Audit intermediate Works with: Any AI

Pricing Power and Discount Leakage Audit

Before after Has example

Find where revenue leaks through discounts.

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Show me how much revenue I lose to discounts and where my pricing is weaker than it needs to be. My price list: [PRICE_LIST]. Sales or invoice data with discounts: [SALES_DATA]. Who can approve discounts: [DISCOUNT_AUTHORITY].

Structure the answer as BEFORE and AFTER.

BEFORE (what the data shows): average discount by product, by customer segment, and by salesperson or channel; the share of deals discounted; the revenue given away in total (list price minus actual price); discounts with no stated reason. Present as a table and call out the three largest leaks.

AFTER (a better policy): a discount rule set with tiers, what must be given in return for each discount (longer term, prepayment, volume, case study), who approves what, and a floor price. Show the revenue effect of the new policy if the discount average fell by one-third, as a simple calculation with my numbers.

Add: three scripts for holding price in a negotiation, and a list of signs that I could raise prices (high win rate, no price objections, long waiting list). Mark any assumption you made.

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BEFORE (from the sales data): average discount 14%; 62% of deals discounted; Salesperson C averages 22%; 9 deals discounted with no reason given. Revenue given away: $48,300 (list price minus actual).
Largest leaks: (1) end-of-quarter discounts, 19% average; (2) bundles for existing customers, 17%; (3) deals under $5,000, 21%.
AFTER (policy): up to 5% free; up to 10% needs a 12-month term; up to 15% needs prepayment and manager approval; floor price 80% of list.
If the average fell by one-third (14% to 9.3%), revenue would rise about $16,100 on the same volume (estimate, assumes no lost deals).
Script for holding price: "I can't change the price, but I can add onboarding sessions if we sign a 12-month term."

• discounts
• pricing-power