The data landscape has evolved in unexpected ways. In April 2025, Google reversed its long-anticipated plan to deprecate third-party cookies in Chrome, and many marketers breathed a sigh of relief. But that relief obscures the accelerated and strategic shift toward first-party data, and the organizations treating Google's reversal as permission to delay are making a costly mistake.
Privacy regulations continue expanding at the state level, with 19 US states now enforcing comprehensive privacy laws. Consumer expectations for transparency keep rising. And perhaps most significantly, AI-powered marketing now demands higher-quality data signals that third-party sources simply can't provide. The marketers gaining ground in 2026 aren't the ones clinging to familiar third-party tactics. They're the ones building first-party data capabilities that will compound in value over time.
This guide breaks down the differences between first-party and third-party data, explains why the distinction matters now more than ever, and provides a practical framework for building a first-party data strategy that positions your marketing for long-term success.
What is first-party data?
First-party data definition
First-party data is information collected directly through their interactions with your brand. When someone makes a purchase on your website, signs up for your email list, engages with your loyalty program, or browses your product catalog, you're collecting first-party data. You own it, you control it, and your customers knowingly provide it through their relationship with you.
This direct collection is what makes first-party data so valuable. There's no intermediary altering or aggregating the information. There's no ambiguity about where it came from or whether the customer consented to its collection. It reflects actual behavior from real customers who have chosen to engage with your brand.
Examples of first-party data sources
First-party data can come from virtually any touchpoint where customers interact with your brand:
Transaction and purchase history including what customers buy, how often, and at what price points
Website and app behavioral data such as pages viewed, products browsed, time spent, and navigation patterns
Email engagement including opens, clicks, and content preferences
Loyalty program activity encompassing points earned, rewards redeemed, and program participation
Customer service interactions from support tickets, chat conversations, and call center records
CRM records containing contact information, communication history, and relationship details
How first-party data is collected
Organizations collect first-party data through their owned channels and direct customer relationships. This includes websites and mobile apps where customers browse, shop, and engage. Point-of-sale systems capture transaction data in physical locations. Customer accounts and profiles store preferences and history. Surveys and preference centers gather explicit feedback and stated preferences. And loyalty programs incentivize ongoing engagement while capturing rich behavioral data.
The common thread across all these sources is the direct relationship. Customers understand they're interacting with your brand, and the data exchange happens within that understood context.
What is third-party data?
Third-party data definition
Third-party data is information aggregated from external sources by companies that don't have a direct relationship with the consumers whose data they're collecting. Data brokers and aggregators compile this information from across the web, package it into segments, and sell or license it to marketers for targeting, enrichment, or audience extension.
Unlike first-party data, which comes from your own customer relationships, third-party data is collected by someone else and made available through syndication on advertising platforms and marketplaces. This means you're often working with data that's been inferred rather than directly observed, aggregated across multiple sources of varying quality, and available to your competitors through the same providers.
Examples of third-party data sources
Third-party data typically originates from:
Data aggregators and brokers who compile information from public records, purchase data, and online behavior
Data management platforms (DMPs) that aggregate audience segments from multiple publishers and data sources
Purchased audience segments offering demographic, interest-based, or intent signals
Demographic and firmographic databases providing information about individuals or businesses
Behavioral data from ad networks tracking activity across websites and apps
How third-party data works
Data aggregators collect information across the web using cookies, device identifiers, and partnerships with publishers and data providers. They then categorize this data into segments based on demographics, interests, behaviors, and inferred intent signals. Marketers license access to these segments for campaign targeting, audience enrichment, or analytics purposes.
The challenge is that third-party data trades precision for reach. Because segments are inferred and modeled rather than directly observed, targeting accuracy suffers. Someone categorized as "interested in travel" based on browsing patterns may have already booked their trip. A "high-income household" segment might include people who simply researched luxury goods for a gift. Third-party data can help you reach broader audiences, but it won't deliver the precision of first-party data built from actual customer behavior and direct relationships.
Understanding second-party and zero-party data
What is second-party data?
Second-party data is essentially another organization's first-party data, accessed through a direct partnership arrangement. A retailer might share purchase data with a consumer packaged goods (CPG) brand. A publisher might share subscriber data with an advertiser. A hotel chain might exchange guest data with an airline partner.
Because second-party data originates from a known source with direct customer relationships, it maintains higher quality than typical third-party data. The partnership structure also provides transparency about where the data came from and how it was collected.
What is zero-party data?
Zero-party data is information that customers intentionally and proactively share with your brand. This includes explicitly stated preferences, purchase intentions, personal context, and communication preferences. When a customer tells you they prefer email over text messages, that they're shopping for a wedding, or that they're interested in sustainable products, they're providing zero-party data.
Zero-party data represents the highest-trust form of customer information because customers consciously choose to share it. This makes it incredibly valuable for personalization, but it also requires creating genuine value exchanges that motivate customers to share.
The complete data classification framework
Think of these data types on a spectrum defined by the directness of the customer relationship:
Zero-party data sits at one end, representing explicit, intentionally shared information with the highest trust and accuracy. First-party data encompasses observed behaviors and interactions within your direct customer relationships. Second-party data extends your reach through trusted partnerships while maintaining data quality. Third-party data sits at the opposite end, offering scale but with significant tradeoffs in accuracy, freshness, and customer trust.
Understanding where your data falls on this spectrum helps you make informed decisions about how to collect, use, and value different data sources in your marketing programs.
First-party vs. third-party data: key differences
Data accuracy and quality
First-party data reflects actual behavior from known customers, and you control the collection methodology. When your website records that a customer viewed a product three times before purchasing, that's a precise behavioral signal you can trust. When your email platform shows that a subscriber consistently opens messages about new arrivals but ignores sale announcements, that preference data is reliable.
Third-party data, by contrast, is often inferred, modeled, or outdated by the time it reaches you. Someone categorized as "in-market for a car" might have already made their purchase. Demographic inferences based on browsing behavior can be wildly inaccurate. And because third-party data is aggregated from multiple sources, quality varies significantly depending on the provider and segment.
Privacy and compliance
First-party data is collected in contexts where customers understand the exchange. They know they're interacting with your brand, and they've typically consented to data collection through your privacy policy and terms of service. This creates clear provenance for regulatory compliance under laws like the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and the growing number of state privacy laws.
Third-party data sourcing can be opaque, making compliance more complex. You may not know exactly how the data was originally collected, whether appropriate consent was obtained, or how the aggregation process handled consumer rights requests. With 19 US states now enforcing comprehensive privacy laws and new CCPA regulations taking effect in January 2026, this uncertainty creates meaningful business risk.
Cost and ownership
Third-party data involves pay-per-use fees for rented access to segments you don't control. Prices can increase, providers can change their offerings, and competitors can access the same data. You're essentially paying for temporary access to someone else's asset.
First-party data requires upfront investment in collection infrastructure, data management, and activation capabilities. But once you've built these capabilities, the data becomes an owned asset that appreciates over time. Every customer interaction adds to your data foundation. Every improvement in data quality compounds in value. And unlike licensed third-party data, your first-party data is exclusively yours.
Customer relationships
First-party data deepens direct relationships with customers. The insights you gather help you serve customers better, which encourages more engagement, which generates more data, which enables even better service. This virtuous cycle strengthens customer loyalty and lifetime value.
Third-party data can extend your reach to new audiences, but it doesn't strengthen your brand connection. You're essentially renting access to someone else's customer relationships rather than building your own.
Why first-party data still matters in 2026
The cookie landscape has shifted, but not simplified
Google's April 2025 decision to keep third-party cookies in Chrome surprised many marketers who had spent years preparing for deprecation. But focusing on Google's reversal misses the broader picture.
Safari and Firefox have blocked third-party cookies by default for years. According to EMARKETER analyst Evelyn Mitchell-Wolf, over a third (34.9%) of US browsers already block third-party cookies by default between Safari and Firefox alone. Brave and other privacy-focused browsers have similar restrictions. The underlying reliability of third-party cookie-based tracking has been degrading steadily through ad blockers, consent banners, and various tracking prevention mechanisms.
Even in Chrome, where cookies remain available, the ecosystem has fundamentally changed. Marketers who built their strategies around third-party cookies have experienced years of declining match rates, shrinking audiences, and increasing measurement gaps. Google's reversal doesn't undo that erosion; it simply means the decline will continue gradually rather than ending abruptly.
Privacy regulations continue expanding
The regulatory environment has grown significantly more complex in 2026. Three new state privacy laws took effect on January 1, 2026, with Indiana, Kentucky, and Rhode Island joining the 19 states with comprehensive privacy legislation.
California's CCPA regulations expanded significantly in January 2026, introducing new requirements for automated decision-making technology, mandatory risk assessments, and enhanced cybersecurity measures. The California Delete Act requires data brokers to honor consumer deletion requests through the state's Data Broker Registry (DROP) system starting in August 2026.
Universal opt-out mechanism requirements are expanding across states, with Connecticut and Oregon joining California, Colorado, Delaware, Maryland, Minnesota, Montana, New Jersey, New Hampshire, and Texas in requiring businesses to honor browser-based privacy signals. This patchwork of state regulations creates compliance complexity that will only increase as more states enact similar laws.
First-party data is now essential fuel for AI
Perhaps the most significant shift in 2026 is the recognition that first-party data isn't just about privacy compliance; it's about AI readiness. As AI-powered marketing tools become central to campaign optimization, audience targeting, and personalization, the quality of your data inputs directly determines the quality of your outputs.
First-party data provides the rich, accurate signals that AI models need to deliver meaningful results. Purchase history, browsing behavior, engagement patterns, and stated preferences all feed AI systems that can predict customer needs, optimize messaging, and personalize experiences at scale.
Third-party data, with its inherent latency and accuracy issues, produces less reliable AI outputs. This is why brands are increasingly investing in owning their data infrastructure rather than depending on external sources. As Gartner analyst Andrew Frank noted, the hype around AI and large language models has driven companies to think more carefully about control and ownership of their data. First-party data has become the strategic asset that powers competitive advantage in an AI-driven marketing landscape.
How to build a first-party data strategy
Audit your current data collection
Start by taking inventory of the first-party data you already collect across the organization. Map out every touchpoint where customers interact with your brand and identify what data is captured at each stage. This includes obvious sources like your ecommerce platform and email system, but also less visible sources like customer service tools, in-store systems, and partner integrations.
Assess the quality and accessibility of this data. Is it accurate and up-to-date? Can you access it for marketing purposes, or is it locked in operational systems? Are there gaps between what you collect and what you need to support your marketing goals?
Implement data collection touchpoints
With a clear picture of your current state, identify opportunities to capture more valuable first-party data. Optimize your owned properties for data capture by implementing progressive profiling, preference centers, and value-driven registration flows. Create genuine value exchanges that motivate customers to share information, whether through loyalty programs, personalized recommendations, or exclusive content.
Focus on collecting data that will actually improve customer experiences. Customers are increasingly savvy about data collection, and they expect to see tangible benefits from sharing their information. The organizations that succeed are those that use data to serve customers better, not just to target them more aggressively.
Unify data with a customer data platform
Collecting first-party data across multiple touchpoints creates a new challenge: fragmentation. The same customer might appear as separate records in your ecommerce platform, email system, loyalty program, and customer service tools. Without a way to connect these fragments, you can't build a complete picture of who your customers are and how they engage with your brand.
Customer data platforms (CDPs) solve this problem by ingesting data from all sources and using identity resolution to create unified customer profiles. These platforms connect the dots across touchpoints, resolve duplicate records, and maintain a persistent view of each customer that updates as new data arrives.
Create a data governance framework
As your first-party data capabilities mature, governance becomes essential. Establish clear ownership for data quality, define standards for collection and usage, and implement access controls that protect customer privacy while enabling legitimate marketing use cases.
Build consent management into your collection processes from the start. Document data lineage so you can trace information back to its source. Create retention policies that balance marketing needs with privacy requirements. Strong governance isn't just about compliance; it builds customer trust and ensures your data remains an asset rather than a liability.
Activate data across marketing channels
First-party data only creates value when you can act on it. Build connections between your unified customer profiles and the platforms where you execute marketing campaigns. This includes paid media platforms, email and messaging tools, personalization engines, and analytics systems.
The goal is to close the loop between data collection, insight generation, and campaign execution. When you can see how customers respond to campaigns and feed that data back into your customer profiles, you create a continuous improvement cycle that makes your marketing more effective over time.
Common first-party data challenges (and solutions)
Data silos across systems
Most organizations have customer data scattered across dozens of disconnected systems. Marketing has email engagement data. Sales has CRM records. Ecommerce has transaction history. Customer service has support interactions. Each system holds a piece of the puzzle, but no single view of the customer exists.
The solution is unified data infrastructure that can ingest data from any source without requiring rigid schemas or complex integrations. Modern CDPs are designed for exactly this purpose, providing flexible connectors and transformation capabilities that bring fragmented data together.
Identity resolution issues
Even when you consolidate data into a single platform, you face the challenge of recognizing the same customer across different records. A customer might use one email address for purchases and another for loyalty program registration. They might browse on mobile but buy on desktop. Without sophisticated identity resolution, these appear as separate customers.
AI-powered identity resolution connects fragmented profiles by analyzing patterns across identifiers, behaviors, and attributes. This creates a complete view of each customer that reflects their full relationship with your brand, not just isolated interactions.
Maintaining data quality
Data quality degrades over time. Customers move, change email addresses, and update their preferences. Records accumulate duplicates. Information that was accurate at collection becomes stale. Without ongoing attention to data hygiene, the value of your first-party data erodes.
The solution is continuous validation and cleansing processes that identify and resolve quality issues as they emerge. This includes deduplication, address standardization, email verification, and regular audits of data accuracy.
Scaling personalization
Having unified, high-quality first-party data doesn't automatically mean you can use it effectively. Many organizations struggle to translate customer insights into personalized experiences at scale. The data exists, but the activation capabilities don't.
Integrated platforms that connect data management with campaign execution bridge this gap. When insights and activation live in the same ecosystem, marketers can move from segment creation to campaign deployment without manual data transfers or complex integrations.
The role of CDPs in first-party data management
How enterprise CDPs unify customer data
Enterprise CDPs are purpose-built to solve the first-party data challenge at scale. They ingest data from any source, including transactional systems, behavioral tracking, third-party enrichment, and offline interactions, without requiring data to conform to rigid predefined schemas.
This flexibility is crucial for large organizations with complex technology ecosystems. Rather than forcing data transformations before ingestion, modern CDPs handle the complexity of normalizing and connecting disparate data sources within the platform.
AI-powered identity resolution and insights
Identity resolution is the core capability that transforms fragmented data into unified customer profiles. Enterprise CDPs use both deterministic matching, connecting records that share exact identifiers like email addresses, and probabilistic matching, using AI to identify likely connections based on behavioral and contextual signals.
Beyond basic profile unification, AI capabilities can enrich profiles with derived attributes and predictive scores. These might include likelihood to purchase, churn risk, channel preferences, or lifetime value predictions. Such insights help marketers prioritize their efforts and personalize their approaches.
From data collection to activation
The ultimate measure of a CDP's value is whether it enables better marketing outcomes. This requires seamless connections to the platforms where campaigns are executed, including demand-side platforms for paid media, email service providers, personalization engines, and customer service tools.
Leading CDPs provide pre-built integrations and flexible APIs that keep customer profiles synchronized across the marketing technology stack. When a customer's profile updates in the CDP, that change flows automatically to every connected system, ensuring consistent, current data powers every customer interaction.
Future-proofing your marketing with first-party data
The shift toward first-party data isn't a temporary response to cookie deprecation or privacy regulation. It represents a fundamental change in how successful brands build customer relationships.
Organizations investing in first-party data capabilities today are building durable competitive advantages. They're creating the foundation for AI-powered marketing that actually works. They're developing customer relationships based on trust and value exchange rather than surveillance. And they're positioning themselves to adapt as the regulatory and technological landscape continues evolving.
The value of first-party data extends beyond traditional marketing applications. Unified customer profiles improve service experiences across channels. Behavioral insights inform product development decisions. And increasingly, strong first-party data assets enable new forms of partnership and collaboration, from retail media participation to data clean room partnerships, that create value for customers and brands alike.
The organizations that thrive in this environment won't be those with the largest third-party data budgets. They'll be those who build direct customer relationships, collect valuable first-party data through genuine value exchanges, and activate that data to deliver experiences customers actually want.
Ready to unlock the full potential of your first-party data? Request a demo to see how Amperity helps leading brands unify their customer data and turn insights into action.
Frequently asked questions
What is the difference between first-party and third-party data?
First-party data is collected directly from your customers through your owned touchpoints like websites, apps, and transactions. Third-party data is aggregated by external companies from sources across the web and sold to marketers for targeting and enrichment. First-party data offers higher accuracy and clearer compliance, while third-party data provides broader reach but with significant quality tradeoffs.
Why is first-party data still important now that Google kept cookies?
Even with cookies available in Chrome, Safari and Firefox block third-party tracking by default, affecting roughly 35% of US browser traffic. Privacy regulations continue expanding, with 19 US states now enforcing comprehensive privacy laws. First-party data remains the most accurate, compliant, and sustainable foundation for marketing, especially as AI-powered tools require higher-quality inputs.
What are examples of first-party data?
Common examples include purchase history, website browsing behavior, email engagement metrics, loyalty program activity, customer service interactions, app usage data, and information customers share through preference centers or account profiles. Any data collected directly through your customer relationships qualifies as first-party data.
How do you collect first-party data?
First-party data is collected through owned channels including websites, mobile apps, point-of-sale systems, CRM platforms, email marketing programs, loyalty programs, customer surveys, and any direct interaction where customers engage with your brand. The key is creating value exchanges that motivate customers to share information willingly.
Is first-party data better than third-party data?
First-party data is generally more accurate, compliant, and valuable for personalization because it comes directly from customer interactions you control. Third-party data can still be useful for prospecting and reach extension in some contexts, but its reliability and availability continue declining as privacy restrictions expand and tracking mechanisms degrade.
What is a customer data platform (CDP)?
A customer data platform is software that unifies customer data from multiple sources into persistent, individual profiles. CDPs help marketers resolve customer identities across touchpoints, maintain data quality at scale, and activate unified profiles across marketing channels. They serve as the foundation for first-party data strategies in enterprise organizations.
What is zero-party data?
Zero-party data is information customers intentionally and proactively share with your brand, such as preferences, purchase intentions, and communication choices. Unlike first-party data gathered through observed behavior, zero-party data comes from direct customer input through surveys, preference centers, or account profiles. It represents the highest-trust form of customer data because customers consciously choose to provide it.