Pricing Optimization & Marketplace Economics
Elasticity, dynamic pricing, matching and the OR toolkit data scientists use in marketplaces
Set prices and match supply to demand with economics, estimation and optimization rather than guesswork: the demand curve, own- and cross-price elasticity, the Lerner markup rule and why a revenue-maximizing price is almost never a profit-maximizing one (a 4 percent profit gain from a 17 percent revenue loss in the worked example); estimating elasticity when observed prices are endogenous (a naive log-log slope of -1.09 against a true -2.0, repaired by randomization at -2.01 and by a cost instrument at -2.16), price experiments, double machine learning, conjoint and pooling across products; multinomial and nested logit demand with the cross-elasticity matrix and the independence-of-irrelevant-alternatives trap, cannibalization and promotion pull-forward worked by hand; single-product first-order conditions, margin floors, price ladders and MAP, a multi-SKU linear program over price scenarios with inventory and margin constraints whose duals are read as shadow prices (0.47 and 0.38 of profit per extra unit of stock, 7.74 per point of margin floor), markdown optimization, and the legal and ethical limits of personalized pricing; revenue management with Littlewood protection levels (a protection level of 44 seats maximizing simulated revenue), surge pricing and the supply response it needs, and bandits with an off-policy-evaluation gate; two-sided marketplaces (liquidity, take rate, subsidies, network effects, bipartite matching where Hungarian assignment saved 14.7 percent of ETA over greedy, stable matching, dispatch); an operations research primer on LP and MIP duals, solvers and heuristics; and how to measure pricing changes with guardrails, long-term effects and fairness audits. Every number comes from code that was run (NumPy, SciPy HiGHS, statsmodels, fixed seeds).
Practice questions (6)
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Design an elasticity estimation program for a grocery delivery app
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Formulate a markdown optimization as a linear program and interpret the dual
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Design surge pricing for a ride-hailing app with guardrails
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Formulate the order-to-courier matching problem for a delivery platform
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Critique a personalized pricing proposal
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