Pricing Methodology

Win Probability

The statistical likelihood that a given proposal will result in a won deal, estimated using historical data, deal characteristics, and competitive context.

Definition

Win probability is the core input to Bayesian pricing and expected-value calculations. It answers the question: "Given everything we know about this opportunity, what are the chances we win?"

Win probability is not a single number. It is a function that varies with price, deal size, client type, competitive intensity, and relationship strength. A deal at €50k with a warm referral has a very different win probability than the same deal at €100k against an incumbent.

Bayesian win probability estimation uses historical deal data to establish a prior distribution, then updates it with deal-specific signals. The output is a posterior probability distribution that becomes more accurate with every deal logged.

The practical application: if a €80k proposal has a 40% win probability but would generate €30k in margin, the expected margin is €12k. If dropping the price to €70k raises win probability to 55%, expected margin becomes €13.2k. The lower price actually yields higher expected margin — a calculation impossible without win probability modeling.

Most agencies don't track win probability at all, let alone model it across deal dimensions. This is the single biggest data gap in agency pricing and the primary opportunity for statistical pricing improvement.

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