Leveraging data for AI-powered customer experiences
Customer data refers to all the interactions, behaviors, and attributes collected from various touchpoints—such as websites, mobile apps, emails, SMS, social media, in-store visits, and customer experience interactions. This data includes:
Behavioral data (website visits, app usage, email opens, purchase history)
Demographic data (name, age, location, preferences)
Transactional data (purchases, returns, subscriptions)
- Engagement data (support tickets, chat interactions, survey responses)
The importance of data quality when using AI-powered tools
Customer data becomes actionable intelligence when processed through AI, enabling customer experience teams to deliver personalized experiences at scale. However, a CDP is essential for maximizing AI solutions relating to customer experiences for three key reasons:
Unified customer view: CDPs aggregate data from all touchpoints (website, app, voice, email, chat) to create complete customer profiles. Without this unified view, AI tools receive fragmented data, producing less accurate predictions and personalization.
Near real-time data accessibility: CDPs make customer data available to AI systems, enabling near real-time personalization during calls, adaptive IVR responses, and timely agent suggestions. This immediacy is crucial for in-the-moment decision making.
Data quality and governance:
CDPs standardize data formats, remove duplicates, and ensure compliance—critical for AI systems that depend on clean, consistent data to function properly.
When built on a robust CDP, AI solutions can deliver truly personalized experiences, accurate predictions, and meaningful insights that drive measurable business outcomes.
For customer experience support teams:
Voice analytics detect frustration, allowing agents to adapt in near real time
IVR systems use past interactions to route efficiently and offer relevant self-service
Agent copilots surface relevant case history and suggest solutions during calls
Omnichannel analytics reveal support trends across channels, improving resource allocation
Predictive models identify at-risk customers before they churn
For customer experience sales teams:
Voice intelligence spots buying signals in conversations
Customer profiles combine web behavior with voice interaction history for targeted offers
Transactional analysis reveals optimal upsell timing and products
Engagement patterns show which customers are primed for expansion
AI identifies cross-sell opportunities based on similar customer journeys
The combination of rich customer data and AI-powered analysis transforms reactive support into proactive relationship building, while enabling customer experience teams to target the right opportunities at the perfect moment.
Agent productivity: empowering teams with AI
Customer support has always required a balance of speed, empathy, and efficiency, yet even the best agents can struggle when systems are fragmented and data is siloed. AI-powered tools change that equation by automating routine tasks, surfacing real-time insights, and guiding agents with intelligent recommendations. The result: faster responses, more personalized service, and agents free to focus on what humans do best, building relationships.
Once viewed as cost centers, contact centers are now becoming strategic growth engines. AI-powered solutions give every agent full customer context—preferences, history, and purchases—before a conversation even starts. Routine inquiries are handled by AI voice agents, while human representatives tackle complex, high-value interactions. That means higher efficiency, lower burnout, and elevated CSAT.
Conversational AI agents engage naturally, reference unified customer data, and know when to hand off to a human, ensuring smooth interactions from start to finish. Every conversation becomes a learning opportunity. With real-time analytics and coaching insights, leaders can monitor quality, improve compliance, and continuously enhance performance. AI turns every service moment into intelligence that drives better experiences and measurable business growth.
Unlocking new use cases with a CDP
If your company is investing in new tools, you need confidence that it will scale alongside your evolving needs. A CDP powered by first-party data delivers a comprehensive, near real-time view of customer interactions, unlocking valuable opportunities across customer experience, and beyond.
Here’s a perfect example to illustrate this:
Sarah leads the customer experience team at a fast-growing e-commerce company. Lately, her team has been drowning in support tickets, and customers are frustrated with long wait times. They have a CRM, so agents can see basic customer details like names, past purchases, and support history—but that’s not enough. They’re still handling every case reactively, with no real way to prioritize or personalize interactions.
Enter the CDP. Sarah’s company integrates Twilio Segment, pulling in near real-time behavioral data from their website, app, and email engagement. Suddenly, her team has a full picture of each customer’s journey—not just their past purchases, but also what they’ve been browsing, whether they abandoned a cart, or if they recently interacted with a marketing campaign.
Now, when a high-value customer submits a ticket about a delayed order, the system flags them as a priority, ensuring they get faster service. If another customer reaches out with a product issue, the agent sees that they’ve been watching troubleshooting videos but still need help, allowing for a more targeted and efficient response.
Even better? With AI-powered insights, the CDP suggests that customers who frequently contact customer experience departments about sizing issues also tend to return items. So, Sarah’s team proactively sends a fit guide to customers browsing those products, reducing future support requests.
By unlocking these new use cases, the CDP transforms customer experience from a reactive cost center into a proactive, revenue-driving team, improving customer satisfaction while making the agents' jobs easier.
