Worked Example: Default Multi-Touch Attribution Scenario
Compare how deal revenue is credited across First-Touch (100/0/0), Last-Touch (0/0/100), Linear (equal split), U-Shaped Position-Based (40% First / 40% Last / 20% Middle), and W-Shaped attribution models.
- Enter parameters for Multi-Touch Attribution in the input controls.
- Apply formula: LinearCredit = DealValue / TouchCount; U_Shaped = 40% First + 40% Opportunity/Last + 20% divided across Middle touches.
- Inspect the 3 interactive SVG charts and comparison table for sensitivity across input ranges.
Result: Produces instant Multi-Touch Attribution output with domain-verified units and sensitivity table.
Business & Marketing Ā· Paid Acquisition & Attribution
Multi-Touch Marketing Attribution (First-Touch, Last-Touch, Linear & U-Shaped) Calculator: inputs, method, and how to read the result
Compare First-Touch, Last-Touch, Linear, and U-Shaped (40/20/40) revenue credit across touchpoints.
Choose inputs for the case you are checking
The defaults are illustrative. Replace them with values for your case and keep the units shown beside each field.
- Display Currency: Amounts are treated in the selected currency; no foreign-exchange conversion is applied.
- Closed Won Deal Revenue: Total revenue or pipeline value of the converted customer journey.
- Total Marketing Touchpoints: Total marketing/sales touchpoints in the buyer journey (minimum 3).
What the calculation includes
With the default values shown, U-Shaped vs. Linear Touch Credit is U-Shape: USD 20,000.00 First/Last ⢠Linear: USD 10,000.00. The calculation follows Multi-Touch Attribution Formula; the formula and variable definitions above show how the inputs combine.
One-input check: With the other defaults held constant, changing Closed Won Deal Revenue from 50,000 USD to 55,000 USD changes U-Shaped vs. Linear Touch Credit from U-Shape: USD 20,000.00 First/Last ⢠Linear: USD 10,000.00 to U-Shape: USD 22,000.00 First/Last ⢠Linear: USD 11,000.00. This is a comparison inside the calculator's stated model, not a prediction.
Where to use caution
- Inputs are within standard operating ranges for the specified equation.
- Extreme boundary conditions may require specialized empirical adjustments.
Scope: Global Standard Check the assumptions and limitations against your situation before relying on the estimate.
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