Compare common attribution models, pick rules that suit your funnel, and see which marketing channels really contribute to conversions and revenue.
An attribution model determines how conversion credit is assigned to marketing channels and touchpoints in a customer journey. It helps you assess whether search, social media, email, direct traffic, or another source contributed to a purchase, registration, or other defined conversion.
Each model produces a different view of channel performance. Last-click can favor channels that close a conversion, while first-click can favor discovery channels. These differences affect reported return, campaign decisions, and budget allocation, even when the underlying journeys stay the same.
Common models include first-click, last-click, linear, time-decay, and position-based attribution. First-click and last-click assign all credit to one interaction. Linear attribution splits it evenly, while time-decay and position-based models weight selected stages of the journey more heavily.
Start with the decision you need to make. Use first-click to examine acquisition, last-click to assess closing interactions, or a multi-touch model to evaluate longer journeys. Also consider your sales cycle, channel mix, tracking coverage, and whether you have enough reliable data for customer journey analytics.
Set a lookback window that reflects the typical time between discovery and conversion. A window that is too short can exclude early touchpoints, while one that is too long can include unrelated interactions. Define channel naming, direct-traffic handling, campaign parameters, and referral exclusions consistently before comparing results.
You need consistent conversion definitions, campaign parameters, timestamps, channel mapping, and a way to connect permitted interactions across the journey. Review missing data, cross-device gaps, consent status, and duplicate conversions. Collection and processing must follow GDPR requirements and your documented retention rules.
Compare several models side by side and identify channels whose reported contribution changes substantially. Check the findings against customer journey analytics, campaign experiments, conversion quality, and business context. Treat attribution as decision support rather than proof that a channel caused the conversion.