What is the challenge?

Price is a major lever for a company’s profit. Price changes directly affect profit margin. Thus, an increase or decrease in price has a greater impact on profit than an increase or decrease in sales of the same percentage. Furthermore, new customers can be won and market share increased through price. Companies therefore have a great interest in applying an optimal pricing strategy. There is often little or no experience with new products and services. This leads to great uncertainty when setting prices. At the same time, pricing is becoming a complex task due to increasing price transparency through the internet and price pressure in many industries, for example from international competitors. 

What data can help?

  • Historical market data (own market price points and sales trends for products at specific prices)
  • Data on offers from competitor suppliers
  • Data from advertising and marketing
  • Macroeconomic data (income, consumer confidence index)
  • Seasonal data (e.g. weather)
  • Cost information for the products being priced
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Use case category: pricing

How can companies use their data?

Using the various data, demand, price sensitivity, cross-price elasticities (measure of change in demand due to price changes) and price effectiveness can be processed and analyzed together. Thus, depending on the strategy, the optimal price corridor for products or product groups can be determined for the respective point in time and the addressed customer segment. The effects of price changes can be simulated by integrating the various data. At the same time, the data-based insights can be used to obtain pricing rules for entirely new offers. With dynamic pricing, companies continuously change their prices based on the evaluation of current demand and supply data. 

Where is this use of data already being applied?

The service company Uber uses dynamic pricing (surge pricing) in its business model. When demand for rides with Uber is high, the price per ride increases and vice versa. This balances supply and demand and increases revenue. Pricing is data-driven via the Uber platform.

The aerospace engineering group Boeing determines the value of aircraft individually and based on data, depending on the age and condition of the aircraft, among other factors. Data on the current market situation of certain models is also used in the pricing process.

The online travel agency Priceline sets dynamic prices with so-called “Name your own price” bookings. Based on data on the occupancy of hotels, flights or car rentals, unused capacity is identified and auctioned off on the platform. In this way, the price is measured and set according to customer demand and willingness. 

How does this use of data contribute to value creation?

Pricing is better aligned with the market and customers through data usage and automation. This means that greater sales can be achieved, but also that a wider range of customers can be optimally served. This has a stabilizing or increasing effect on value creation.

Aim of data use

Sources: Business Insider (2019), Boeing (2018), Psychology Today (2019)