Create advanced Works with: Any AI

Discount Campaign Impact Analysis (Before and After)

Before after Has example

Check whether a promotion really made money.

The Open buttons send the prompt text as currently shown below to that site only when you click. Fill in the placeholders first.

Evaluate a discount campaign. Campaign details: [DISCOUNT_DETAILS]. Dates: [CAMPAIGN_DATES]. Data for the period before, during, and after: [PASTE_DATA]. Margins and costs: [MARGIN_DATA].

Structure the analysis:
BEFORE: baseline daily orders, revenue, margin, and new customers in the two weeks before, as averages.
DURING: the same measures, plus the discount cost, meaning revenue given away on orders that would have happened anyway.
AFTER: the same measures for the two weeks after, to look for a pull-forward dip.
UPLIFT TABLE: incremental orders = (daily orders during - baseline) x days; incremental revenue; incremental profit; and payback after discount cost. Show every formula.
CUSTOMER QUALITY: share of new customers, repeat rate if available, and refund rate versus normal.
LEARNINGS: three conclusions, each with a confidence level (high, medium, low) and caveats about seasonality or other changes.
Say plainly which numbers are measured and which are estimated, and do not call the campaign a success on revenue alone when margin or repeat behavior says otherwise.
Finish with a decision (repeat, change, or stop) and an improved test design using a holdout group or an alternative offer. Do not claim causality beyond the data.

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BEFORE (2 weeks): 40 orders/day, revenue 2,000/day, margin 38%, new customers 9/day.
DURING (20% off): 58 orders/day, revenue 2,320/day (average order fell from 50 to 40), margin 26%, new customers 17/day.
AFTER (2 weeks): 33 orders/day (pull-forward dip).
Uplift: incremental orders during = (58-40) x 7 days = 126; dip after = (40-33) x 14 = 98; net +28 orders. Incremental profit: during profit/day = 2,320 x 26% = 603 vs 760 before (-157/day); campaign profit lost about -1,100 over 7 days. 
Customer quality: 29% of orders came from new customers (17 of 58); refund rate 7% versus 4% normally.
Conclusion (medium confidence): not profitable on first orders; repeat purchases would need to exceed 30% to pay back. Decision: change. Test a bundle offer with a holdout group.

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