Perfect attribution is not the goal. Useful attribution is.
Attribution models cause endless arguments because people expect them to be truth. They are not truth. They are a lens.
The goal is not perfect attribution. The goal is an attribution model that is consistent enough to guide decisions and stable enough to improve over time.
First touch attribution answers: where did this lead start? It is useful for understanding what creates awareness and new demand.
Last touch attribution answers: what was the final driver before conversion? It is useful for optimizing conversion actions and closing steps.
Multi touch attribution tries to distribute credit across multiple interactions. It can be useful, but it also introduces complexity and false precision if your data hygiene is weak.
Before you choose a model, you need measurement discipline. If your UTMs are inconsistent, attribution cannot be reliable. That is why this post should link to UTM discipline. If your event measurement is inconsistent, you cannot even agree on what a conversion is. Link to event naming conventions.
Then you need operational truth. If outcomes are not logged in the CRM, attribution will optimize for the wrong goals. That is why attribution is incomplete without outcome logging. Once outcomes are logged, you can report models against qualified leads and wins instead of raw leads.
A practical recommendation for most service businesses is to start with first touch and last touch, then layer complexity later only if it changes decisions and you trust data quality.
For implementation, attribution alignment often requires both tracking work and CRM mapping. That points to Automations Webhooks CRM Systems and, for paid optimization, Paid Ads and PPC Management.