Customer preferences are no longer limited to basic profile information stored in a CRM, and today’s contact centres can understand far more about how customers want to engage.
With AI and modern customer data platforms (CDPs), contact centres can now tailor interactions with a level of precision that was previously impossible.
To find out more, we asked Martin Taylor, Co-Founder and Deputy CEO at Content Guru, to explain how contact centres can use customer preference data to create more personalized and responsive customer experiences.
Video: Customer Preferences: Every Interaction Can Now Be Tailored to Individuals
Watch the video below to hear Martin explore what’s now possible with customer preferences and how every interaction can now be tailored to individuals:
With thanks to Martin Taylor, Co-Founder and Deputy CEO at Content Guru, for contributing to this video.
This video was originally published in our article ‘12 Amazing Things You Can Now Do With Customer Preferences’
How AI Is Making Hyper-Personalized Customer Experiences Possible
Customer preferences are becoming far more detailed, dynamic, and actionable, and contact centres can now act on customer preferences with far greater precision than ever before, as Martin explains:
“Contact centres can now act on highly granular customer preferences with far greater precision than ever before. This means tailoring every interaction based on language, channel choice, time of day, and whether a customer prefers self-service, written communication, or speaking directly with a human.”
Instead of treating personalization as a one-size-fits-all process, contact centres can tailor interactions based on factors such as:
- Preferred language
- Channel choice
- Time of day
- Self-service versus human support preferences
- Written versus verbal communication styles
This allows contact centres to create experiences that feel more natural, convenient, and relevant for each individual customer.
Why Understanding Preferences Matters More for Younger Customers
Customer expectations are evolving rapidly, particularly among younger demographics who increasingly favour digital-first communication, and many customers now prefer:
- Chat and messaging channels
- Automated self-service
- Written communication over voice calls
- Fast and low-friction digital interactions
For some services, these preferences are especially important, as Martin continued:
“Understanding individual preferences is particularly important when engaging younger audiences who often favour digital and automated interactions over traditional voice channels.
For example, one national mental health service we work with offers a written chat service that is aimed at and used by young people.”
This example demonstrates how understanding customer preferences is no longer simply about convenience but about making services more accessible and effective for different audiences.
Why Customer Data Platforms (CDPs) Are Becoming Essential
Capturing customer preferences is only valuable if contact centres can operationalize them effectively, and to do this, many organizations are turning to customer data platforms (CDPs).
“To capture and operationalize these preferences effectively, organizations need a customer data platform or CDP.
Unlike a traditional CRM, a CDP acts as a system of action, unifying the organization’s multiple systems of record into a single real-time view and triggering actions – such as an automated or human outbound contact – in response to changes in information.”
Unlike traditional CRM systems, which primarily store customer records, a CDP acts as a real-time system of action by:
- Connecting multiple systems of record
- Creating a unified customer view
- Triggering automated actions and workflows
- Updating systems dynamically as customer data changes
This enables organizations to move beyond static customer profiles and create experiences that continuously adapt to customer behaviour and preferences.
How AI-Generated Data Powers Smarter Personalization
AI-powered transcription and summarization tools are now generating enormous volumes of customer interaction data, including:
- Conversation summaries
- Behavioural signals
- Sentiment indicators
- Preference insights
- Contextual interaction data
However, much of this information does not belong inside traditional systems such as CRMs or electronic health records.
Instead, the CDP interprets and contextualizes this data specifically for customer experience purposes, as Martin explains:
“CDPs also ingest vast volumes of data from AI-powered transcription and summarization tools. Most of this AI-generated data does not belong in the organization’s core information systems, such as CRMs or electronic health records.
Instead, the CDP interprets its data within a customer experience context, and securely updates the underlying systems of record, ensuring that the organization’s information is up to date and that every future interaction reflects the exact preferences of every individual customer.”
The CDP can then securely update underlying systems of record, ensuring customer profiles remain accurate and up to date across the organization.
Creating Real-Time Personalized Experiences at Scale
The ultimate goal of combining AI with customer preference data is to ensure every future interaction reflects the needs and expectations of the individual customer, which could mean:
- Routing customers to their preferred channel
- Offering the right level of automation or human support
- Adjusting communication style and tone
- Providing faster, more relevant resolutions
Because these insights are updated continuously, personalization becomes dynamic rather than static.
Contact centres are no longer relying on outdated preference forms or assumptions, and instead they can respond to customers in ways that reflect how they actually want to engage right now.
If you are looking for more great insights from the experts, check out these next:
- Why Contact Centre Data Still Lives in Silos
- How to Capture Customer Preferences From Conversations
- 3 Principles for AI Pilots That Actually Deliver
Author: Robyn Coppell
Reviewed by: Jo Robinson
Published On: 10th Jul 2026
Read more about - Video, Artificial Intelligence (AI), Content Guru, Customer Experience (CX), Customer Service, Martin Taylor, Personalization, Service Strategy, Technology Enablement Strategy, Videos
