Editorial
The Gist:
-
Personalization and data. Businesses need a strong customer data strategy to deliver the personalized experiences customers demand.
-
CDP adoption growing. The rise of customer data platforms helps businesses collect and unify customer data, making it easier to analyze and use across touchpoints.
-
Real-time insights. Real-time data analysis is becoming mainstream in 2025. It allows businesses to react faster to customer behavior changes and improve decision-making.
Experience is at the heart of modern business success. Sixty-four percent of customers prefer to buy from brands that personalize according to their wants and needs. The experience your brand delivers defines how it is perceived by customers and whether it can continue to thrive in the modern-day, competitive business environment.
Data is central to personalized experiences. Your brand cannot deliver the experience your customers have grown to expect from you unless you have their data. Collecting, analyzing and extracting meaningful insights from data requires planning. That’s why businesses that want to use customer data effectively need a well-planned, proactive data strategy
2025 is expected to be a year of big technological advances. With CDPs increasing in popularity and AI and ML capabilities gaining power, CX leaders can look toward many trends that have the potential to change how they build and execute their customer data strategy.
Table of Contents
- Every Customer Data Strategy Needs a Solid Foundation
- Customer Data Strategy Trends to Watch in 2025
- Staying Ahead in a Shifting Data Landscape
Every Customer Data Strategy Needs a Solid Foundation
Your customer data strategy is your action plan. It defines all the details about how your business will collect, process, analyze and use customer data. A holistic strategy helps you gather customer data and build a complete profile. You can then use that profile to design more relevant experiences.
Proactively building a customer data strategy allows you to stay ahead of the curve. It lets you uncover the latest trends that are yet to hit the market. When you know what’s coming in the world of data, tech and customer experience, you can proactively adjust your strategy accordingly.
Customer Data Strategy Trends to Watch in 2025
2023 brought news of the depreciating use of third-party cookies, and with that came a rise in popularity for zero and first-party data collection.
In 2024, we saw AI, particularly generative AI, taking more of a central role and becoming a household name.
Now, 2025 is expected to be a year of significant technological development. Economies across the globe are finally recovering, humanity is getting closer to seeing quantum computing become a reality, and concerns around data privacy are at an all-time high. In this world, we might see forward-thinking businesses adapt their customer data strategies to account for these changes.
Here are key customer data strategy trends that may define how customer data is collected and managed this year.
Data Democratization
Seventy-three percent of organizations consider data democratization and self-service functionality important. Data democratization is the process of making data accessible to more people within an organization or society. When accomplished in a company, democratization helps break down the walls between departments. It allows data to move freely and lets more employees access those insights, even if they don’t have a skill set to extract meaningful information from the data.
Data democratization does not only make data more accessible. It aims to make it more understandable and actionable, as well. With the ever-increasing demand for data across all departments, more companies may begin using data democratization in 2025. This gives employees what they need to make smarter decisions on their own.
API-first architectures and generative AI may lead this wave of data democratization. Businesses may start investing in tools that make insights easy for anyone to understand and act on. Companies that make data literacy a priority and give employees better access to information will be in a stronger position than those that don't.
Increasing Importance of Zero and First-Party Data for Personalization
The need for personalization will never wane. If anything, it will only increase further. However, the way businesses collect and use data for personalization has changed, and it will continue to evolve through 2025. AI in personalization leads to concerns around privacy.
Businesses now need to get creative and strike a balance between privacy and personalization. Using zero and first-party data is one way to do that. This approach isn’t new; businesses have been using it for a while now.
However, a recent change in the digital landscape could push businesses to rely even more on this data collection strategy. This year, Google announced a new experience for users which will allow them to choose whether they want to allow third-party cookies or not. With Chrome representing almost half of all web browser usage worldwide, the new experience may prompt more businesses to incorporate zero and first-party data collection in their customer data strategies.
Proactively deploying systems for zero and first-party data collection will allow businesses to blunt the impact of depreciating third-party cookies. To be successful, blending transparency and a clear value proposition within the customer data strategy will be critical.
As businesses collect zero and first-party data, they will have to be explicit about how they are going to use this data. They will also need to clearly explain what customers receive in return for the data they share or allow the brand to collect.
The Rise of CDPs
Customer data platform (CDP) adoption will continue to increase through 2025.
There are many touchpoints where customers interact with a brand. Manually collecting data across all touchpoints and using it to get a holistic understanding of customer behavior is simply impossible. CDPs make it possible and easier by collecting data across all customer touchpoints and aggregating it to present a single, unified customer profile.
CDPs are becoming more common. Fueled by the increasing complexity of customer data sources, the demand for CDPs will increase, which will result in the increased adoption of CDPs across more businesses. We may also see CDPs integrate AI to deliver enhanced value and potentially help businesses with their data democratization efforts.
Customer Data Platform Capabilities, Use Cases and Market Outlook
Editor's note: According to the 2025 CMSWire CDP Market Guide, Customer Data Platforms are evolving into enterprise-critical tools that unify fragmented data, enable personalized experiences and power real-time decision-making. This table highlights the core functions, strategic use cases, and projected market growth for CDPs.
| Category | Detail | Why It Matters |
|---|---|---|
| Core Capabilities | Data Capture | Collects first-party data from digital and offline channels in real time or batch mode. |
| Data Management | Unifies and cleanses data to create a central customer profile with identity resolution. | |
| Data Analytics | Uses AI and ML to segment customers, forecast behaviors and personalize experiences. | |
| Data Activation | Pushes real-time customer profiles to marketing platforms for omnichannel engagement. | |
| Top Use Cases | Single Source of Customer Truth | Eliminates data silos and ensures all teams work from unified customer profiles. |
| Identity Resolution | Combines fragmented data to provide consistent experiences across sessions and devices. | |
| Campaign Connection | Delivers personalized content and offers in real time across email, web and mobile. | |
| Privacy Compliance | Simplifies management of consent preferences and supports GDPR/CCPA compliance. | |
| Advanced Analytics | Identifies patterns, predicts churn or conversion, and suggests next-best actions. | |
| Marketing Automation | Enables intelligent workflows, lead scoring and cross-channel engagement strategies. | |
| Market Outlook | Global Market Size | Expected to grow from $2.95B in 2024 to $10.12B in 2029, driven by demand for real-time personalization and healthcare use cases. |
| Key Growth Driver | Real-time, omnichannel personalization and increased enterprise adoption of customer data platforms. |
Real-time Data Analysis
Also known as data streaming, real-time data analysis is a topic that has been a part of the conversation in the data world for quite a while now. Still, because of the need for high computing power, data streaming has been restricted to niche companies and resourceful businesses. Today, only a fraction of all the available data is processed in real-time. Most businesses rely on batch processing for insights.
2025 may be the year we see real-time data analysis becoming more mainstream. Real-time data analysis helps businesses use predictive analytics to address issues before they become a problem. Using real-time data, businesses can react quickly to changes in customer behavior and adjust their marketing strategies to enhance their experience.
New technologies and software architectures like Kappa and Lambda are now helping make real-time data analysis a possibility for more businesses.
New technologies and software architectures like Kappa and Lambda are now helping make real-time data analysis a possibility for more businesses.
Webinar
Sep
25
CMS Briefing: A Live Look at What’s Next in AI-Driven Platforms
Learn how leading organizations are using AI‑driven tools to publish faster, personalize smarter and stay secure.
Register
Webinar
Sep
25
Call Spoofing Trends Financial Institutions Can't Afford to Ignore
Don't let robocalls sabotage your customer relationships. Learn how to secure your voice channel.
Register
Webinar
On demand
Ready or Not: How Data-First Organizations Are Unlocking Agentforce Potential
Learn how to cut through the noise, activate Agentforce and build a Salesforce AI strategy that actually delivers.
Watch Now
Webinar
On demand
CX Reality Check: What Your Customers Are Really Thinking
Register now and get the insights you need to not just meet rising expectations, but exceed them.
Watch Now
Webinar
On demand
Content Leaders Collective: What a Good CCMS Actually Looks Like
Discover how content leaders transform clunky systems into growth engines — and why your competitors are ahead.
Watch Now
Webinar
On demand
From Hype to High-Impact CX Strategies That Actually Scale
Turn buzzworthy AI and outsourcing trends into measurable CX wins with fresh 2025 data.
Watch Now
Besides the mainstream availability of the required architecture, the widespread adoption of real-time analysis may be driven by the promising ROI associated with data streaming.
“2025 will become the tipping point when data streaming transitions from a leading-edge technology to a widely adopted driver of growth and competitive differentiation,” said Richard Timperlake, senior vice president of data streaming platform Confluent.
Enhancement of Data Security and Privacy Best Practices
Global data creation is projected to grow to more than 394 zettabytes. With increased volume of data comes more responsibility and heightened concerns around the security of this data. Enforcement of new privacy laws and fears of data breaches are at an all-time high, and this may drive businesses to rethink legacy data security and privacy approaches. With a business’s data security best practices being tied to its reputation, we may see more businesses taking data security seriously and also informing their customers of their commitment to respecting their privacy.
With the ubiquity of generative AI, we may see increased concerns around shadow AI and the unsanctioned use of AI by employees, without approval from IT. This year, businesses may start including shadow AI oversight as part of their data privacy and security best practices.
Use of AI and ML for Data Processing
AI is helping advanced analytics tools become more accessible. What once felt out of reach is now becoming part of the mainstream. This includes, for example, enhanced data democratization and real-time data analysis.
While AI and ML are already playing vital roles in many data processing operations, we may see them taking more of a central role in customer data management. Extracting meaningful insights from vast volumes of data in a timely manner has always been a challenge. New AI and ML technologies may allow CX leaders to redefine their customer data strategies and adopt better ways to gather and apply customer data to improve the overall experience.
With increasing expectations for delivering hyper personalization at scale, new AI technologies may just be the solution for CX leaders and marketing professionals.
Agentic AI
Agentic AI refers to systems that can analyze data, extract meaningful insights and take appropriate, autonomous actions. AI agents can work alongside humans to shoulder some of their responsibilities and automate repetitive, time-consuming processes. Organizations that adopt AI agents have reported up to 98% reduction in operational costs for AI-driven processes.
Customer experience offers scope for agentic AI, and CX leaders who embrace it may see better efficiency and smarter automation.
Related Article: Your Dashboard Is Outdated: Welcome to the Agentic AI Era
Key Capabilities for Customer Data Leaders in 2025
This table summarizes all the essential capabilities and trends customer data leaders must understand to build a modern, effective customer data strategy that enables personalization, real-time insights and secure data governance.
| Capability | Description | Strategic Value |
|---|---|---|
| Data Democratization | Making data and insights available to non-technical users across the organization. | Drives cross-functional collaboration, smarter decisions, and faster insight-to-action. |
| Zero and First-Party Data | Data collected directly from customer interactions and volunteered information. | Enables compliant personalization and reduces reliance on third-party cookies. |
| Customer Data Platforms (CDPs) | Technology platforms that unify data from multiple touchpoints into a single profile. | Drives real-time personalization and campaign orchestration across channels. |
| Real-Time Data Analysis | Streaming architectures like Kappa/Lambda enable predictive insights as events happen. | Boosts agility and responsiveness, improving retention and conversion rates. |
| Data Security & Privacy Governance | Policies and controls to manage risk, consent, and regulatory compliance. | Builds customer trust and prepares the organization for evolving legal requirements. |
| AI & ML Integration | Use of artificial intelligence to derive insights, automate decisions, and forecast behavior. | Increases personalization at scale and empowers smarter marketing and service delivery. |
| Agentic AI | AI agents that act autonomously on insights and work alongside humans. | Reduces operational costs and improves efficiency in customer operations. |
Staying Ahead in a Shifting Data Landscape
We are now on the brink of a new era of data analytics. As advanced technologies become mainstream, 2025 could mark a turning point in how CX leaders collect, manage and use customer data.
This year, AI may take more of a central role in the world of data analytics. We may see real-time data analytics and more widespread data democratization rising as defining trends that set the tone for how we work with data for the next decade. Besides that, zero and first-party data collection may continue to rise in popularity, as businesses react to strict data privacy laws.
Forward-thinking CX leaders can explore self-service analytics, focus on collecting zero and first-party data and guarantee complete privacy and transparency. They should also consider incorporating data streaming tools to their 2025 plans. This may help them stay ahead of the curve in the new era of customer data analytics.
Learn how you can join our contributor community.
