Identity Graphs and Third-Party Cookie Restrictions

Third-party cookies are disappearing, and digital marketing is transforming. Browsers like Chrome will block these cookies by late 2024, and privacy laws like CCPA demand explicit consent for data tracking. This creates challenges for marketers, including fragmented data, less accurate targeting, and compliance hurdles.

Identity graphs are the solution. They build unified customer profiles by connecting data points like email addresses, device IDs, and purchase history. Unlike cookies, identity graphs work across devices and channels, offering privacy-compliant tracking, personalization, and real-time insights.

Here’s why identity graphs matter:

• Better tracking: Connect interactions across devices and platforms.
• Improved personalization: Tailor campaigns using complete customer profiles.
• Privacy compliance: Use hashed data and first-party information to meet legal standards.

As third-party cookies phase out, marketers must shift to identity-based strategies to stay effective. Tools like Reform can simplify first-party data collection while ensuring compliance, helping businesses thrive in this new era.

Identity Graphs Can Fill The Hole In Marketers' 'Sweet Tooth': TransUnion's Kowalick

Problems with Third-Party Cookie Restrictions

The phase-out of third-party cookies is shaking up the digital advertising landscape, forcing marketers to overhaul how they target audiences and measure campaign success. The ripple effects are most evident in tracking challenges and the fragmentation of data.

User Tracking Issues and Data Fragmentation

One of the biggest hurdles is the collapse of cross-device tracking. Previously, marketers could follow users across roughly 70% of the open web. That number is expected to plummet to below 40% as major browsers finalize their third-party cookie restrictions.

This drop leads to what experts call data fragmentation - a scenario where customer interactions are scattered across multiple platforms and devices without a reliable way to piece them together. For instance, a single user visiting on a smartphone and later on a laptop might now appear as two entirely separate individuals.

The issue doesn’t stop at devices. Marketing channels - like email campaigns, social media ads, search engines, and direct website visits - are becoming siloed. Without a unified view, teams lose sight of how these channels interact to drive conversions. This makes it nearly impossible to pinpoint which touchpoints are most effective, leaving brands struggling to understand customer journeys. As a result, lead generation efforts risk losing continuity, forcing companies to start from scratch when trying to build relationships.

Less Accurate Audience Targeting and Attribution

The loss of third-party cookies has also made audience targeting less precise. Without access to behavioral data across websites and devices, segmentation becomes a guessing game. According to Forrester Consulting, advertisers now waste $0.21 of every dollar spent on ads due to poor data quality - a problem that has worsened with these restrictions.

Attribution models are also taking a hit. Marketing teams can no longer reliably connect ad impressions to conversions when those actions occur on different platforms or devices. This creates a domino effect: if you can’t measure what’s working, you can’t optimize your campaigns. Budget allocation becomes more about intuition than data-driven insights.

The challenges are particularly evident in retargeting campaigns. Previously, marketers could target users who browsed specific product pages or abandoned shopping carts. Now, those audiences are shrinking and less reliable, leading to weaker campaign performance and higher customer acquisition costs.

Personalization efforts are also suffering. eMarketer’s 2023 research found that over 80% of U.S. marketers believe the loss of third-party cookies will significantly impact their digital advertising strategies. As a result, tailored experiences are being replaced by generic messaging, which risks lowering engagement and conversion rates across all channels.

Compliance and Privacy Requirements

The shift away from third-party cookies aligns with broader privacy-focused trends, driven by both regulatory changes and evolving consumer expectations. Laws like the California Consumer Privacy Act (CCPA) have set the stage, with other states, such as Virginia, introducing their own comprehensive data protection regulations.

These laws require explicit consent for data collection and give consumers the right to know how their information is being used. This means marketers can no longer rely on passive tracking methods. Instead, they need to adopt transparent, consent-based strategies that hand control back to users.

Consumer attitudes toward privacy have also shifted dramatically. People are more aware of how their data is collected and used, and they’re demanding greater control. Even tracking methods that technically comply with regulations may face pushback if they don’t meet user expectations for transparency and respect.

The compliance challenges don’t end there. Marketing teams must now embrace privacy by design, ensuring that data collection practices are secure, transparent, and aligned with user preferences from the start. This often requires new tools, workflows, and a fresh approach to managing customer data.

For businesses operating across multiple states, the patchwork of privacy laws adds another layer of complexity. What’s compliant in one state may fall short in another, forcing companies to either adopt the strictest standards or create intricate, location-specific compliance systems. This adds significant operational and legal challenges to an already shifting landscape.

What Are Identity Graphs and How They Help

As third-party cookies fade away and customer data becomes increasingly fragmented, identity graphs step in to piece everything together. Think of them as a master address book that organizes all the ways a customer interacts with your brand into one clear, unified profile.

Identity Graphs Explained

An identity graph is essentially a database that connects consumer data from multiple sources - like devices, platforms, and touchpoints - into a single, cohesive profile for each person or household. Unlike third-party cookies, which track users anonymously, identity graphs use a variety of identifiers, such as email addresses, phone numbers, device IDs, and even offline data, to recognize an individual no matter how they interact with your brand.

These identifiers create what’s often called a "golden record", a unified profile that captures all interactions and attributes linked to a person. The process, known as identity resolution, pulls information from CRM systems, platforms, and partner feeds, matching and merging data in real time. This enables immediate personalization.

For example, let’s say a customer browses your website on their smartphone, checks an email on their laptop, and later makes a purchase on their tablet. An identity graph connects all these actions to one profile, rather than treating them as separate users.

Industry data confirms that identity graphs can offer high levels of accuracy across devices and channels, even at scale. For instance, a furniture retailer successfully combined website visits, email activity, and in-store purchases into a single view. This allowed them to personalize their communications, ultimately boosting their ROI. Beyond personalization, this unified approach also strengthens privacy measures.

Privacy and Compliance Advantages

Identity graphs not only unify fragmented data but also address modern privacy and compliance concerns. Unlike third-party cookies, which often operate without clear user consent, identity graphs rely on privacy-compliant methods and transparent practices. They primarily use first-party data - information customers willingly share through actions like logging into accounts, filling out forms, or subscribing to newsletters.

To protect sensitive information, identity graphs use techniques like hashing and tokenization, which limit exposure to personally identifiable information (PII). This privacy-first design ensures compliance with regulations like the California Consumer Privacy Act (CCPA) and fosters trust by clearly showing users how their data is collected and used.

By centralizing data management into one auditable system, businesses can also reduce compliance risks and simplify the complex task of managing cookies across various platforms. This "privacy by design" approach builds robust protections into the system from the start, making it easier to adapt as privacy laws evolve.

Platforms like Reform complement identity graphs by supporting privacy-first lead generation, helping businesses create a comprehensive and compliant customer engagement strategy.

sbb-itb-5f36581

How Identity Graphs Help Marketers

Identity graphs are changing the way marketers understand and connect with customers, addressing the limitations of third-party cookies. Instead of relying on fragmented data and guesswork, these tools provide a clear, unified view of each customer's journey across all their interactions.

Better Cross-Device and Cross-Channel Tracking

Identity graphs bring together data from various devices and platforms - like email addresses, device IDs, and purchase histories - into a single, cohesive profile. This integration allows marketers to track an individual's activity across websites, apps, in-store systems, and even call centers, regardless of device switches. For instance, imagine a customer browsing products on their phone during lunch, reading reviews on a laptop at home, and completing the purchase on a tablet while watching TV. Without an identity graph, these actions might appear as separate users. With one, they’re recognized as a single journey, enabling consistent communication and more accurate attribution.

This level of tracking not only improves accuracy but also reduces wasted ad spend. Marketers can better measure campaigns, avoid targeting current customers with acquisition-focused ads, and allocate budgets more effectively. Additionally, when a new browser cookie is detected, it can instantly link to an existing customer profile, triggering personalized content or loyalty rewards in real time. This unified approach opens up opportunities for deeper personalization and sharper insights into customer behavior.

Better Personalization and Customer Insights

By consolidating scattered data, identity graphs provide a full picture of customer behavior. This clarity allows marketers to create audience segments based on actual habits rather than isolated data points. With this complete view, brands can craft personalized experiences that drive conversions. For example, if a shopper abandons their cart on a mobile device but frequently checks emails on their desktop, a targeted email featuring the abandoned items could nudge them toward completing the purchase.

Identity graphs also allow marketers to build look-alike audiences, sequence their messaging, and fine-tune ad frequency. Instead of overwhelming users with the same ad across multiple platforms, marketers can design coordinated campaigns that tell a cohesive story, delivering the right message at the right time.

Identity Graphs vs. Third-Party Cookies Comparison

The advantages of identity graphs become even clearer when compared to traditional third-party cookies:

This comparison highlights why identity graphs are a step ahead. As privacy laws tighten and third-party cookies become less effective, identity graphs offer a reliable, regulation-friendly alternative. They provide persistent profiles and precise identity resolution, ensuring marketing efforts remain impactful while adapting to the evolving landscape. With this approach, brands can future-proof their strategies and maintain meaningful connections with their audiences.

How to Use Identity Graphs in Marketing

Shifting from understanding identity graphs to putting them into practice requires a well-thought-out approach that emphasizes both data quality and privacy compliance. The foundation lies in building a reliable pool of first-party data while ensuring every action aligns with U.S. privacy laws.

Data Collection and Authentication Methods

To create an effective identity graph, start with high-quality first-party data sourced from your CRM, CDP, and website forms. Gather deterministic identifiers like email addresses and device IDs through secure, authenticated channels.

Enhance accuracy by implementing multi-factor authentication and real-time email validation. Make sure to obtain explicit user consent and regularly review your authentication protocols to maintain data integrity.

If you’re using data enrichment tools to expand customer profiles, ensure that all processes comply with U.S. privacy regulations. It’s a delicate balance - completing customer profiles while safeguarding sensitive information. By focusing on secure practices, you can build a data foundation that supports real-time analytics and responsive marketing strategies.

Real-Time Analytics and Campaign Optimization

Real-time data recognition across channels opens the door to dynamic segmentation and timely, personalized messaging.

For example, real-time insights can help exclude existing customers from acquisition campaigns, allowing you to reallocate resources to retention or upselling efforts. This kind of responsive campaign management not only improves cost efficiency but also enhances attribution accuracy and budget allocation.

These insights also enable synchronized, cross-channel messaging. Imagine a customer abandons their cart on mobile but frequently checks their email on a desktop. A well-timed email prompt could recover the sale, creating a seamless and cohesive brand experience.

Once real-time insights are in place, the next step is incorporating tools like Reform to collect leads while prioritizing privacy.

Using Reform for Privacy-First Lead Collection

Reform’s form builder integrates seamlessly with identity graphs, offering a way to collect high-quality, validated data. Its lead enrichment capabilities gather additional customer details without requiring users to fill out long, cumbersome forms - reducing friction while building robust profiles.

As users fill out forms, Reform validates email addresses in real time, ensuring that only accurate and deliverable contact information enters your identity graph. This step is crucial because invalid emails can disrupt customer profiles and weaken cross-channel tracking. Additionally, Reform’s built-in spam prevention ensures that only genuine leads make it through, preserving data quality.

Reform’s multi-step forms and conditional routing make it easier to collect detailed information progressively. This not only boosts form completion rates but also enriches the data needed for effective identity resolution. Even incomplete submissions can provide valuable insights.

Thanks to deep integrations with CRM and marketing automation platforms, Reform feeds your identity graph with accurate, deduplicated data. Designed with privacy compliance at its core - including adherence to regulations like the CCPA - Reform helps you build an identity graph that is both reliable and legally compliant.

Conclusion: Preparing for a Cookie-Free Future

The move away from third-party cookies marks a major shift, pushing marketers to rethink how they collect and use data. One promising solution is identity graphs, which provide a privacy-compliant way to unify customer data. With accuracy rates between 92–97%, these tools not only improve data reliability but also help reduce wasted ad spend - saving up to $0.21 for every dollar spent.

This change calls for immediate action. Start by prioritizing first-party data through methods like email sign-ups, loyalty programs, and form submissions. Tools such as Reform can simplify this process by validating and enriching customer data in real time, ensuring a smoother experience. Next, invest in identity resolution technology to unify data across channels and devices, creating a complete view of your customers. And, of course, make sure your strategies comply with privacy regulations while still delivering the tailored experiences your audience expects.

Taking action now can give marketers a serious edge. Those already using identity graphs are seeing benefits like improved cross-device tracking, better personalization, and more accurate attribution. By adopting privacy-first strategies, they’re setting themselves up for success in a digital world that’s rapidly changing.

This cookie-free era isn’t just a challenge - it’s an opportunity. With more accurate data, stronger privacy measures, and tailored customer experiences, marketers can turn these changes into a competitive advantage. Identity graphs offer the tools to not only adapt but thrive in this new landscape.

FAQs

How do identity graphs help businesses comply with privacy laws while gathering customer data?

Identity graphs play a vital role in ensuring compliance with privacy laws by securely bringing together customer data from various sources while sticking to strict data protection guidelines. They rely on hashed identifiers and anonymized information to safeguard individual privacy, making sure personal details remain protected and are not misused.

By prioritizing transparency and incorporating user consent mechanisms, identity graphs align with regulations such as GDPR and CCPA. This method enables businesses to create a well-rounded understanding of their customers without jeopardizing privacy or eroding trust.

How do identity graphs differ from third-party cookies in tracking and personalization?

Identity graphs and third-party cookies play distinct roles in tracking and personalizing user data. Third-party cookies, which rely on browser-based tracking, gather information about users as they navigate across websites. However, growing privacy concerns and stricter regulations have significantly limited their effectiveness, making it harder to deliver consistent and reliable user insights.

On the other hand, identity graphs take a broader approach by pulling together data from various sources - like email addresses, device IDs, and purchase history - to build a comprehensive, privacy-conscious profile of users. Because they aren’t tied to browsers, identity graphs remain effective even as third-party cookies face obsolescence. This makes them an invaluable resource for marketers aiming to create personalized experiences while adhering to privacy standards.

What steps can businesses take to adopt identity graphs as third-party cookies are phased out?

As third-party cookies lose their reliability, businesses can shift to using identity graphs by following a few practical steps:

• Collect first-party data with care: Focus on gathering data directly from users through opt-ins, subscriptions, and interactions on your website or app. Always ensure compliance with privacy laws like GDPR or CCPA to build trust.
• Use identity resolution tools: Invest in platforms that can consolidate data from multiple sources into a unified view of each customer. This enables a better understanding of user behavior across devices and channels.
• Collaborate with trusted partners: Partner with reliable data providers or organizations to enhance your identity graph. This approach helps maintain accuracy and relevance without relying on third-party cookies.

By implementing these strategies, businesses can achieve effective targeting and personalization while prioritizing user privacy in a world moving beyond cookies.

Related Blog Posts

• Cookieless Analytics: Future of Privacy-First Tracking
• AI Tools for Cookieless Marketing
• Policy Changes Impacting Third-Party Cookies
• Identity Resolution Without Cookies: A Guide