moheetsubudhi-isb/pricing-toolkit

Measure how sales respond to price and promotions, and turn the answer into a pricing call. Use whenever someone asks for price elasticity or cross-price elasticity; how much volume a price rise or cut will lose or gain; whether a price change will raise revenue or profit; whether customers respond differently when a product is on promotion; whether two products are substitutes or complements; how to fit a log-log demand model on sales and price data; whether a discount pays for itself in extra volume; or how a competitor's price or promotion moves our sales. Not for designing tiers, bundles or segment prices, not for pricing from willingness-to-pay survey data, and not for reading regression coefficients outside a pricing question.

Design how prices differ across customers, versions and bundles so more value is captured without the low price leaking to everyone. Always use this skill to diagnose a product line's price ladder, gaps or margins; when discounting has eroded realised margins or pushed lines into loss; when asked whether volume, bulk or quantity discounts make sense; and for the fairness or legal risk of charging different people different prices, including personalised or dynamic pricing. Also use it for segment prices, good-better-best tiers, versioning, bundles, two-part tariffs, peak and off-peak or regional prices and student or loyalty discounts; how to structure plans and the gaps between them; why customers keep choosing the cheaper tier; and what fences stop a discount leaking. Not for estimating elasticity from sales data, not for running a willingness-to-pay survey, and not for sharing out scarce supply fairly.

Set prices from what customers say or show they will pay: design the willingness-to-pay research, turn responses into demand at each price, and find the revenue- or profit-maximising price for each product, plan, seat or ticket type. Always use this skill when someone has survey responses, or a column of the most each respondent would pay, and wants a demand curve, price-response table or the best price. Also use it for how to find out what customers would pay before a launch; how to write pricing survey questions (direct willingness to pay, Gabor-Granger, Van Westendorp, conjoint); how to price several ticket, seat or plan types with limited capacity; how to correct for people overstating what they will pay; or when to trust a survey over sales data. Not for estimating elasticity from historical sales, and not for designing tier fences, bundles or segment discounts.