Dynamic pricing implies that the price of a good is not fixed over a longer period of time, but temporally adjusted based on market demand, customer characteristics, etc. Arvind Sahay from the Indian Institute of Management Ahmedabad provided an overview in the MIT Sloan Management Review in 2007 when and where to use this technique.
The larger the market, the number of customers and the amount of transactions, the greater the opportunity for dynamic pricing
Sahay argues that the automotive market in the United States is one example here: In 2003, Ford used in-depth market analysis data to adjust the prices for a car model based on spatial and temporal demand throughout the country, working with different promotions and incentives and changing the corresponding prices on a weekly level. In comparison with GM, which had to lower its prices during the same period by 2 percent, Ford could increase overall price levels by 0.2 percent.
The higher customer involvement and the larger heterogeneity in customers’ needs, the greater the opportunity for dynamic pricing
The researchers’ example here is a hairdresser in London with opening hours from Monday to Saturday and a diverse client base (pensioners, families with kids, business people). During the week, workload was usually moderate, but on Saturdays, when business people were struggling to get appointments in between the remaining customers, there were, despite prior scheduling, still long waiting times.
After introducing demand-based pricing, with lower rates during the week and higher rates on Saturdays, customer satisfaction increased: business people were thankful to have shorter waiting times, which they were awarding with higher prices, while families and pensioners were happy about lower prices during the week. Overall, the number of customers increased, revenues grew by 10 percent, and profits by 25 percent.
Products with a well-defined shelf-life offer a greater opportunity for dynamic pricing
Classical examples of a well-defined shelf-life is fashion. Sahay gives an example from a department store that moved away from fixed-date promotions (e.g. 10 percent off in November, 20 percent off in December, etc.) to a demand-based approach that carefully tracked inventory levels of various lines of apparel per store. Using this approach, the department store chain could also increase its prices in some cases, while offering more selective price promotions during some months. Overall, profitability grew by 15 percent, while the amount of goods that remained for the clearance sales was reduced by 80 percent.
Sahay provides more examples in his article based on auctions, which occur relatively seldom in retailing and therefore, are not presented here.
Overall, these examples provide some guidance for managers to introduce dynamic pricing. However, the examples are void of competitive activities, which, in our view, are essential when setting prices accordingly. Read more about it in our blogpost “The Ultimate Online Pricing Guide – 5 Steps Toward Active Price Management”
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