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Click Prediction Value Calculator

Work out click prediction value instantly with clear inputs, formula shown and shareable results.

About Click Prediction Value Calculator

In ad and feed ranking, the click model's predicted probability is multiplied by value to set bids and to forecast revenue, so calibration matters as much as ranking quality. A model with a perfect ranking but a predicted CTR 14 percent above reality overstates revenue by 14 percent and overbids by the same margin, which is why the predicted-over-actual ratio is monitored continuously.

Formula

Revenue from CTR

revenue = impressions x CTR x revenue per click; calibration ratio = predicted CTR / actual CTR

Worked example

With the default values below, Click Prediction Value Calculator returns Actual revenue of $36,750.00. Change any input above and every figure here is recalculated in your browser.

Inputs used

Impressionsminimum 1
5,000,000
Predicted click-through rateaccepts 0–100 %
2.4 %
Actual click-through rateaccepts 0–100 %
2.1 %
Revenue per clickminimum 0
0.35

Results

Actual revenue
$36,750.00
Revenue the model forecast
$42,000.00
Predicted / actual CTR
1.1429
Forecast error in revenue
$5,250.00

Step by step

  1. 1Values used
  2. 2Revenue from CTR
  3. 3Actual revenue= 36,750.00
  4. 4Revenue the model forecast= 42,000.00
  5. 5Predicted / actual CTR= 1.1429
  6. 6Forecast error in revenue= 5,250.00

Assumptions and limits

  • The result is derived only from the 4 inputs listed above. Anything not among them is not part of the calculation.
  • In particular, this calculator does not take inflation, tax, fees or charges or compounding frequency into account.
  • Figures are rounded for display to 4 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.

How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.

Frequently Asked Questions

How is a miscalibrated model fixed without retraining?

Post-hoc calibration: Platt scaling or isotonic regression fitted on recent data maps predicted scores onto observed frequencies and is cheap to refresh daily.

Why do downsampled negatives break calibration?

Training on a subsample of non-clicks shifts the base rate, so predictions must be corrected back with the known sampling ratio before they are used as probabilities.

Related Calculators

Click Prediction Value Calculator – Calculate Actual revenue