Event tracking is not just about adding scripts to a website—it is about creating a structured, reliable foundation for behavioural analytics. Companies that take event tracking seriously will benefit from clear insights, data-driven decision-making, and a scalable analytics strategy. By embedding tracking into engineering workflows and ensuring governance, you can really help businesses unlock the full value of their event data.
Event tracking is the backbone of behavioural analytics. It enables organisations to capture, understand, and act upon user interactions within their digital products.
However, many companies struggle with poor implementation, governance, and integration of event tracking into their data strategies. This blogpost explores why event tracking is essential, what a good implementation looks like, common pitfalls, and how our approach differentiates from others in the space.
What is Event Tracking?
Event tracking refers to the systematic collection of behavioural data that captures user interactions with digital products. This data is often blended with Customer Data Platforms (CDPs) and extends into other data collection paradigms, though many companies fail to engage with these additional layers effectively.
At its core, event tracking involves:
- Capturing key user actions (e.g., page views, button clicks, form submissions) – objective data points that are foundational in any customer analytics platform.
- Structuring event data to be actionable and scalable
- Ensuring events contain sufficient context for later analysis
- Integrating event data into broader analytics and business intelligence frameworks.
Why Invest in Event Tracking?
Event tracking provides foundational data that enables companies to understand how customers interact with their products. The value of investing in a robust tracking framework includes:
- Accurate Behavioural Insights: Enables data-driven decision-making by ensuring data quality.
- Scalability: Supports product evolution without losing tracking continuity.
- Trustworthy Data: Events should be truthful, accurate, and not subject to subjective interpretation.
- Foundation for Analytics: Well-structured event tracking underpins everything from conversion optimisation to feature adoption analysis.
- Efficient Engineering Workflows: When tracking is integrated into development cycles, it becomes a habitual and efficient process rather than an afterthought.
What Does Bad Look Like?
Many companies fail at event tracking due to misconceptions about its complexity and importance. Some common failure scenarios include:
1. Over-reliance on Out-of-the-Box Analytics Tools
- Solutions like Mixpanel, Amplitude, and Google Analytics often market themselves as plug-and-play.
- These tools provide event tracking but lack visibility and governance.
- Teams end up with thousands of overlapping events with no clear ownership.
2. Lack of Clear Ownership
- Engineering teams often do not receive clear guidance on what events should be tracked.
- Product and data teams assume external tools handle everything, creating an “ownership vacuum.”
- The result is an unstructured mess of event data that cannot be trusted.
3. Misinterpretation of Event Tracking
Event tracking is often confused with other types of event logging:
- Logging: Engineers write logs for debugging purposes, with no defined schema or business context.
- Application Events: Used in microservices architecture for system state monitoring, often minimal in context.
- Analytics Events: Require rich contextual information (e.g., user state, session attributes) to drive business decisions.
If analytics events are treated like logging or application events, they lack the necessary structure & context for effective analysis.
How Tasman Does Things Different
Many agencies and software solutions fail to provide structured, objective, and business-aligned event tracking. Our approach focuses on:
1. Event Tracking as a First-Class Citizen
- Tracking is embedded into engineering workflows, making it part of the “Definition of Done.”
- Developers and data teams collaborate on defining tracking requirements early in the product lifecycle.
2. Structured Governance and Visibility
- We implement blueprints that define tracking methodologies within a company’s unique context.
- Our frameworks ensure visibility across product, data, and engineering teams.
3. Objective Event Data for Business Analytics
- Our events are atomic, capturing unambiguous user actions (e.g., “Page Viewed,” “Button Clicked”).
- Well-tracked events serve as the foundation for all analytics, from conversion optimisation to product iteration.
4. Balancing Collection and Modelling
- We strike the right balance between collecting data at the source and enriching it later through modelling.
- Over-tracking leads to unnecessary engineering complexity, while under-tracking results in weak analytics.
- Unlike tools like Mixpanel, which offer limited modelling capabilities, we focus on Snowplow and warehouse-native solutions that allow retrospective data modelling.