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Consumer demand analysis
In Economic Analysis Team
Analyses conducted by EY encompass a wide variety of solutions aimed at delivering insights into consumer willingness-to-buy and customer segmentation. We help our Clients in planning production volume and pricing in the view of various changes in market environment: competitor landscape or prices of the substitute products. We identify main demand drivers and quantify their impact on sales.
What EY can do for you
Consumer demand analysis, conducted by EY EAT, focuses on:
Consumer demand analysis may be combined with:
What are the outcomes?
The analysis of consumer demand may give answers to such questions as:
- How many customers would switch to alternative products if the Client increased the price of its product (i.e. what is the price elasticity of the demand for Client’s products)?
- What brands/products are the main competitors for the Client’s product (some of them may not be obvious, e.g. is beer a competing product for wine? Are soft drinks or juices also competing products for wine?)
- What are the common demand patterns across customers?
- Which groups of customers drive the demand for the Client’s product (more or less affluent, younger or older, etc.)?
- How considered changes in taxation may impact the Client’s sales?
- What are the potential outcomes of various market scenarios for the Client?
What purpose can it serve?
- Enhances the understanding of crucial drivers of the demand for the Client's products
- Develops the knowledge on the Client's customers and competitors
- Offers insights that will allow the Client to improve the pricing and marketing strategy
- Adjusts sales tools to customer preferences, improving customer service, and hence, customer loyalty
How does it work?
We apply the model-based approach to analyse consumer demand in a more organised and comprehensive way.
In our approach, we usually apply advanced econometric modelling that allows us to capture the formal statistical relationship between the demand for the Client’s product(s) and the factors that influence it, as well as key differentiators that divide customers into specific segments. Furthermore, the results can be enhanced by in-depth data mining with the statistical matching techniques.
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