Detect, investigate, and prevent tracking, campaign, privacy, consent, and data quality issues.

What it does

Trackingplan is an AI-powered quality layer designed to identify, investigate, and proactively prevent issues within marketing and analytics data. It addresses silent budget waste and distorted decision-making caused by tracking errors, campaign misconfigurations, privacy violations, and poor data quality.

Key features

AI-driven issue detection — Leverages artificial intelligence to automatically identify anomalies and errors in marketing and analytics data that might otherwise go unnoticed.
Real user session analysis — Monitors actual user sessions to provide live or near-live alerts when tracking or data collection deviates from expected behavior.
Automated analytics QA — Automates the process of quality assurance for analytics implementation, reducing manual effort and increasing delivery capacity.
Budget waste prevention — Identifies and flags issues that lead to wasted marketing spend due to inaccurate tracking or campaign performance data.
Data quality enhancement — Ensures the integrity and accuracy of data, leading to more reliable insights and better decision-making.

Use cases

Proactively identifying and fixing broken website tracking tags before they impact campaign performance.
Ensuring GDPR and CCPA consent management is correctly implemented and firing as expected.
Validating data accuracy for e-commerce conversion tracking and attribution models.
Automating the manual process of analytics debugging and data validation for multiple clients.

What makes it different

Trackingplan provides an AI-powered, automated quality layer that continuously monitors real user sessions for data integrity, offering near-live alerts and proactive prevention of issues that traditional methods often miss until significant damage is done.

David Pombar

Projects

Trackingplan

David Pombar

Projects

Trackingplan