Price optimization is the mathematical analysis that a company performs to determine the response of potential buyers to different prices for its products and services. The aim is to meet a company’s objectives of maximizing profits and growing and retaining a customer base.
A good price optimization model is critical for the success of a company. Exaggeration of the price might alienate customers while low prices may cause a loss of potential profits. Many companies base their prices on competitors’ prices though there is no indication that their competitors’ prices are optimized. A good model for price optimization guarantees a balance between customer satisfaction and maximized profits, while allowing the company to determine which of these factors they would like to emphasize.
Companies should rely on past interactions with customers, mainly sales history and customer feedback, while also taking into account data representing manufacturing costs, projected profits, and additional economic factors relevant to the company.
A good price optimization model should utilize data from competitors, including pricing, feedback, and total profits. Circumstantial events such as recessions and market dips should also be taken into account. Price optimization is a matter of customer psychology so internal data alone is not sufficient for the creation of a good and dynamic model.
Additional data that could potentially be useful could include surveys, questionnaires, weather, and seasonal factors.
Firstly, the collection of external data from competitors can be very difficult; creating a reliable comparison between your product and competitors’ product is also complicated. Prediction of customer reactions to varying prices for different products can also be quite challenging.
As much as 60% of shoppers choose retailers with optimal prices. … IBM learned that as many as 73% of respondents (retailers) are planning to use intelligent automation to enhance their pricing and promotion by 2021.
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