Definition
Residual price elasticity is a measure of the dependence of the demand for a product on changes in the price of the same product. For example, if the price of a product increases by 10%, then the residual price elasticity will show how much the demand for that product will change. This value can be used for market research and data analysis to predict changes in demand when price changes.
The concept of residual price elasticity injects competitive dynamics into the pricing equation, encompassing factors like competitive retaliation and cross-elasticity. Consequently, it elucidates why real-world pricing seldom aligns precisely with the theoretically optimal levels proposed by straightforward elasticity analyses.
Whether consciously or unconsciously, marketers factor in competitive dynamics when formulating pricing strategies.
The Encyclopaedia of Marketing
A simple analysis of the price elasticity of demand will rarely lead to optimal prices. This limitation arises from treating all other demand influencers, including competitors' pricing, as static entities, devoid of temporal fluctuations. Yet, competitors' pricing exerts a pivotal influence on sales figures, as price alterations by one company may trigger responses from rivals.
The concept of residual price elasticity amalgamates three critical factors: own price elasticity, cross-elasticity and competitor response elasticity.
Residual price elasticity = Own price elasticity + (Competitor's response elasticity × Cross elasticity)
Own price elasticity denotes the quantity sold variation in response to price adjustments for a product or service.
Competitor response elasticity reflects how competitors alter their pricing in response to changes in the company's prices.
Cross-price elasticity signifies the changes in a company's product or service sales triggered by alterations in competitors' pricing.
Evidently, competitor reactions and shifts in the prices of related goods significantly influence pricing strategies.
Example
Consider this scenario: Online store A sells laptops and has decided to raise the price of one popular model. At the same time, he remembered the price of this model from competitor B, whose price was lower. After this, sales decreased, but competitor B after some time decided to also raise the price in order to earn more money on this model. After some time, sales from online store A returned to their previous level. At the same time, he began to earn more from this laptop model (just like his competitor online store B). Also, online store A recorded how much the price change of competitor B affected the sales of its product and this value can be used in the future to to determine the optimal price and plan changes in demand.
Employing price monitoring proves invaluable in tracking competitors' pricing strategies. By automatically gathering data on a daily basis, businesses amass a wealth of information to analyse market dynamics and optimize pricing strategies.
Read more about price monitoring and analysis
In essence, envision the typical competitive interplay surrounding price fluctuations on products:
- The company adjusts its product pricing and monitors the ensuing sales dynamics.
- Competitors take note of these adjustments and recalibrate their own pricing strategies.
- The company scrutinizes competitors' pricing shifts and evaluates their impact on sales.
The process can continue indefinitely, the greater the volume of data collected, and the more accurate the pricing process becomes. This iterative process facilitates a refined understanding of customer and competitor behaviour, empowering businesses to forecast demand fluctuations accurately. Time-bound data collection emerges as a pivotal element, ensuring precise analysis of pricing dynamics and market trends.
Calculation and Practical Application of Residual Price Elasticity
Understanding how changes in pricing affect sales volume is pivotal for businesses aiming to optimize their pricing strategies. The concept of residual price elasticity offers a sophisticated framework for analysing these dynamics. To estimate the percentage change in demand for a product based on its price adjustments, we employ the formula:
Change in sales volume (%) = Own price change (%) × Residual price elasticity
Consider this scenario:
Company A slashes its price by 10%, resulting in a 20% surge in sales. However, when the competitor subsequently reduces its price by 5%, Company A experiences a 3% shortfall in anticipated sales. By delving into the data, we can derive crucial insights:
The change in the quantity of sales as a function of a change in price is own elasticity::
EA = ∆QA(%)/∆PA(%) = 20/-10 = -2
The change in a company's price in response to a competitor's price change is the elasticity of the competitor's response::
EC = ∆PA/∆PC = -10/-5 = 2
Change in the number of sales depending on the change in competitor's prices C – cross-elasticity:
EAC = ∆QA/∆PC = -3/-5 = 0.6
It appears that when you reduce your price and when your competitor's price is reduced, the sales growth is 6%, but not 10% when the competitor's response was not taken into account.
Let us obtain the residual price elasticity:
Residual price elasticity = Own price elasticity + (Competitor's response elasticity × Cross elasticity)
E0 = EA + (EC x EAC) = -2 + (2 x 0.6) = -0.8
Let's calculate the approximate growth in sales volume:
Sales volume growth ≈ Price change x Residual elasticity
∆QA% = ∆QA x E0 = -10 x (-0.8) = 8
In other words, under all these conditions, when the company's own price is lowered and the competitor's price is lowered, sales are expected to increase.
Practical Implementation:
ShopService.pro offers a comprehensive solution for monitoring and analysing competitors' pricing dynamics, complete with precise recording of price fluctuations over time.
The process is streamlined:
- Customized setup of data collection mechanisms for each competitor's website.
- Thorough data processing and analysis to generate actionable insights.
- Generating a report where you get the information:
- Identification of competitors with prices lower or higher than yours.
- Percentage deviation from your prices.
- Detection of violations against recommended retail prices.
- Calculation of optimal prices considering competitors' pricing strategies.
- Margin calculations based on existing and proposed prices (if purchase price data is provided).
- other opportunities
- Flexible options for data export
- We can also uploading products with optimized prices to your website or online store.
Tailored frequency of monitoring, ranging from daily to monthly reports, facilitating ongoing market analysis and price elasticity calculations.
