GLOSSARY

Price matching is the practice of setting one’s selling prices at the same level as those of one or more competitors for specific products. It can be strict (exactly the same price), flexible (allowing for a difference of a few cents or percentage points), or conditional (matching prices only if competitors lower theirs). It is the operational implementation of a competitive pricing strategy.

Competitive analysis is the systematic study of competitors’ prices, product assortments, promotions, and business strategies. It forms the foundation of an informed pricing policy and enables a company to position its offerings in line with the market. It is an ongoing process that combines data collection (web scraping, field surveys) and analysis (benchmarking, segmentation, scoring).

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Competitive benchmarking is the systematic comparison of prices, product assortments, and promotional offers between a retailer and its direct competitors. More structured than simple price monitoring, it incorporates summary metrics (price index, promotion rate, assortment depth) that enable retailers to manage their competitive position over time and by category.

Bundle pricing involves selling multiple products or services as a package at a total price lower than the sum of their individual prices. It is a powerful tool for increasing the average order value, moving slow-moving inventory, and enhancing perceived value. There are two types of bundles: pure bundles (available only as a package) and mixed bundles (products also sold individually).

Intra-category cannibalization is the phenomenon whereby sales of Product A capture a portion of the sales of Product B, which belongs to the same category or the same brand. It can be intentional (the launch of a new product intended to replace an older one) or involuntary (a promotion that erodes the margin of a competing product). When properly understood and managed, it is a lever; when poorly managed, it is a destroyer of value.

Product chaining involves linking together successive SKUs for the same product over time, even when there are changes in packaging, EAN codes, brand names, or internal SKUs. The goal is to reconstruct a product’s complete history in order to analyze trends in its prices, sales, and performance, even if its technical SKU has changed.

Competitive pricing is a strategy that involves setting prices by directly referencing competitors’ prices (matching, marking up, or marking down). It is the dominant approach in mature, highly competitive markets, such as mass retail, e-commerce, and specialty retail, where price differences are immediately visible to consumers.

Cost-based pricing is a method that involves setting a product’s selling price based on its total production cost, to which a target profit margin is added. It is one of the oldest and most widely used approaches in retail, manufacturing, and services, as it mathematically ensures that direct and indirect costs (raw materials, labor, logistics, overhead) are covered before the profit margin is applied.

The halo effect refers to the phenomenon whereby the price of a product (often a flagship item or one with high visibility) influences the overall perception of a retailer’s price image. If key products are perceived as inexpensive, the entire product range is seen as competitive, even if some products are actually more expensive. This is a powerful tool for building a reputation for value without having to lower prices across the entire catalog.

Cross-price elasticity measures the sensitivity of demand for product A to a change in the price of product B. It reflects the economic relationships between products: substitutes (Coca-Cola/Pepsi), complements (printer/ink cartridge), or independent products. It is an essential concept for managing a product assortment consistently and avoiding pricing decisions that cancel each other out at the category level.

Price elasticity measures how sensitive demand for a product is to changes in its price. Technically, it is calculated as the percentage change in the quantity sold divided by the percentage change in price. A product is said to be "elastic" if a small change in price leads to a large change in sales volume.

A price index is a composite indicator that measures a retailer’s pricing position relative to its competitors for a given basket of products. It helps answer the question: “Am I 5% more expensive or 3% cheaper than the competition?” The index is generally expressed on a base of 100, where 100 represents the average market price or the price of the benchmark competitor.

Pricing KPIs (Key Performance Indicators) are the key metrics used to measure, track, and manage the performance of a retailer’s pricing strategy. They help answer essential questions such as: “Am I competitive?”, “Is my margin growing?”, “Are my promotions profitable?”, and “Are my prices optimal?”. Without KPIs, it is impossible to effectively manage pricing.

KVI (Key Value Items) are the products that have the greatest impact on customers’ overall perception of a retailer’s pricing. These are the items that consumers easily compare across retailers and that directly influence price perception: milk, baguettes, eggs, smartphones, etc. Being competitive on KVI is essential for building a reputation for attractive prices.

Machine learning (ML) is a branch of artificial intelligence in which algorithms learn from data rather than being explicitly programmed. In pricing, ML is used to model complex relationships (elasticity, demand, competition), make predictions, and recommend optimal prices. It transforms a discipline historically based on business expertise into a data-driven and scalable discipline.

Gross margin is the difference between a product’s pre-tax selling price and its pre-tax purchase cost. It represents the gross profit generated on each sale before deducting overhead costs (logistics, personnel, rent, marketing, etc.). Gross margin is expressed as an absolute value (in euros) or as a percentage of the selling price (gross margin rate).

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Net margin is the actual profit generated by a business after deducting all costs: cost of goods sold, operating expenses (personnel, rent, marketing, logistics, IT), depreciation, financial expenses, and taxes. It represents the final profitability and is measured as a percentage of revenue. It is the ultimate indicator of a company’s financial health.

Markdown refers to price reductions applied at the end of a season, collection, or product lifecycle to clear out remaining inventory before it loses all value. Unlike traditional promotions (which aim to generate traffic or volume), markdowns serve an inventory management purpose: to sell what’s left rather than throw it away, sell it at a deep discount, or store it at high cost.

Product matching is the process of identifying and linking equivalent products between your catalog and those of your competitors. The goal is to ensure that when you compare prices, you are comparing the exact same product (same brand, same model, same packaging, same variant). Effective product matching is essential for reliable price monitoring.

Penetration pricing, or a penetration strategy, involves launching a new product or service at a deliberately low price to quickly capture market share. The goal is to attract a large number of customers from the outset, build customer loyalty, and then gradually raise prices once the market position has been established. This approach is typical in competitive markets with high price elasticity.

Demand forecasting is the process of predicting future sales volumes for a product, category, or retail location over a given time frame (day, week, season). It relies on sales history, external variables (weather, calendar, competition), and, increasingly, machine learning models. It forms the foundation of sales planning, purchasing, and pricing strategy.

Sales forecasting (or demand forecasting) involves predicting future sales volumes for a product or category over a given period (week, month, season). It is based on an analysis of sales history, market trends, seasonality, planned promotions, and external events (weather, holidays, social trends). Forecasts inform purchasing, pricing, and logistics decisions.

Price monitoring refers to the process of collecting, analyzing, and tracking competitors' prices. In retail and e-commerce, it relies on automated tools that scrape competitors' websites, track in-store prices, or aggregate panel data to provide a real-time view of pricing positioning.

The price waterfall is a graphical representation that breaks down, step by step, the progression from the list price (or advertised price) to the actual net price received after all discounts, rebates, promotions, and hidden costs. Each step in the waterfall represents a "leak" in margin. The goal is to identify where value is being lost and to optimize each lever.

Web price scraping is a technique for automatically extracting pricing data from competitors’ websites or marketplaces. Performed by web crawlers, it enables the large-scale collection of prices, product descriptions, inventory levels, and promotions. It is the underlying technology behind online price monitoring and competitive benchmarking.

Predictive pricing is a pricing approach that uses machine learning models to anticipate future demand, changes in competitors’ prices, and the impact of a price change even before it is implemented. It transforms pricing from a reactive discipline (adjusting after the fact) into a proactive one (making decisions with visibility into the expected impact).

A loss leader is a price that is intentionally set very low—sometimes even below cost—for a visible and desirable product, with the aim of driving traffic to the store or website. The goal is not to make a profit on that product, but to attract customers who will then purchase other, more profitable items. The loss leader is a classic promotional marketing tactic.

Dynamic pricing is a strategy that involves automatically adjusting prices in real time based on contextual variables such as demand, available inventory, competitors’ prices, time of day, weather, customer profile, and more. Algorithms analyze this data and adjust prices to maximize revenue or profit margins. This practice is common in the airline industry, the hotel sector, and increasingly in e-commerce.

Psychological pricing refers to the set of techniques that exploit consumers’ cognitive biases to influence their perception of value and their purchasing decisions. The best-known example is pricing a product at €9.99 instead of €10: even though the difference is minimal, the brain focuses on “€9” and perceives the product as significantly cheaper.

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The depth of a promotion refers to the extent of the discount applied to a product during a promotion, typically expressed as a percentage discount relative to the regular price. For example, a 20% discount corresponds to a promotion depth of 20%. The greater the depth, the stronger the impact on sales volume, but the lower the unit margin.

Price monitoring is the process of collecting competitors’ prices for a sample of products, either in physical stores or online. It can be done manually (through field surveys conducted by researchers) or automatically (via web scraping, APIs, or data panels). Price monitoring is the first step in any price monitoring strategy.

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Skimming pricing, or the skimming strategy, involves launching a product at a high price to initially attract customers willing to pay the most (early adopters, premium segments), and then gradually lowering the price to reach broader segments. It is the exact opposite of penetration pricing: the goal is to maximize the unit margin at launch rather than volume.

A promotional strategy consists of the decisions that define a retailer’s promotional policy: which products to promote, how often, by how much, through which channels, and for what purposes (traffic, inventory turnover, customer acquisition, etc.). A coherent promotional strategy balances price image, profitability, and sales momentum.

The promotional rate measures the proportion of revenue or sales volume generated by promotional items relative to total sales. It is expressed as a percentage and provides insight into the retailer’s promotional intensity. A promotional rate of 30% means that 30% of sales are generated by products on promotion. It is a key indicator for managing the balance between price image and profitability.

Natural Language Processing (NLP) is a branch of artificial intelligence that enables machines to understand, analyze, and generate text. In pricing, NLP is used to match products with different descriptions across catalogs, analyze customer reviews, extract product features, or detect price mentions in unstructured sources.

Value-Based Pricing sets the price of a product or service based on the value perceived by the customer, rather than on the cost of production. The central idea is that the price should reflect the benefit a buyer derives from the product (time saved, money saved, prestige, performance), which can generate margins significantly higher than those of a traditional cost-plus approach.

Online price monitoring is the automated and continuous collection of prices charged by competitors on their e-commerce sites and marketplaces. It relies on web scraping technologies, partnerships with price tracking services, and APIs. It serves as the foundation for any modern competitive pricing strategy and is essential for keeping pace with the digital market.

Yield management, or revenue management, is a pricing strategy that involves adjusting the price of a product or service in real time based on projected occupancy rates and future demand. Originating in the airline and hotel industries, it has now expanded to many sectors, including ticketing, rentals, restaurants, parking, and even retail for fresh produce.