Attribution models (8+1)

Short Description Hive9 supports multiple attribution models for assigning credit to tactics. This article gives a tour of the standard models and when to use each.

What this article answers

The attribution models Hive9 offers out of the box.
The intuition behind each model.
How to pick a model for your reporting.

What attribution does

Attribution assigns "credit" for a marketing outcome — a response, an MQL, a closed deal — across the tactics that contributed to it. Because most B2B buying journeys involve multiple touches, attribution helps you understand which tactics drove which results.

The standard models

Hive9 supports the following attribution models out of the box:

1. First Touch

All credit goes to the first tactic the buyer engaged with.

Best for: understanding what drives awareness and entry into the funnel.

2. Last Touch

All credit goes to the last tactic before the outcome (e.g., last touch before a closed deal).

Best for: understanding what closes deals — but biased toward bottom-funnel tactics.

3. Linear

Credit is split equally across every tactic in the buyer's journey.

Best for: treating every touch as equally important — useful in steady-state evaluation.

4. U-Shaped (Position-based)

Credit is weighted toward the first and last tactics, with a smaller share to middle touches.

Best for: acknowledging the importance of both attraction and closing while still crediting nurture.

5. W-Shaped

Credit is weighted toward the first touch, the lead-creation touch, and the opportunity-creation touch.

Best for: B2B funnels with distinct lead and opportunity milestones.

6. Time Decay

Credit increases for tactics closer in time to the outcome.

Best for: longer sales cycles where the most recent touches are most causal.

7. Data-Driven

Credit allocation is algorithmically derived from the actual paths in your data.

Best for: mature analytics teams with sufficient data volume to support model training.

8. Custom (Even / Weighted)

Custom rules defined by your organization — for example, double-weighting paid media touches.

Best for: organizations with strong, opinionated attribution policies.

9. Unattributed

A "model" that surfaces touches and outcomes without assigning credit — for raw event analysis.

Best for: debugging, data quality checks, and analysis that doesn't need model assumptions.

How models show up in reporting

Most performance dashboards let you switch between attribution models. Switching changes the per-tactic credit numbers but doesn't change the underlying events. The same buyer journey produces different attribution outputs depending on the model.

[SCREENSHOT NEEDED — Dashboard with attribution model selector]

Picking a model

A few practical principles:

One model per audience. Don't shift models between meetings — pick one for your leadership conversations and stick with it.
First Touch and Last Touch are easiest to explain but tell incomplete stories. Use them as supplements, not the main model.
Linear or U-Shaped is a reasonable starting default for most B2B teams.
Data-Driven is best when you have the volume. Don't switch to Data-Driven without enough data to support it.

Common questions

Can I compare attribution models side by side? Some dashboards let you display two models on the same view. Otherwise, switch models and screenshot for comparison.

Why doesn't a tactic show in attribution reports? Either (1) it has no associated outcomes in the Measure data, (2) its integration-side mapping is broken, or (3) the model's rules exclude it. See My integration isn't syncing data into Hive9.

Does Hive9 attribute revenue or just lead counts? Hive9 supports both, depending on what your integration feeds in. Revenue attribution requires opportunity / closed-deal data from your CRM.

Can I build custom attribution? Yes — the Custom model lets you define weighting rules. Work with your CSM if you need help configuring complex rules.