attribution

Each platform claims credit for the same conversions using its own attribution window, and ad platforms also count view-through conversions. De-duplicate all platform numbers against one source of truth, usually your CRM or backend, and never sum conversions across platforms.

For long B2B sales cycles, show first-touch and last-touch side by side rather than picking one, since the gap between them reveals how demand is created versus closed. Position-based attribution is a defensible primary model, paired with self-reported surveys at demo or signup.

Append the visitor's anonymous analytics ID to the outbound booking link via the tool's metadata passthrough, then merge it in the booking webhook using an identify call with the anonymous ID. Only ever pass anonymous IDs, never emails or identified user IDs, to avoid corrupting profiles.

Platform-reported ROAS is inflated by self-crediting, view-through counting, and post-iOS modeled conversions, so it is not incremental ROAS. Run an incrementality test such as a geo holdout or on-off test to measure true lift, and use incremental CPA to drive budget decisions.

Direct traffic is mostly a measurement gap, not a channel: it includes stripped referrers, dark social, app-to-web visits, and dropped tracking. A large direct share usually means your top of funnel is working but under-measured, so use self-reported surveys to surface the hidden sources.

Use MMM when you have material spend across multiple channels including offline ones like podcasts or TV, plus two to three years of weekly data. For smaller budgets and short cycles, clean UTMs with last-non-direct attribution and a post-purchase survey are more practical.