendations without added context.
Don’t forget to define the boundaries of what is appropriate and what privacy means in customer interactions. But when you do figure out where to apply personalization and stick the landing, then you’ll realize personalization is no longer just for marketing; it can live in sales, after-sales, and customer success models. More than anything, it can live in conversations.
Co-Founder & CTO, 8x8
Bryan Martin is Co-Founder and Chief Technology Officer at 8x8, where he leads the company's technology vision across AI, cloud communications, and platform architecture. One of the original architects of 8x8's cloud infrastructure, Bryan has shaped the company's technical direction from its early days as a VoIP pioneer to its current position as a Communications Intelligence Platform. He holds 137 U.S. patents spanning semiconductors, video processing, computer architecture, and communications — and brings that same builder's instincts to how 8x8 approaches AI: specific use cases, clean handoffs, and outcomes that hold up under scrutiny. Bryan received Bachelor's and Master's degrees in Electrical Engineering from Stanford University.
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