In March 2017 McKinsey&Co published an article titled “How Retailers can drive profitable growth through dynamic pricing“, in which they state, that:
- Dynamic pricing is a critical capability for competing in retail to drive revenue and margin growth, and
- Dynamic pricing plays a crucial role in improving both consumer price perception and retailer profitability.
McKinsey&Co’s article describes five different methods of dynamic pricing each handled by separate modules working in parallel to generate price recommendations for every product in different product categories with different competitive attributes with respect to price sensitivity. The five modules each consist of rules and algorithms based on analytics and mathematical models, each constructed to handle five different cases:
KVI Module: this module addresses the Key Value Items, which are the top sellers and traffic generators, that consumers tend to remember. These are the most price sensitive products, or more generally speaking: cases or situations when the Price Elasticity of Demand >= 1. In the retail fuel market, this would equally apply to certain times of the day. This possibly relates to 80% of transactions generating only 20% af margin.
Long-Tail Module: with Long-Tail products McKinsey&Co’s article refers to products that are new or have no historical data. The key characteristic here is, that products typically have very low price sensitivity, since consumers have no comparison or no experience with them. Specifically in the case of retail fuel, the reason for low price sensitivity could also be the time of day, location, need, convenience, or the case where the customer isn’t paying for the fuel himself, because he drives a company car or has a fleet card.
Elasticity Module: this module actually addresses the core of dynamic pricing: price elasticity of demand and cross-price elasticity of demand. How does customer demand for a product respond to changes in its price over time and in relation to competitive products’ prices, as well as competitors’ pricing of the same product? This is the ultimate customer centric approach to pricing. The better knowledge you have of the price elasticities of demand, the better you can price to optimise profit and volume (market share) according to your goals. And if you can do this within minutes for each product at each location at any time, you have the perfect dynamic pricing solution.
Competitive-Response Module: this is a rule-based module that prices products as a rule-based response to competitors’ prices and price changes. It is the traditional pricing method of the price-follower who manually responds to what competitors do. This can obviously be improved with automated data collection and processing with decision-tree algorithms of various complexity.
Omnichannel Module: the purpose of this module is to coordinate prices between the retailer’s different channels, like online and offline, if applicable. In the case of fuel retailers this could serve as a differentiation between manned and unmanned stations, i.e. locations with convenience store and facilities versus locations with fuel pumps only and automated payment.
McKinsey&Co’s article illustrates with three case examples, how specific retailers have tailored dynamic-pricing methods to their particular business needs and objectives by carefully differentiating between products (SKUs) according to their demand attributes and applying the methods of one or more of the five modules described.
As McKinsey&Co point out, a best-in-class solution includes all five modules. However, developing such a world-class dynamic-pricing solution is no mundane task, but a rather complex project, that requires a task force of professional data scientists and IT specialists. And the team should preferably have a thorough understanding of the retailer’s industry, business context and objectives.
The reward that retail businesses can expect to capture from dynamic pricing is significant and sustained: McKinsey&Co states a typical impact of 5-10% in margin increase, and a volume growth of 2-5% – along with higher levels of customer satisfaction through improved price perception.
There is no doubt to me, that dynamic pricing offers a significant competitive advantage, and in view of a potentially shrinking retail fuel market indicated by future e-mobility and increasing market consolidation, dynamic pricing has become a necessary capability to grow or at least maintain profitability – especially for small and medium sized businesses.
