Revenue Attribution
The process of connecting revenue events (purchases, subscriptions) to the marketing channels and campaigns that drove them. Accuracy depends on how many events the analytics system actually observes.
How does revenue attribution work?
Revenue attribution assigns conversion credit to a traffic source. Different attribution models assign that credit differently:
- Last-click: the source recorded on the conversion pageview gets full credit.
- First-touch: the source recorded on the first observed pageview gets full credit.
- Multi-touch (linear, time-decay, position-based): credit is split across observed touchpoints of the same identified user across sessions. Requires per-user tracking.
Last-click and first-touch models work with aggregate, anonymous event data. Multi-touch models require the analytics system to identify a visitor across sessions — which, in Europe, usually requires cookies and consent.
What does revenue attribution require to be accurate?
Revenue attribution is uniquely sensitive to data loss. If your analytics miss 87% of pageviews to consent rejection, ad blockers and browser restrictions, the remaining 13% is what the attribution model operates on — so the channel totals it produces are biased by whatever demographic survived the filter. The typical result: direct traffic is inflated, top-of-funnel channels are undervalued, and budget allocation follows the bias.
How does SealMetrics handle revenue attribution?
SealMetrics does last-click revenue attribution on 100% of observed events. When a conversion event fires, the traffic source recorded on that pageview is credited. Channel totals roll up by campaign, landing page and creative. There is no multi-touch model and no cross-session stitching — because there is no cookie, no personal identifier and no way to recognise a returning visitor. The trade-off is deliberate: aggregate channel totals that reconcile with your backend, in exchange for giving up per-user journey analysis.
Because every pageview is captured through cookieless analytics, last-click attribution reflects the full observed traffic — not the cookie-accepting minority.
Related concepts
- Attribution ModelA rule or algorithm that determines how credit for conversions is distributed across marketing touchpoints. Common models include first-touch, last-touch, linear, time-decay, and data-driven attribution.
- Multi-Touch AttributionAn analytics model that distributes conversion credit across multiple touchpoints observed for the same identified visitor. Requires per-user tracking and is not part of SealMetrics' last-click, anonymous architecture.
- Event TrackingThe method of recording specific user interactions on a website beyond pageviews — clicks, form submissions, video plays, downloads, and eCommerce actions. GA4 uses an event-based data model where every interaction is an event.
- Data Loss in AnalyticsThe gap between actual website traffic and what analytics tools report. Caused by consent rejection, ad blockers, browser restrictions, and data sampling. Typically 70-87% in the EU.