Most attribution models tell you where leads came from. Revenue attribution tells you where revenue came from — and those are often very different answers. A channel that generates a high volume of MQLs may contribute almost no closed-won revenue; a lower-volume channel may be closing deals at 3× the rate. This stack connects your closed-won data from Salesforce with Marketo multi-touch attribution and ad platform spend, runs it through Claude, and produces a revenue-by-channel model you can defend in a board meeting without hedging every number.
The Stack
The Prompt
This stack is built around the Attribution Audit Diagnostic Prompt. Here's the abbreviated version — the full prompt with all variables and usage notes is on its own page.
You are a B2B marketing analyst building a revenue attribution model. Review the Salesforce closed-won data, Marketo touchpoint report, and ad spend data below. For each marketing channel, calculate: total revenue attributed, revenue per dollar spent, and first-touch vs. multi-touch contribution split. Flag channels where MQL volume is high but closed-won revenue is disproportionately low. Identify the 2–3 channels with the strongest revenue-per-dollar efficiency.[ ... continued — see full prompt ]
The Workflow
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Export Salesforce closed-won opportunities
Pull all closed-won deals from the last 90 days with campaign source, primary channel, and opportunity amount. Include the marketing campaign influence fields if your Salesforce instance tracks them.
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Pull Marketo multi-touch attribution report
Export the Marketo program performance report for the same period — program touches, influenced pipeline, and influenced revenue by program type.
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Add paid media spend data by channel
Include total spend per channel for the period. This is what turns an attribution report into a revenue efficiency model — dollars in vs. revenue attributed out.
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Run through the Attribution Audit Diagnostic prompt
Paste all three datasets with revenue attribution framing. Claude builds a channel-by-channel revenue model, flags MQL-heavy channels with weak closed-won contribution, and identifies the highest-efficiency channels.
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Export to Google Sheet and post exec summary to Slack
Paste the revenue model into a Google Sheet. Post the executive summary to your leadership Slack channel before the next pipeline review. Flag any channel that warrants a budget conversation.
What This Replaces
- Attribution models that show where leads came from but can't connect to closed revenue
- Defending channel investment decisions based on MQL volume rather than revenue contribution
- Spending hours pulling data from three systems to build a model you can't fully trust
Related Stacks
New stacks drop weekly.
Each one includes the tools, the Claude prompt, and the workflow logic. Free — built for in-house B2B demand gen managers.