Data increasingly drives the direction of commercial strategies,and price elasticity is often presented as the Holy Grailof pricing.. This statistical tool, which measures how the demand for a product changes in response to its price, may at first appear to be the cornerstone of an optimized pricing strategy. However, one question remains: Is price elasticity really a reliable lever for all pricing decisions?
In recent years, some software providers and retailers have made it a strategic pillar, relying on a mathematical reading of the demand function. Others, however, remain skeptical and favor more nuanced approaches, viewing elasticity-based strategies as secondary—believing that more fundamental strategic priorities must be addressed before such a model can be meaningfully applied.
This divergence highlights an important reality :price elasticity cannot be seen as a universal solution. It has its limitations, and its application requires discernment and contextual understanding. It is neither systematic nor a top priority across all product categories. Consumer demand—particularly for essential goods—does not always follow purely economic logic.
This brings us to a central question: is price elasticity a reliable compass for all pricing decisions?
Price Elasticity: A Compelling Statistical Tool, but Not All Products Respond Equally
Why Does Price Elasticity Fascinate? The Promise of Rationality and Precise Margin Optimization
By definition, price elasticity measures the variation in the quantity demanded resulting from a change in price.. The higher the absolute value of the elasticity coefficient,the greater the sensitivity to price.
What makes price elasticity so attractive is its ability to model the market’s increasing demand in response to an adjusted average price. In theory, knowing the rate of price change is enough to estimate the corresponding percentage change in quantity demanded. It’s a compelling logic, aligned with the principles of microeconomics—particularly in contexts of perfect competition.
But many economists agree on the practical limitations of this approach. Biased historical data—especially regarding price variations Promotional price changes or stockouts often distort elasticity estimates. For low-volume products, the quantities traded are simply too limited to generate a reliable demand function. In a competitive market environment, price is rarely the only factor influencing demand.
Take the example of fast-moving consumer goods (FMCGs): their production volumes tend to follow predictable sales cycles.
In contrast,niche private label(PL) products, often perceived as lower quality, may exhibitlow elasticity.—or even non-existent . This means that a price increase does not necessarily lead to a drop in demand, as some consumers continue to purchase these products out of habit or brand loyalty.
National brands in fast-moving consumer goods (FMCG) are generally more sensitive to price changes than entry-level or organic products, which are perceived as higher or standard quality items, depending on consumers’ income levels.
National brands in fast-moving consumer goods (FMCG) are generally more sensitive to price changes than entry-level or organic products, which are perceived as higher or standard quality items, depending on consumers’ income levels.
Price Elasticity: Two Opposing Yet Complementary Schools of Thought
Scientific approach
This approach is based on the ability to automate pricing throughutility functionsand behavioralequations It relies on models that incorporate cross-price elasticity, substitution elasticity, and even integrated approaches involving marginal revenue or marginal cost.
The advantage? A systemic approach to pricing based on demand, capable of modeling either overall market demand or steady demand depending on the product.
But real-world conditions don’t always conform to theoretical models.
For example, Carrefour has been investing significant internal resources for several years in the analysis of elasticity. While the results regarding promotional elasticity have been conclusive, those related to base-shelf elasticity have been more disappointing, as they have yet to yield any truly actionable indicators.
The drop in demand was unexpected, as customers interpreted the price reduction as a sign of declining product quality. The algorithmic supply function had not anticipated this image-related effect.
The pragmatic business approach
Here, elasticity is just one parameter among many. Retailers rely more heavily on supply-driven logic, market demand forecasts, or strategic choices such as maintaining low prices on flagship products.
Thus, E. Leclerc sustains growing demand for baguettes not through calculated elasticity, but through an implicit social contract with its loyal customer: offering essential goods at a fair price.
At Intermarché, price adjustments for diesel or transportation-related products follow a logic that balances supply and demand, but also considers perceived social value.
Les marges sont parfois sacrifiées pour défendre une position sur des produits de demande de transport, où l’offre croissante ne suffit pas à stabiliser les quantités offertes.
3. The Stance of Optimix Solutions: Clarity, Balance, and Adaptation
At Optimix Solutions, we believe that price elasticity of demand—powerful as it may be—cannot, on its own, dictate pricing strategy. Since 2011, our approach has been based on a clear principle: to integrate data without ever idolizing it.
We take into account normal and inferior goods, overall demand effects, and marginal behavioral variations. We analyze demand curves to enrich the strategy, but we complement them with qualitative, commercial, and field-based insights.
For us, elasticity is an elasticity module—a tool in the service of a broader line of reasoning.
Price Elasticity: A Powerful Lever, but One That Requires Discernment
Price elasticity, while undeniably a valuable tool for understanding consumer behavior and optimizing margins, cannot be used in isolation or applied mechanically. It must be understood within a broader context—one that considers sector- and category-specific characteristics, as well as competitive and market dynamics.
Consumers have never been so volatile, and excessive price manipulation—especially when driven by opaque algorithms—can be risky. A poorly perceived or poorly calibrated adjustment could open the door to more opportunistic competitors, ready to seize market share by exploiting the vulnerabilities such changes may create..
Examples from leading retailers show that striking a balance between data-driven approaches and more pragmatic, ground-level strategies is essential for developing effective and sustainable pricing strategies
At Optimix Solutions, we firmly believe that optimal pricing is built on a balanced vision and a thoughtful combination of data, intelligent analysis, and strong field knowledge. Our pricing optimization solutions, combined with our proven methodology, empower our clients to navigate this complex landscape successfully.
If you’d like to learn more about our approach and discover how we can help you maximize your margins and refine your pricing strategies, feel free to reach out. Together, let’s explore how to combine data intelligence with market reality to make price elasticity a powerful and relevant lever in your pricing strategy.
Contact us today to turn your data into effective strategic decisions.
