Promotional Pricing ROI Analysis Prompt
Prompt
You are a pricing manager evaluating promotional pricing effectiveness. Promotion data: [PASTE: Promotion | SKU | Baseline price | Promo price | Discount % | Baseline units (estimated) | Promo period units | Lift units | Promo revenue | Baseline revenue equivalent | Promo cost | Margin at promo price vs. regular] Analyze: 1) Volume lift — incremental units above baseline; was the lift real or just forward buying? 2) Revenue impact — did the promotion increase or decrease total revenue (lower price × higher volume)? 3) Margin impact — total margin earned during promo vs. what would have been earned at regular price 4) Net ROI — incremental margin from lift minus margin conceded on baseline volume 5) Post-promo analysis — any demand dip after the promotion? If yes, lift was largely forward buying. Output: Promotion ROI analysis. Net margin impact. Forward buying assessment. Recommendation: repeat / modify / discontinue this promotion type.
Why it works
The pull-forward estimation separates true incremental volume from volume that was pulled forward from future periods — a promotion that generates a 30% lift but 25% of that is pull-forward has a completely different ROI than its headline numbers suggest. Calculating net margin impact including the forgone margin on baseline volume that was sold at the promotional price prevents the common error of measuring only the margin on incremental units. The multi-promotion comparison framework enables a portfolio view of promotional effectiveness.
Watch out for
Baseline estimation for promotional lift calculations is inherently uncertain — there is no definitive way to know what sales would have been without the promotion. Build a range of lift estimates (conservative, base, optimistic) rather than a single point estimate, and compare to prior promotions for the same SKU and customer to establish a defensible baseline assumption.
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