A DIY retailer, for instance, has the potential to increase its sales revenue by 1 – 2% annually with price elasticity of demand application.
Meeting customers’ needs is essential for a retailer wellbeing. A retail business failing to do so will be simply pushed out of the market, soon or later. Some retailers rely on their gut feeling but as data analytics experts, we are perfectly familiar with Arthur Conan Doyle who once said, “It is a capital mistake to theorize before one has data”.
The Collins English Dictionary defines Retail Analytics as “any information that allows to make smarter decisions and manage their business more effectively”.
Retail data analytics comes to help retail professionals to make informed and unbiased decisions in order to boost efficiency. Sales forecasting and demand prediction, product portfolio optimization, trends prediction, etc. are just some of its tools we`ve already discussed at our data analytics blog. Now we are adding one more, the price optimization, also known as price elasticity of demand.
A MILLION-dollar retail question: Whether a price drop will generate sales boost so big it will outperform the lower margin?
Price elasticity of demand is a tool enabling retailers to know how consumers are going to respond to price changes. This way, any price cuts during the promotion season can be risk-mitigated while any uncertainty will be reduced.
Its good to have in mind that consumers are relatively insensitive in price changes of habitually demanded products like bread, tobacco, and alcohol. Since they are necessities, their consumption will be barely reflected by price drop or increase. If we take luxury goods like big TV sets or fashion products, their price elasticity is high and their price drop will lead to sales gains.
Price elasticity of demand can point the sweet pricing spot, which is creating a win-win situation for both retailer and customer.
A retail price elasticity project we`ve made recently clearly showed that a DIY retailer can increase between 1 and 2% of its annual revenue by utilizing price elasticity. With Big Data on your side, the uncertainty about pricing is not just going to diminish but it will be turned into a profit-boosting machine. As Bernard Mar, the author of “Big Data in Practice” said in an article on Forbes:
“Prior to the age of analytics, most retailers would just reduce prices at the end of the buying season for a particular product line, when demand was almost gone.”
By knowing the price elasticity of a particular SKU, a retailer is aware which products can get price increase or decrease with a particular amount and the final financial outcome of such an effort. Pretty important before Black Friday, isn’t it?