How segments are built from goal sets
Tailkey generates segments automatically from its attribution scoring. Each segment is a group of visitors identified by behavior and linked to device IDs for targeting. This page describes how segments are created and how to use them.
Segment types, and when each becomes available
Availability depends on whether a goal set is definedGeneral segments are computed from raw behavior and are available before a goal set is defined. Attribution segments are computed from the attribution model's output and become available after a goal set is defined and the pipeline has run.
Segment types
Tailkey computes two types: general segments, built from raw behavioral data, and attribution segments, built from the attribution model's output. This distinction determines when each type becomes available and what question it can answer. The comparison below shows both:
Because attribution segments are computed once per goal, the same visitor can appear in a segment for one goal and not for another. This is expected: proximity to one goal does not imply proximity to another, and the model reports each goal separately.
The goal set is not a filter applied at the end of the pipeline. It defines what the entire model measures.
One site, three goals, three outcomes
A goal set defines the event that counts as a conversion: a purchase, a signup, or a demo request. Tailkey runs the attribution pipeline once for each goal set, producing separate journeys, scores, and segments. The following example uses the same site with three different goal sets:
When the run finishes, the segments below are available. They are generated by the model, not defined manually.
Segment catalog
A completed pipeline run produces the following segments, grouped by the decision they support: five are audiences you can target directly, two indicate how much to trust those audiences, and one controls timing. All figures update when you change the goal set.
Segments are not limited to reporting. Any tier or row above can be exported from the dashboard as a list of device IDs, which can be uploaded as a custom audience to Google Ads, Meta, or an email platform. Select the tiers to export; the resulting campaign targets exactly the segment identified by the model.
General and attribution segments are most useful together: one identifies who is at risk, the other explains why it matters.
Combining churn risk with attribution
Churn risk is a general segment. It tracks engagement decay across the site and identifies visitors who are becoming less active, without requiring a goal set. On its own, it identifies who to prioritize but not why. Combined with an attribution segment, it produces a shortlist with a stated reason:
Each row combines churn risk with attribution data. For example, a visitor with high churn risk who stalled at the pricing table, with high journey confidence, for the purchase goal, indicates both an at-risk visitor and the reason for the risk. Export the row to get device IDs for targeting.
Define a goal set to generate segments
General segments are available as soon as your data connects. Define a goal set to generate attribution segments after the first pipeline run. Segments are scored against your visitors and can be exported for use in campaigns.
The model behind it
How Tailkey's attribution modeling works
See how touchpoints are scored before they become segments.
Read the attribution guide →