Multi-Channel Attribution Calculator
Split credit across Search, Social, SEO and direct.
Your numbers
Total attributed revenue
₹50.00 L
Google Search
40% · ₹20.00 L
Meta / Social
30% · ₹15.00 L
Organic / SEO
20% · ₹10.00 L
Direct / Referral
10% · ₹5.00 L
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Definition
Multi-channel attribution decides how credit for a sale is shared between the touchpoints that influenced it. Last-click gives everything to the final interaction; first-click to the discovery; linear and position-based spread it. The model you choose changes which channels look profitable — without changing what actually happened.
The formula
Channel credit = Conversion value × Model weight for that touchpoint
No model is correct. Last-click systematically overpays search and remarketing and underpays everything that created the demand; first-click does the reverse. The value is in comparing models and noticing where they disagree.
A worked example
The same sale, three models
- 1A ₹50,000 sale touched Meta (discovery), then organic search, then branded search.
- 2Last-click: branded search gets the whole ₹50,000. Meta gets nothing.
- 3Linear: each of the three gets ₹16,667.
- 4Position-based (40/20/40): Meta ₹20,000, organic ₹10,000, branded ₹20,000.
Under last-click, Meta looks worthless and would be cut — which would remove the discovery that started the whole path. Same sale, opposite decisions.
How to move the number
Compare models rather than choosing one
Run last-click and position-based side by side. Channels that look strong under one and weak under the other are exactly where your budget decisions are most fragile.
Ask buyers where they heard about you
A single self-reported field on the enquiry form catches the influence no tracking sees. It is imprecise and still more honest than a model that assigns zero to everything untracked.
Use holdout tests for the truth
Turning a channel off in one region for a few weeks tells you its real incremental contribution. It is the only method here that measures cause rather than correlation.
Where people get this wrong
- Making budget decisions on last-click alone, which reliably defunds the channels that create demand.
- Adding up platform-reported conversions across Google and Meta, which double-counts the same sales.
- Treating an attribution model as measurement rather than as an assumption you have chosen.
- Ignoring untracked influence entirely, which is a growing share of how Indian buyers actually decide.
Multi-Channel Attribution Calculator — questions we get
Which attribution model should I use?
Position-based is a reasonable default for most SMBs — it credits discovery and conversion without ignoring the middle. But use it alongside last-click rather than instead of it, and treat disagreements between them as information.
Why do Google and Meta both claim the same conversion?
Each sees only its own touchpoints and claims credit under its own model and window. Adding them together will always exceed your real sales. Your back-end revenue is the only reliable total.
How do I measure channels that produce no click?
You cannot attribute them directly. Use a self-reported field on the form, watch branded search volume as a proxy for demand you created, and run geographic holdout tests when the spend justifies the effort.
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