Event Property
A piece of metadata attached to a tracked event that provides additional context, such as the product name on a "purchase" event, the plan type on a "subscription started" event, or the search query on a "search performed" event.
Also known as: event attribute, event parameter, event metadata
Why It Matters
Events tell you what happened. Event properties tell you the story behind what happened. A "purchase completed" event without properties tells you someone bought something. With properties like product name, category, price, quantity, and discount code, that same event becomes a rich data point for segmentation, analysis, and personalization.
Event properties are what make analytics actionable. Without them, you can count how many searches happened. With them, you can see what people searched for, which queries returned zero results, and which searches led to purchases. The difference between "we had 10,000 searches" and "42% of searches for winter boots returned zero results" is the difference between data and insight.
Well-designed event properties also future-proof your analytics. When a new question arises months later, you can slice historical data by properties you had the foresight to capture, instead of waiting to collect new data.
Industry Applications
An apparel retailer tracks "product_viewed" events with properties for category, price_range, color, and size. Analysis reveals that users who filter by size early in their session convert at 2x the rate of browsers, leading to a redesigned product listing page with prominent size filters.
A video conferencing tool tracks "meeting_created" events with properties for duration, participant_count, and recording_enabled. They discover that teams using recording convert to paid at higher rates and begin highlighting the recording feature during onboarding.
How to Track in KISSmetrics
When instrumenting events in KISSmetrics, pass properties as key-value pairs with each event call. Use a consistent naming convention (snake_case or camelCase, but pick one and stick with it). KISSmetrics stores properties at the event level and makes them available for filtering, segmentation, and reporting across all report types. Use the Power Report to analyze events broken down by any combination of properties.
Common Mistakes
- -Capturing too many properties, including data you will never analyze, which creates noise and slows instrumentation
- -Using inconsistent naming conventions across teams (product_name vs productName vs ProductName)
- -Storing high-cardinality values like full URLs or user-generated text as properties, which makes reporting unwieldy
- -Forgetting to document what each property means and what values it can take
- -Passing personally identifiable information as event properties without considering privacy regulations
Pro Tips
- +Create an event property style guide before instrumenting and enforce it with code reviews
- +Limit properties to values you plan to filter, group, or segment by - if you would never break a report down by that dimension, do not track it
- +Use enums or controlled vocabularies for property values rather than free text to keep data clean
- +Review your event schema quarterly and deprecate properties that no one uses
- +Include a version property on key events so you can track instrumentation changes over time
Related Terms
User Property
A persistent attribute attached to a user profile that describes who they are, such as their subscription plan, account creation date, company size, or lifetime revenue.
Event Schema
A structured definition of all tracked events in an analytics system, specifying each event's name, required and optional properties, data types, and allowed values.
Data Taxonomy
A hierarchical classification system that organizes analytics data into logical categories, defining how events, properties, and metrics relate to each other and to business concepts.
Data Quality
The measure of how accurate, complete, consistent, timely, and valid data is for its intended use, determining whether analytics outputs and business decisions built on that data can be trusted.
People Tracking
An analytics approach that ties every event and interaction to an individual person rather than to anonymous sessions or pageviews, enabling full lifecycle analysis and person-level insights.
See Event Property in action
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