Introduction

In modern-day B2B, personalization has made the drastic transition from a nice-to-have to a must-have, with buyers expecting that their every interaction with the company is based on their specific needs, behaviors, and intent, and that all changes take effect instantaneously. But for many organizations today, there seems to be an insurmountable chasm, with the collection of data on one side and the implementation of actionable personalization on the other. With the data disjointed on several different platforms, teams are unable to activate insights at speed, and ultimately, the user experience gets compromised. This is where CDPs come in to seal the gaping hole between fragmented data and serious engagement in real time.

Unusual for traditional CRM and analytics tools, CDPs are designed to unify first-party data from all channels into one single view of the customer, the last enduring truth about that customer. This customer profile forms the very base for the delivery of hyper-relevant experiences-be it a personalized product recommendation, dynamic website content, or behavior-based nurture journey. A CDP's true strength lies not just in the unification of data but in turning that very data into action across the entire buyer journey almost instantaneously. That is where CDPs, when embedded in your martech tool kit, empower companies to have real-time decisions enabled across their teams and channels.

This blog will deep-dive into how CDPs enable real-time personalization at scale, from a strong data foundation to orchestrating personalized campaigns across touchpoints. It will share how the best B2B brands are using CDPs to grow their businesses; what feature sets to seek when deciding on a platform; and how to avoid common pitfalls during implementation. Whether you are considering CDPs for the first time or want to take your personalization strategy to the next level, this guide will provide insights and frameworks to turn data into action and action into impact.

What is a CDP? Why Does It Matter for Real-Time Personalization?

A Customer Data Platform is an aspiring collection of activity, intended for popularly collecting, unifying, and activating customer data from several sources at one time in real-time. Think about it as the brain of a marketing stack, it takes in behavioural, transactional, and demographic raw data and determines a usable, continuously updated customer profile. Unlike other systems intended simply for analytics or execution, a CDP is built for converting that data for action across channels so that you do not just sit on insights but can use these insights to shape experiences at the moment.

At its heart, a CDP will ingest first-party data from websites, mobile applications, CRMs, email platforms, support tools, and more. Then it turns that into a single customer view, persistent (evolving over time), and accessible (easy to integrate with your tools). That's it: every click, open, form fill, and session becomes part of an intelligent, unified view to personalize the next touchpoint hold on while it's still relevant.

Distinguishing CDPs from CRMs, DMPs, and Data Lakes

While some data platforms may seem similar, it is often the case that the true function of a CDP is confused with a CRM, DMP, or data lake. Here is an overview:

CRMs exist for relationship management, tracking contacts, deals, and interactions strictly for sales and service use cases. They have no functionality for real-time data ingestion or cross-channel orchestration.
DMPs focus on third-party data, primarily for advertising and audience segmentation. They are cookie-based, using anonymized data, which is not well-suited for long-term customer identity management.
Data Lakes consist of large repositories where raw data sits. These are certainly a great asset for storing and making analytical deductions from, but in reality, they act poorly for any real-time initiation. Extraction-value ISO required technical expertise.

The CDP is different. It reconciles the operational side with the analytical by storing clean, structured, machine-readable, and human-readable profiles in real-time. Notably user-friendly but in all respects built for performance.

Unified Customer Profiles: Identity Resolution & Cross-Device Stitching

One of the most necessary superpowers of a CDP is identity resolution by connecting the dots between the actions of a user across devices, sessions, and even channels. Whether a user is on a mobile browsing site, clicks an email on their desktop, or talks to a chatbot, this is all captured into a single evolving profile.

It’s not just easy for the user, but this is what allows your personalization engine to produce coherent experiences. "Imagine suggesting a product that is abandoned in their mobile cart when a follow-up email is opened on desktop. Also, pausing ads after the transaction is closed. Such orchestration will never be possible unless your platform senses that it is the same person behind all these activities.

Real-Time Personalization: A Brief Overview

Real-time personalization is basically the adjusting of experiences in terms of content, messages, offers, or journeys with regard to the latest behaviors, contexts, or user preferences. For instance, a user watching a series on Netflix can get to see personally curated recommendations right after watching the series. On the B2B front, a company might customize its homepage call-to-action according to the industry or funnel stage of its visitors.

Not just limited to websites, real-time personalization has applications in email, in-app messages, paid media, chat, and even sales outreach. The purpose is, logically place something presented in an intuitive way, not as an intrusion, to reach people literally and contextually where they are.

Why CDPs Are Foundational for Real-Time Personalization

graphic showing the foundational elements of real-time personalization

Real-Time Data Ingestion and Activation: The power of Customer Data Platforms lies mainly in their ability to absorb real-time data and activate it instantaneously. Most of the time, what systems lacking a CDP work on are insights from yesterday. Today, a CDP gives action to a buyer's click, download, or scroll to trigger the next best action, right away. Whether it’s showcasing a new product recommendation, changing a pricing page, or adjusting a lead score in the middle of the session, a CDP helps ensure that your personalization is actually operating in real time. The beauty of this is that it all operates automatically without bottlenecking your team and just works behind the curtains to fuel whatever experience you are putting together.

Enabling Continuous Feedback Loops Between Behavior and Experience Delivery: Not only that, but CDPs are also instrumental in creating these feedback loops whereby user behavior influences not just one turn of response but continues to adjust the experience being delivered forward. For example, as soon as a prospect begins to engage with a new area of solutions, their content journey can dynamically change to reflect this, thereby shifting them onto a new campaign track or exposing them to new sets of testimonials and case studies.

These feedback loops are what make modern and adaptive personalization possible. But they work only if your system listens (for new data) and responds (with tailored experiences)- all in real time. Agility like this simply won't work without a CDP acting as the central nervous system.

Core Capabilities of a CDP That Power Real-Time Personalization

Real-time personalization at scale cannot just be implemented with a CDP; it is about what the platform can do with that data. The best CDPs are not just passive data repositories, but have been built to have active capabilities that convert raw signals instantly into orchestrated intelligent experiences. This section expands on the four critical capabilities any CDP must provide to fully partake in real-time personalization—unified identity, live data activation, predictive segmentation, and omnichannel execution. All help put intent into action, ensuring every user interaction feels personalized, timely, and relevant.

Unified Customer Profile and Identity Resolution

Each customer has a singular, unified profile at the core of the CDP, spanning the anonymous and known behavior of that customer across devices, channels, and sessions. This requires advanced identity resolution that intelligently stitches fragmented data points (like cookies, IDs, CRM records) into a single profile.

This matters when thinking of real-time personalization because otherwise, personalization amounts to random guesswork. If your platform cannot make out that "browsing_user_4231" on mobile is, in fact, the same person who was downloading a whitepaper on desktop, you run the risk of sending messages that are irrelevant, an inability to capitalize on buying signals, or worse, losing customer trust altogether. Identity stitching enables personalization to flow with the user, making each and every interaction designer smarter, more relevant, and timed just right.

Real-Time Data Collection and Event Tracking

Real-time personalization starts with real-time data. CDPs are designed to constantly take in signals from a number of different sources, namely: websites, mobile apps, CRMs, customer-servicing platforms, and offline POS systems, even third-party data sources. These whole stream activities, just like behavioral cues, clicking, scrolling, adding the item to the shopping cart, transactional events such as purchases, renewals, upgrades, and some contextual data such as where the customer is, what device they are using, when in the day, etc.

Event tracking goes off as soon as an action occurs, making the CDP respond instantly. For example, if a user downloads the product comparison sheet, this immediately updates the user's lifecycle and starts an email to him/her. The ability to comprehend and interact with these events in real-time is the reason why a CDP can act differently from older systems based on batch processing, thus making personalization appear more conversational rather than delayed broadcasting.
Segmentation and Audience Activation

A few seconds after data have been gathered and unified, the second stage of audience segmentation comes into play. It's not static audience segmentation. Leading CDPs provide mechanisms for dynamic segmentation, the automatic update of audience segments in response to real-time behavioral and evolving attributes of customers. This means that if a user suddenly changes from casual browser to high-intent buyer, he can be shifted to a new segment in seconds rather than being delayed for days.

An advanced form of CDP incorporates predictive scoring and AI-powered segmentation. Both functionalities rely on historical patterns and an individual's real-time behavior to predict how a customer is likely to react: to churn, convert, or expand. Discerning this predictive intelligence allows marketers to prioritize the right actions, in turn allowing for deepened personalization of the messaging directed at the customer as well as judicious targeting of resources to the appropriate places across the funnel. In this sense, segmentation is less concerned with who somebody was and now, in real time, with whom they are becoming.
Integration with Engagement Channels

The reason real-time personalization is relevant is that it reaches the customer wherever they are. That is why a powerful CDP needs to connect seamlessly with all of your engagement channels, from email platforms to website personalization engines and from online advertising networks to sales enablement tools, such as chat platforms.

Beyond distributing data, this is about establishing two-way flows. These tools should be informed by what the CDP knows and vice versa. Suppose, for instance, a sales rep marks a lead as closed-won in his CRM. That would signal an update to the CDP, which would suppress further nurture emails at that time. A different scenario would arise when a customer clicks on the upsell offer in the email and sends a signal from there to the rest of the channels where that message should reverberate in the next web session. Personalization feels seamless, not disjointed or out of sync, with this level of real-time orchestration.

How Real-Time Personalization Works with a CDP: End-to-End Breakdown

The full lifecycle of real-time personalization based on a CDP is taken apart here-from the first sign of data to the very end of a personalized experience. The aim is to not only explain the steps in a conceptual manner, but to also break them down in such a way that you develop a simple, clear, practical understanding of what is happening behind the curtain. The following five steps explain how a CDP operationalizes data for creating relevant, responsive cross-channel experiences-whether you are building a real-time personalization engine from the ground up or optimizing anything that exists.

How real-time personalization works with CDP - A step by step graphic

Step 1: Data Collection and Event Stream Processing

The journey starts with real-time data ingestion. From the initiation of the ingestion of real-time data, CDPs use tracking scripts (JavaScript for websites), SDKs (for mobile applications), and server APIs in order to stream data at the moment of occurrence. Such data includes behavior signals such as clicks, form submissions, scroll depth, time on page, cart additions, and so on. Everything users do across touchpoints. In order for the data to be useful for personalization, you need a clean event taxonomy — a naming and categorization convention for organizing events in a structured way.

Example, product_viewed with properties like product_id, category, price; form_submitted with form_type, utm_source, etc.

This taxonomy assures that your CDP will understand and standardize what is being tracked so that downstream systems can personalize based on event context. Without real-time actions get messy or inconsistent, and rules for automation break. So if this is an opportunity to design, spend time aligning stakeholders on the event structure—it's foundational.

Step 2: Identity Resolution and Profile Enrichment

Once events are collected, the CDP needs to answer a key question: Who is this? This is where identity resolution comes in. CDPs use a mix of deterministic matching (e.g., email address, login ID) and probabilistic matching (e.g., device fingerprinting, IP + behavior patterns) to stitch anonymous and known behaviors into a single profile. But resolution is just the start. The CDP then enriches profiles by merging in additional data streams:

Clickstream data from web and app behavior
CRM data such as deal stage, account ownership, lifecycle status
Firmographic data like industry, company size, and location
Product usage data (for SaaS), including feature adoption and usage frequency

This multidimensional profile becomes your personalization fuel, ready to be segmented, scored, and activated at any moment.

Step 3: Real-Time Segmentation and Decision

With a unified profile in place, the next step is deciding what action to take—and when. This is powered by real-time segmentation and decision-making logic. CDPs offer both:

Trigger-based logic: “If user visits pricing page AND is not a customer, show a free trial banner”
Continuous recalculation: “If the user’s engagement score drops below 30, move them into the at-risk segment.”

You can also combine static attributes (like company size or role) with behavioral signals to create high-value micro-segments. For example:

“Visited the pricing page 2+ times” + “enterprise company” + “low engagement score”
→ Add to a sales-priority list + trigger a tailored retargeting ad + show new website hero banner.

The goal here is to make decisions in real time that are both context-aware and business-aware, not just fast, but smart.

Step 4: Activation Across Channels

Once the personalization decision is made, the CDP passes it to your execution layer—the tools and platforms where the customer actually experiences the personalization.

This includes:

In-session web personalization (changing banners, content blocks, CTAs)
Email and SMS (dynamic content based on recent actions)
Chatbots (context-aware conversation starters)
Paid media (updating audience lists or creative dynamically)
Sales enablement tools (alerting reps in real-time when leads engage)

Advanced CDPs also power next-best-action models and adaptive journeys. These models calculate what the user is most likely to need next, like a case study, a pricing request, or a call with sales, and serve that asset through the most relevant channel. Execution is where all the intelligence gets real. But it only works if the CDP is deeply and bi-directionally integrated with your channels, so it can both deliver and learn from every customer interaction.

Step 5: Feedback Loop and Optimization

Real-time personalization isn’t a set-it-and-forget-it system—it’s a living cycle that gets smarter with every interaction. That’s why the final (and ongoing) step is optimization through feedback loops. Key components include:

Real-time performance analytics: Which segments are converting? Where are people dropping off? What variant of the message performs best?
A/B testing and experimentation: Run multivariate tests on copy, timing, layout, or offers. Feed those results directly into the CDP.
Model optimization: Feed back interaction data to improve segmentation rules, scoring models, and prediction algorithms.

Your CDP should be able to learn continuously. The more it understands how users respond, the more precisely it can personalize future touchpoints. This is what makes personalization sustainable at scale—not just one-off tactics, but a feedback-driven system that gets more effective over time.

Use Cases of Real-Time Personalization with a CDP

Real-time personalization isn’t a one-size-fits-all strategy—it flexes differently based on your audience, industry, and customer journey complexity. CDPs make it possible to apply personalization in highly contextual ways, whether you're trying to convert an enterprise lead, re-engage a distracted shopper, or orchestrate a seamless omnichannel experience. Below are specific use cases broken down by segment: B2B, B2C, and Omnichannel—each showing how real-time data and smart orchestration can drive measurable outcomes. We’ve also included real-world examples where companies are already putting these strategies into action.

graphic showing the real-time personalizaton use cases with CDPs

B2B Use Cases
1. Website personalization based on firmographics + intent data: The personalization of websites according to firmographics and intent data: When it comes to B2B, personalization is all about relevance, not showcasing sparkling products. These CDPs empower you to customize a visitor's web experience based on their company size, industry, tech stack, and intent signals (such as content consumed, ad campaigns clicked). For instance, an SaaS company can dynamically update its homepage to emphasize enterprise-level solutions for a visitor from a Fortune 500 company. Clearbit and Segment integration allows B2B companies such as Asana to target website headlines and CTAs based on visitor firmographics, displaying enterprise vs. SMB messaging all in real-time.
2. Sales alerts for high-intent actions (e.g., demo page visits): When a prospect looks at pricing or a demo page, it’s often considered a “hot lead.” CDPs can instantly alert the assigned sales rep, or key integrations with Salesforce, Outreach, and HubSpot can trigger a real-time Slack message prompting fast and relevant sales follow-up.
  Example: In the case of Drift, they use CDPs to notify SDRs at the exact time any target account visits any important product page, allowing reps to engage while the interest is sizzling-hot, enormously improving their connect rates.
3. Account-Based Marketing (ABM) personalization for strategic accounts: In ABM, you’re focused on a curated list of accounts. CDPs help deliver account-specific messaging across web, email, and paid channels. You can create hyper-personalized landing pages, show tailored ads on LinkedIn, and coordinate outbound efforts based on where each account is in the buying journey.
  Example: Snowflake uses real-time ABM strategies by leveraging its CDP to personalize site content and ad messaging for decision-makers in target accounts, aligning each touchpoint to the account’s industry and buying stage.
B2C Use Cases
1. Product recommendation engines fed by real-time behavior: CDPs track what users are browsing, favoriting, and purchasing, feeding real-time signals into recommendation algorithms. This means the next time they land on your site (or even refresh the page), the product grid is instantly reshaped to reflect their preferences and browsing history.
  
  Example: Amazon is the classic example, but brands like Sephora use CDP-fueled recommendations based on real-time behavior, purchase patterns, and beauty profile data, creating deeply personal shopping experiences.
2. Cart abandonment triggers across email and SMS: A CDP can detect an abandoned cart in real time and immediately trigger an omnichannel response, starting with an email reminder, followed by an SMS nudge if there’s no engagement. The message can include the exact items left behind, personalized offers, and urgency-based messaging (e.g., “Only 3 left in stock”).
  
  Example: Nike automates cart recovery emails and mobile notifications using real-time behavioral data from its CDP, often with dynamic incentives personalized to the user’s segment or past purchase behavior.
3. Personalized push notifications based on app usage: In mobile-first commerce, CDPs can personalize push notifications based on what a user just did (or didn’t do) in the app. For instance, if someone viewed five items but didn’t purchase, a push notification can highlight one of those products with a limited-time offer within minutes.
  
  Example: Starbucks uses CDP data to send app users hyper-personalized push offers based on purchase history, time of day, and loyalty status—driving return visits and higher spend.
Omnichannel Use Cases
1. Orchestrating consistent experiences across web, mobile, email, and ads: Real-time orchestration means the same user sees consistent, sequential messaging, regardless of the channel they’re on. CDPs sync profiles and preferences across platforms, ensuring messaging doesn't feel fragmented or repetitive. For example, if a user completes a download form on the website, they shouldn’t receive an email asking them to do it again.
  Example: Spotify uses its CDP to unify user data across web, mobile, ads, and email, allowing for seamless campaign storytelling, like reminding users of upcoming concert dates tied to their listening habits across channels.
2. Real-time channel switching (e.g., site visit triggers email follow-up): If someone interacts on one channel and drops off, a CDP can automatically switch the channel, continuing the experience via email, push, or ads. For example, a user viewing a webinar page but not registering might trigger an instant email with the replay link or a reminder.
  Example: Zendesk uses real-time channel switching to nudge buyers toward conversion, serving ads and emails personalized to recent site visits and engagement patterns.

Key Technologies and Integrations That Enable CDP-Based Personalization

A Customer Data Platform doesn’t operate in isolation—it thrives when plugged into the rest of your martech stack. Real-time personalization becomes exponentially more powerful when your CDP acts as the central nervous system, sending signals and orchestrating actions across marketing, sales, and customer experience channels. In this section, we’ll break down how CDPs integrate with core technologies—web personalization engines, email platforms, paid media networks, and CRM/sales tools—to deliver adaptive, context-rich experiences across the funnel. Each integration is both strategic and tactical, enabling brands to respond to behavior as it happens, not after the moment is gone.

graphic showing the CDP Integration for real-time personalization

CDP + Web Personalization Engines

Web personalization engines become exponentially more effective when fueled by CDP segments. Rather than relying on session-only data, CDPs enable dynamic, identity-resolved profiles to power experiences. As a visitor lands on the site, the CDP recognizes them (even if they’re anonymous) and immediately pushes them into a relevant segment—like "enterprise prospect," "loyal returning customer," or "cart abandoned."
Example Use Case: Display a different homepage banner and CTA for:
1. First-time visitors (e.g., “Explore Our Platform”)
2. Existing customers (e.g., “See What’s New”)
3. Target ABM accounts (e.g., “See Why [Company] Chooses Us”)
CDP + Email Marketing Platforms

CDPs allow marketers to build and trigger emails in real time, based on what users are doing right now, not just what they did yesterday. Whether it’s browsing behavior, form abandonment, or product interaction, these signals are used to initiate personalized messages that are relevant and timely. Many email campaigns are built hours (or days) in advance. CDPs can recalculate audiences seconds before a send, ensuring you’re not emailing someone who’s just purchased, unsubscribed, or taken another disqualifying action. This eliminates redundancy and improves deliverability and relevance.
CDP + Paid Media and Retargeting

CDPs help you build highly granular audience segments that feed directly into ad platforms like Google, Meta, LinkedIn, and programmatic DSPs. These aren’t just static lists—they’re continuously updated cohorts reflecting real-time behaviors and profile changes. This precision leads to more efficient spending and higher ad relevance. Equally powerful is suppression. If someone makes a purchase, schedules a demo, or completes an onboarding step, your CDP can immediately remove them from ad audiences so you’re not wasting budget or creating awkward user experiences.
CDP + CRM + Sales Tools

Modern sales teams thrive on data—but only if it’s timely and contextual. CDPs can monitor engagement across channels (website visits, email clicks, ad interactions) and flag “surge signals” in real time. These can be piped into CRMs like Salesforce or sales tools like Outreach to trigger playbooks, alerts, or task assignments. When a rep reaches out, having context like “visited demo page three times this week” or “watched 80% of the onboarding video” enables hyper-relevant messaging. CDPs ensure this insight is surfaced without the rep having to dig through multiple tools.

How to Get Started: Implementing a CDP for Real-Time Personalization

You don’t need a perfect martech stack or an army of engineers to unlock value from real-time personalization. What you do need is a methodical approach: one that balances ambition with execution, and vision with foundational hygiene. This section offers a step-by-step guide to help teams move from interest to implementation. Whether you're just starting with a CDP or trying to optimize its real-time potential, these four pillars will ground your strategy in reality and help you deliver meaningful outcomes from day one.

Graphic showing steps to implement a CDP for real-time personalization

Evaluate Your Tech Stack Readiness

Ask the right diagnostic questions: Before launching into real-time personalization, take inventory of your current capabilities:
1. Is your real-time data capture infrastructure in place?
  Can you ingest behavioral and contextual data in <1 second from web, mobile, and app sources via SDKs, APIs, or tag managers?
2. Is your identity graph reliable?
  A stable and accurate identity resolution system is non-negotiable. You need to confidently stitch together touchpoints across devices, sessions, and systems—whether someone is anonymous, semi-known, or fully known.
Best practice tip: If your identity resolution is still brittle or real-time data capture is limited to surface-level metrics (e.g., page views), prioritize tightening this foundation first. Personalization on shaky data leads to mistrust, both internally and with customers.
Set Clear Personalization Objectives
1. Start with what matters: You don’t need a grand vision to start—you need clarity on what you’re trying to influence. Real-time personalization works best when tied to clear, measurable goals:
  1. Boosting conversion rates on key pages like pricing or product pages
  2. Increasing engagement with product tours or content
  3. Driving retention or upsells through lifecycle nudges
2. Prioritize quick wins to build momentum:
  1. Exit-intent banners based on user segment (e.g., show a demo CTA to mid-funnel leads)
  2. Behavioral email triggers (e.g., send a “you left something behind” email 5 minutes after cart abandonment)
  3. Homepage variations for returning users based on last action
    Quick wins prove ROI, build stakeholder confidence, and lay the groundwork for more complex journeys later.
Build a CDP-Driven Personalization Playbook
1. Operationalize your personalization strategy: Once your foundation is in place, start building a repeatable system, not just campaigns. Your playbook should include:
  1. Use case templates: e.g., “high-value user onboarding,” “retargeting dormant users”
  2. Data flow diagrams: map out how event data moves from source → CDP → activation channel
  3. Segment recipes: codify definitions like “high intent,” “low engagement,” or “at-risk churn”
  4. Governance and QA checklists: include naming conventions, trigger rules, consent checks, and logic validation protocols
This helps new team members onboard faster, ensures consistent execution, and minimizes errors as your personalization efforts scale.
Establish a Continuous Optimization Loop

Don’t just launch, learn, and adapt: True personalization is never static. It evolves as your users, data, and business priorities shift. Embed an always-on feedback loop by:
1. Setting up dashboards that track personalization-specific KPIs (e.g., conversion uplift per segment, time to engagement, cohort-specific bounce rates)
2. Experimenting relentlessly: A/B test personalization logic, creative, and timing. Try suppressing messages in certain journeys. Test nudges at different lifecycle moments.
3. Feeding insights back into the CDP: Whether it’s improved engagement signals, content preferences, or user drop-off patterns, use this data to refine segment definitions, trigger conditions, and next-best actions.

Conclusion

Real-time personalization is no longer a luxury—it’s an expectation. Whether you’re in B2B or B2C, customers today demand experiences that are not only personalized but delivered in the moment, based on their unique behaviors, needs, and intentions. A Customer Data Platform (CDP) is the backbone that makes this level of personalization possible, providing the tools to collect, unify, and activate data across all touchpoints in real time.

As we’ve explored throughout this blog, the journey to leveraging a CDP for real-time personalization requires strategic planning, strong data foundations, and cross-functional alignment. From ensuring your tech stack is ready and setting clear objectives, to building a repeatable playbook and establishing continuous optimization loops, each step is an investment in delivering more meaningful, timely interactions with your customers.

Ultimately, the power of real-time personalization lies in its ability to adapt to and reflect the changing needs of your audience, helping you stay relevant and build deeper, long-lasting relationships. While the challenges can seem daunting, the rewards are immense: increased engagement, higher conversion rates, improved customer loyalty, and a more agile business that can respond to shifts in customer behavior faster than ever before. By following the actionable steps outlined in this blog and focusing on creating a robust, scalable personalization framework, you can transform your customer experiences and unlock the full potential of your CDP.

Remember, personalization is not just about the data—it’s about delivering the right experience, at the right time, in the right way. And with a well-implemented CDP, you have all the tools you need to make that happen.

How to Use CDPs to Power Real-time Personalization

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