How to set prices for maximum sales
It’s a lesson many of us learn in Economics 101 – sales volume is a function of price.
While we all know that in general the lower the prices the more we’ll sell and vice-versa, it’s a largely conceptual relationship that is of limited use to a business because it’s so imprecise. But with the smart use of data we can determine how pricing affects sales for specific products and provide businesses with a high degree of confidence about the outcomes of their pricing decisions before they’re implemented. The difficulty of accurately establishing this relationship in the past has been that there are many factors in addition to price that can affect sales.
Take the seemingly simple product category of bottled water for sale in a convenience store. Undoubtedly, price influences sales volume, but there are other factors.
A customer might buy a premium brand for $4 or a house brand bottle for $2.50, and the relativity of these prices will affect sales. The supermarket next door might be selling home brand water at $2, and some customers will decide it’s worth the extra time and effort to queue up at the supermarket to save 50c.
Non-price factors also affect sales
Then there are the non-price factors. More people will buy water on hot days; sales in the CBD might drop during public holidays when more people are out of town; and brands will be affected by their own and their competitors’ sales promotions.
In the example of water, we could look back through time and see how many bottles of premium water were sold across hundreds of convenience stores over the past five years to understand what’s driving demand. We are trying to find out why sales might vary from one day, week or month to the next by looking at all the things that have changed. We will take into account factors like the weather, holidays, competing product promotions, and the proximity of competitors’ shops so that we can effectively isolate the impact of price.
Weighing up different pricing scenarios
Once a business has an accurate and usable statistical model of the relationship between sales and price for their products, the business leaders can start considering different pricing scenarios. We can compare how the differential price between products will affect sales. What if the price of the premium water drops from $4 to $3 so that it’s only 50c more than the own brand water? How many more people would buy the premium brand? And if the supermarket next door was selling home brand water at 50c less than the $2.50 for the convenience store, how many people would pay extra at the convenience store to save themselves the bother of going to the supermarket and queuing up? And what would happen if the convenience store dropped its price to $2.25?
Advanced data analytics and modelling of previous prices and sales can provide a business with a very powerful pricing tool. They can use the model to determine the right combination of price and sales volumes to maximise their margins. Or if they only have a limited amount of stock to sell, they can determine the price to move all the stock at the best possible margin.