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Privacy-First Cross-Device Attribution

Privacy-First Cross-Device Attribution

Om Rathodby Om Rathod
|
5 min read
Feb 26, 2025

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Privacy-First Cross-Device Attribution

Cross-device attribution must work across devices while respecting privacy regulations and not being overly reliant on any single company's ecosystem. With third-party cookies going away, businesses are looking for new ways to achieve accurate attribution without sacrificing privacy.

Navigating Privacy Regulations

Contemporary attribution calls for balance between tracking and privacy regulations. Data cannot be collected and used as freely as before, given privacy regulations like GDPR (General Data Protection Regulation) and CCPA (California Consumer Privacy Act), particularly for third-party cookies.

In contrast, proposals such as Google's Privacy Sandbox seek to offer a way for ad targeting to happen while also maintaining privacy by restricting tracking to mechanisms approved by the user. Consent management matures as well, with the need for granular user consent when it comes to data collection and attribution, advanced systems that respect what a person allows through compliant data modeling techniques.

First-Party Data Strategies

In an era of raised privacy standards, first-party data — or data collected directly from customers — is becoming increasingly important. The confidence of businesses in their cross-device attribution data also increases when they successfully gather first-party data via registrations, loyalty programs, or direct interactions.

Effective strategies include:

  • Encouraging account creation through rewards or exclusive content mechanisms
  • Providing transparent value for customer data
  • Gradually profiling customers once getting to know them better over time
  • Keeping data collection as flexible as possible in terms of the type and structure of data collected across platforms

This information can be used for privacy-compliant attribution with identifiers that the users have explicitly provided and may improve attribution accuracy without dependence on third-party cookies.

How trivas.ai Enables Privacy-First Attribution

trivas.ai is an AI-automated ecommerce analytics platform that aggregates numerous data sources such as Amazon, Shopify, Google Ads, Meta, and more in a single dashboard.

This consolidation enables privacy-first cross-device attribution based on first-party data sourced directly from ecommerce platforms and ad channels. trivas.ai's real-time KPIs and cross-channel performance insights empower marketers to make fully-informed, data-driven decisions that are consistent with privacy and other regulatory restrictions.

With AI-powered recommendations that enable you to find the most efficient use of your budget allocation and optimize campaign effectiveness while complying with privacy standards, it's a key solution for performance marketers navigating the new privacy-first attribution landscape.

In short, trivas.ai empowers the world's leading marketers to adopt privacy-friendly, people-based cross-device attribution that utilizes AI and machine learning to match device data with easy-to-use first-party data.

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Om Rathod

Om Rathod

Co-founder & CRO

Revenue growth leader and co-founder driving Trivas's commercial strategy. Om has led the product vision and execution from scratch. With a strong background in SaaS sales and GTM strategy, Om bridges product innovation with real-world customer needs.

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