Trackingplan is an embedded software platform that automates the monitoring and auditing of digital analytics, marketing pixels, and campaign performance to ensure data quality and attribution accuracy. It provides real-time alerts for errors and anomalies, enabling users to quickly identify and resolve issues without manual data audits.
Funding
$2.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Many organizations struggle with maintaining the integrity of their digital analytics implementations, leading to inaccurate data, flawed insights, and wasted marketing spend. Manual audits are time-consuming and often fail to catch errors in real-time, resulting in delayed identification and resolution of critical issues.
Solution
Trackingplan is a software platform designed to automate the monitoring and auditing of digital analytics, marketing pixels, and campaign performance, ensuring data quality and attribution accuracy. By embedding a single pixel, Trackingplan observes the data sent to analytics, marketing, and attribution integrations, using AI to identify patterns and detect anomalies. The platform provides real-time alerts for errors, traffic changes, specification validations, campaign monitoring, and privacy risks, enabling users to quickly identify the root cause of issues and resolve them before they impact performance. Trackingplan eliminates the need for manual data audits, delivering trusted insights and saving time for marketers, analysts, and tagging specialists.
Target Audience
Trackingplan is designed for digital analysts, marketing and growth teams, developers, QA teams, and agencies who need to ensure the quality and accuracy of their digital analytics data.
Features
- Automated discovery and auditing of Martech stack implementations using real data
- Real-time alerts via email, Slack, or Teams for traffic anomalies, rogue events, schema problems, and campaign misconfigurations
- Automated root cause analysis to streamline diagnosis and resolution times
- Specification validation to detect missing properties, incorrect property types, and unexpected property values
- Campaign monitoring to spot attribution errors, UTM naming convention errors, and missing pixels
- Privacy risk identification to detect data privacy breaches and compare events based on consent mode
- Regression testing to validate event sequences and compare page variations
- A single pixel implementation that requires no crawling, maintained tests, or code changes