I write about pricing strategy, applied economics, and the practical challenges of translating quantitative analysis into business decisions. Posts draw from my research and client advisory work across pricing optimization, marketplace economics, and experimentation.
April 2026 | Pricing Strategy
A revenue-maximizing algorithm recommends a 40% price decrease for an electronics category with elastic demand, projecting an 82.7% revenue increase. At a 65% COGS structure, that recommendation reduces profit by 144%. The algorithm is technically correct on its own terms and commercially destructive in practice. Here is why the revenue-profit divergence happens and what to do about it.
Read MoreApril 2026 | Pricing Strategy
Pricing teams spend months refining demand models and elasticity estimates. The analysis that actually determines whether recommendations are implemented correctly is cost validation, which takes two to four weeks and is almost always skipped. A five-point COGS error forfeits 70 to 75% of potential profit gains. A 20% elasticity error preserves profitability across all scenarios. The implications for how pricing teams allocate their analytical resources are direct and counterintuitive.
Read MoreComing Soon | Marketplace Economics
In the Olist Brazilian e-commerce marketplace, 97% of customers make exactly one purchase and never return. The explanation is not poor customer experience. It is a structural feature of the aggregator model that makes platform-specific loyalty formation impossible. Understanding why changes how you think about retention strategy in marketplace businesses.
Dinesh R Poddaturi, PhD
Applied Economist
Pricing Strategy
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