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Stage conditions

A stage condition is the filter attached to a funnel stage. When filters pass, an account can sit on that stage (subject to the funnel’s evaluator rules). Conditions are built with the same structured filter experience used elsewhere in FunnelStory—groups of rules combined with AND / OR logic inside the builder.

What you can filter on depends on the evaluator​

In the funnel stage drawer, FunnelStory passes different filter palettes based on the funnel’s evaluator:

EvaluatorStage filter types (high level)
TimelineMetrics, activities, and account properties only.
Last matchBroader palette aligned with audience-style filters—for example signals, subscriptions, account metrics, health tags, funnel stages / funnel states, and more—plus the timeline-compatible types.

Why the split: the Timeline evaluator replays history with stricter semantics; it only consumes filter types that are meaningful for that replay. Last match evaluates the account’s current snapshot, so additional dimensions are available.

If you switch evaluators after building filters, revisit each stage: types that are incompatible with Timeline should be removed or simplified so evaluation stays deterministic.

Condition structure​

  • Groups — Organize rules into AND/OR combinations the way you would for audiences or account list filters.
  • Empty stages — A stage with no configured filter conditions does not count as “configured” for readiness checks and does not contribute useful gating.
  • Save path — Each stage saves independently via Save Filters in the drawer.

Practical tips​

  • Start with the minimum rules that truly define “this stage is achieved,” then add refinements—dense filters are harder to reason about in Last match and can cause unexpected movement when data changes.
  • Align metric windows and activity definitions with how your models refresh so accounts are not stuck waiting for stale inputs.
  • When a stage is only for reporting nuance inside a broader step, consider merging steps instead of stacking many near-duplicate filters.