Read the equation
For each listed outcome i, multiply its value v_i by its probability p_i, then add those contributions from i=1 through n. When these are mutually exclusive outcomes covering the possibilities and their probabilities sum to one, the expression is the expected outcome value. Outcomes with larger values, larger probabilities, or both contribute more to the sum. Here p_i denotes an outcome probability; the same symbol denotes a pain-point quantity in the separate Message component.
Its role in the build
The MADDIE Equation — Client Conversion Formula
Terms & definitions
| Term | Meaning in this source |
|---|---|
| L | Lead value as defined in this component. |
| v_i | Value of outcome i. |
| p_i | Probability of outcome i; this is a different use of p_i from the Message formula. |
| i | Outcome index. |
| n | Number of listed outcomes. |
| Σ | Addition of all indexed outcome contributions. |
How it works
Identify the n outcomes and assign each its value v_i and probability p_i.
If treating the sum as an expectation over exclusive outcomes, check that the outcome set is complete and its probabilities sum to one.
Compute each product v_i·p_i and add the n products to obtain L.
Assumptions & limits
The poster supplies neither an outcome set nor a numerical probability distribution or outcome values.
It does not specify whether these probabilities are conditional on closing, which affects how L relates to the separate ER=L×P_c formula.
Original context
Read the surrounding source passage
The MADDIE Equation — Client Conversion Formula: Adds each outcome value weighted by its probability.
Exact original notation
L = Σ_{i=1}^{n} v_i · p_iRelated builds
Sources & provenance
L = Σ_{i=1}^{n} v_i · p_i