Attribution & Marketing Reporting
One honest view of which channels produce results, and where they disagree.
Every platform claims credit for the same sale, and no single attribution model is correct. We consolidate channel and spend data, compare models side by side, and build reporting that shows you where the disagreement sits rather than hiding it behind one number.
Tools we work in
- Google Analytics 4
- Looker Studio
- BigQuery
- Google Ads
- Meta Ads Manager
- HubSpot
- Salesforce
- dbt
Scope
What this covers
The specific work included when you engage us for this service.
- Consolidation of cost and outcomes across paid, organic, email and offline channels
- Comparison of last-click, first-click, linear, position-based and data-driven models
- Cost per acquisition by channel, campaign and, where volume permits, audience
- Lead quality reporting by source using CRM outcome data rather than form fills
- Offline conversion imports so closed deals are credited back to their origin channel
- Incrementality tests and holdouts where your volume can support them
- Documentation stating the model behind each figure and its known limitations
What you receive
- 01A cross-channel report with the attribution model named for every figure shown
- 02A model comparison showing which channels gain or lose under each approach
- 03A shared metric dictionary so the numbers mean the same thing to everyone
Questions
Attribution & Marketing Reporting, answered
Which attribution model is the right one?
None is universally right, and each platform defaults to the model that flatters itself. We report at least two side by side so you can see which channels gain or lose under each. In our experience decisions become more cautious rather than less once the size of the disagreement is visible.
Can you measure channels that have no click to track?
Not directly, and we will not pretend otherwise. Direct mail, podcasts, word of mouth, most dark social and many offline conversions produce no clickable identifier. We handle them with survey questions, geo tests or holdout experiments where volume allows, and we mark them as estimates rather than letting a model silently claim their results.
Will this tell us whether to increase or cut ad spend?
It gives you a defensible basis for the decision rather than a guarantee. Attribution describes correlation in the data you collected; only an incrementality test establishes causation. Where budgets are large enough to run one, we recommend it, and we will say plainly when the honest answer is that the data supports a range rather than a single number.
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Tell us where the manual work is
A 30-minute call. We map the process, tell you what we would automate or build first, and what it costs. No retainer before you agree the scope.
- No retainer before scope is agreed
- Written plan you can act on alone
- Worldwide delivery, on your hours