Segments & Attributes

Overview

Derived attributes turn customer history into reusable facts. Segments use those facts, together with profile, channel, and event data, to define saved audience rules.

Raw customer data is often too detailed to use directly in audience rules. The CDP turns that detail into customer facts, then uses those facts to build audiences that marketing and operations teams can preview, reuse, and export.

Attributes

Derived attributes are backend-defined facts calculated by ResultFly from profile data, channel state, and event history.

Typical examples include:

• total spend
• first purchase date
• last purchase date
• current loyalty tier
• count of qualifying events in a period

These values are managed by the platform so teams do not have to recompute them manually in every campaign or export. In this delivery, users do not create arbitrary custom derived-attribute rules from custom event properties in the UI.

Derived attributes matter because they turn history into a simple customer-level fact. Instead of rebuilding “how much has this customer spent?” or “when was the last purchase?” in every segment, teams can reuse the same computed fact consistently.

Event Conditions vs Derived Attributes

Event conditions look for specific things that happened. Derived attributes summarize what has happened over time.

For example, “users who purchased a ticket for a specific match” is an event-based condition. It checks whether a matching event exists, often with a registered event property such as match_id.

“Customers whose total spend is above a threshold” is a derived-attribute condition. It uses a computed customer fact that summarizes purchase history over time.

Segments

A segment is not just a temporary customer list. It is a saved rule that can be previewed, reviewed, reused, and exported.

A segment may combine:

• profile fields
• attributes
• channel presence
• channel consent status
• event existence
• registered event-property conditions

The segment builder gives teams a broad list of inputs:

• profile fields such as city, loyalty status, or balance-related values
• platform derived attributes
• communication channel presence
• channel consent status
• channel reachability
• event conditions based on ACTIVE event definitions
• compatible DEPRECATED event definitions when they remain available for historical segment rules
• filterable properties from registered event definitions

Use the group operator to decide how conditions are combined:

• AND means every listed condition must match
• OR means at least one listed condition must match

For event-based rules, a segment can check whether an event happened, whether an event did not happen, or how many times an event happened in a period. Event rules can also use registered filterable properties when the event definition allows them.

Examples:

• customers in Gold loyalty status
• profiles with email consent granted
• users who purchased a ticket for a specific match
• customers whose total spend is above a threshold

Why Saved Rules Matter

ResultFly stores the segment definition itself, not just a temporary result set.

The matching audience can change as customer data changes. For example, a customer may enter or leave a segment after a new event arrives, consent changes, or a derived attribute is recomputed.

When a segment is exported, ResultFly evaluates the saved segment rules and produces the audience snapshot for that export job.

That gives teams:

• a reusable audience definition
• preview before export
• consistent use across operators
• a stable object that can evolve through review and validation

Guardrails

Guardrails make sure marketers can only build segments from data that ResultFly knows how to interpret safely and consistently.

ResultFly validates segment rules against the registered CDP model.

In practice, that means:

• unknown event types are rejected
• unsupported properties are rejected
• only approved filterable properties can appear in segment rules
• export runs asynchronously for reliability

This keeps the segment builder simple for marketers and predictable for developers.

How This Fits the Flow

1. Customer data enters the CDP through profiles, channels, and events.
2. Backend-defined derived attributes turn repeated or historical data into reusable facts.
3. Teams build a segment from profile fields, channels, event conditions, and derived attributes.
4. The segment can be previewed to check the current matching audience.
5. The saved segment rule can be reused and reviewed.
6. Export runs the saved segment rule and produces an audience snapshot for that export job.