Factors Influencing Elasticity Calculation

Price elasticity is The most practical and meaningful metric, to answer the crucial question in price management: How do customers react to a price increase/price reduction of x percent? On the basis of this key figure, it is possible to set up a differentiated price management system. Always in focus: the customer.

Unfortunately, the road to reliable elasticity values is rocky. In practice, there are many pitfalls and peculiarities which, if not adequately considered, cause major inaccuracies in determining price elasticity. The result can be serious miscalculations. The aim of this series of blog posts is to highlight these pitfalls. The focus of this article is on the question: Which factors influence price elasticity in which way?

Many intervening influencing factors

All aspects of the sales process and the market affect the relationship between price and sales. The number of possible influencing factors and interdependencies is so large and varied that the search for completeness cannot be effective. There is no checklist which, when carefully completed, guarantees that all important factors have now been taken into account and that robust elasticity values can therefore be derived.

In order to show the diversity of influencing factors, I have provided a selection of frequently mentioned influences here:

• Information about the number of competitors, their relevance, their prices and their promotions
• Information about your own advertising measures: What advertising measures are there? What was your running time? How do the measures affect pricing (coupon campaigns, etc.)? Are the measures individualized or common?
• Location information: Online or offline? Standing alone or in a shopping mall? City or country?
• Information on competing and complementary products
• Trademark information
• Holidays, seasonality and, if applicable, information about the days of the week, the time of sale or even the weather or weather forecasts that were valid at the time of sale

It is neither practicable nor possible to integrate all of these factors into one model. In addition, many of these factors have complex interdependencies with price and sales. Two examples are intended to illustrate the complexity that can be associated with modelling individual factors.

Brands

Brands are one of the most important marketing tools. When successfully implemented, brands increase customer loyalty and serve customers as quality standards. These aspects have an impact on pricing. For established brands/branded products, it is expected that customer reactions to price changes will be less severe than for private brands from retail chains, for example. Our practical experience only partially confirms this assumption. Although branded products generally have higher prices than other products, this does not yet result in increased pricing freedom, particularly for retailers. Branded products are researched more actively and consciously by customers. In markets with a high level of market transparency, there are therefore significant price change reactions for branded products.

Product life cycle

The scientific literature makes ambivalent statements when it comes to the question of how the product life cycle affects price elasticity. The assumptions regarding the functioning of product life cycles are diverse. A new product may have relevant advantages, so that customers only develop price awareness when there are corresponding competing products. At the time of product launch, there is therefore a low price elasticity, which increases over time. On the other hand, it is also possible to find product categories that have experienced strong product differentiation. The result is increased customer loyalty and thus almost necessarily lower price elasticity.

Especially for retail companies with a diverse product portfolio, the product life cycle aspect can be a difficult aspect to understand when determining elasticity. However, this does not mean that the product life cycle is unimportant. From our point of view, it only means that product life cycles are an analytically demanding construct to be understood due to their diverse potential impact dynamics.

Which factors should be considered?

I don't know a complete list of all possible factors that may be relevant. Nor can they exist due to the complexity of the task and the diverse markets. However, there are still a few important guidelines that can be helpful. Finally, a few guidelines:

Objective of the analysis: It is important to clarify in advance the objectives with which elasticity should be determined. Is it about determining elasticities for individual products or for a brand? Is a basic elasticity sought for a product or is it about elasticities in a specific sales situation, such as as as as as as part of an advertising campaign? Depending on the requirements, different minimum requirements are derived with regard to the factors to be taken into account.

Data availability: An obvious, sometimes somewhat sobering but very important selection criterion is data availability. It is a helpful step to get at least a superficial overview of the available data at the beginning. This alone often limits the number of usable variables. At the same time, this step can be a source of many new and relevant features. This point doesn't have to be sobering, but can be the starting point for many creative ideas.

Business area: Which business segment does the customer operate in and what are the characteristics of their products? Are these business-to-business or business-to-consumer transactions? Are they short-lived consumer goods or durable consumer goods? Is the consumer good easy to store or one that expires quickly? The exchange with the respective project partner is always one of the first steps in this process. This is where the expertise lies.