name: Measure business impact tagline: Turn experiment or launch results into a scale, change, or stop recommendation. summary: Give ChatGPT an experiment or launch plan, success metrics, cohort data, dashboard exports, customer signals, and launch notes, then ask it to quantify lift, check guardrails, explain segments, and draft a sourced impact readout. skills:
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token: $spreadsheets description: Calculate lift, guardrails, segment differences, and supporting tables or charts.
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token: google-drive url: https://github.com/openai/plugins/tree/main/plugins/google-drive description: Read experiment plans, dashboard exports, cohort tables, and launch notes.
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token: $documents description: Create a stakeholder-ready impact readout with methodology notes and caveats. bestFor:
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Experiments, launches, or initiatives that need a clear scale, adjust, or stop recommendation.
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Teams comparing lift across cohorts or segments while checking guardrail metrics.
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Readouts that need methodology, caveats, and confirmed results separated from interpretation. starterPrompt: title: Write a business impact readout body: >- Measure whether [initiative, experiment, or launch] improved [target outcome].
Use the experiment or launch plan, success metrics, relevant dashboards, cohort or assignment data, customer signals, and launch notes I provide. Quantify lift or movement, check guardrail metrics, inspect segment differences, and explain whether the team should scale, change, or stop the initiative.
Return a business impact readout with charts, methodology notes, caveats, source links, and a clear recommendation. Separate confirmed results from interpretation and flag any missing inputs. suggestedEffort: high relatedLinks:
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label: "OpenAI Academy: Data science teams" url: https://openai.com/academy/codex-for-work/how-data-science-teams-use-codex/
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label: Analyze datasets and ship reports url: /codex/use-cases/datasets-and-reports
Start with the decision the readout must support
An impact readout should connect the result to a decision, such as scale, adjust, or stop. Provide the experiment or launch plan, success metrics, cohorts, guardrails, and customer context so ChatGPT can show what the data supports.
- Name the initiative, target outcome, evaluation window, and decision owner.
- Attach the plan, metric definitions, assignment or cohort data, dashboards, and launch notes.
- Ask ChatGPT to validate inputs and explain the analysis method before writing the recommendation.
- Run the starter prompt and check lift, guardrails, and segment differences.
- Review methodology, caveats, and missing data with the analyst or experiment owner.
Keep measured results separate from interpretation. If the design or data cannot support a causal claim, ask ChatGPT to narrow the language rather than fill the gap.
Audit the recommendation
Before sharing the readout, ask for a compact evidence audit focused on the recommendation and its most important numbers.