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Select a model using payment-conversion evaluation

Compare model variants on payment conversion in an isolated test experiment and select using prespecified windows, sample counts, and uncertainty rather than public benchmarks alone.

Goal

Compare model variants on payment conversion in an isolated test experiment and select using prespecified windows, sample counts, and uncertainty rather than public benchmarks alone.

Steps

  1. Fix the eligible population, model arms, offer conditions, and conversion window. [src-openai-select-model-using-payment-conversion-evaluation]
  2. Record exposures and test-mode payment events in Stripe, linked to model versions. [src-openai-select-model-using-payment-conversion-evaluation]
  3. Compare conversion rates and sample sizes, then document the selection and limits. [src-openai-select-model-using-payment-conversion-evaluation]

How to verify

Verify arms, exposure counts, conversion numerator/denominator, and time windows before reporting a winning model.

Troubleshooting

If traffic or offers differ, stop comparing raw conversion; fix randomization/attribution and rerun on the same population.

Permissions

Prerequisites

Permissions

Limitations

Conversion results depend on sample size, experiment bias, and changing users; one experiment cannot guarantee future performance.

Pinned upstream source

https://github.com/openai/openai-cookbook/blob/5bd6cb40b6b84b69b2032d810610aa85064102df/examples/stripe_model_eval/selecting_a_model_based_on_stripe_conversion.ipynb

Repository
openai/openai-cookbook
File path
examples/stripe_model_eval/selecting_a_model_based_on_stripe_conversion.ipynb
Pinned commit
5bd6cb40b6b84b69b2032d810610aa85064102df
Source checked
2026-10-14 · Reviewed against the pinned upstream source

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License: MIT

Main topic

Turn ecommerce campaign materials into a reviewable weekly brief

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