Using pricing analytics through the slowdown

How pricing analytics can help businesses through the slowdown
For the first time in over three decades, Australian businesses are operating in a high inflation environment and need to think differently about many aspects of their operations, including setting prices.

With CPI inflation running close to 8%, business costs are rising sharply sometimes by much more than the 8% headline inflation rate.

Combined with higher borrowing costs, it is leading to an inevitable margin squeeze. But with businesses and consumers facing the same price pressures, it’s not always easy to simply pass through rising costs through increased prices. The impact of getting it wrong is potentially a lot higher.

This is where predictive analysis and demand forecasting can help.

A company’s past sales data, including prices, volumes, promotions and competitors’ pricing and promotions provides a wealth of insights that can be used to generate a predictive decision-making tool.

An accurate model of the price-volume trade-off

Collecting historical data is the first step is to enable analysis to look for correlations and common features of different sales volumes. Businesses can see how pricing, promotion, seasonality, competitor actions, and other external factors (ice cream sales increase in hot weather, for instance) affect volumes.

This enables the development of a predictive model that prescribes what a decision maker should do to get a given result. This could be a standalone model or may simply involve ‘tweaking’ existing business planning systems to provide a more accurate output.

It allows the business run scenarios to understand, for instance, what the effect of a 10% price rise might be on volume, and to see how other variables might influence the result. What if they accompanied the price rise with some promotional activity? What if competitors also put their prices up by 10%, or just 5%?
Businesses will gain confidence in their understanding of the price-volume trade off and get a better idea of how they can manage profit margins. They can decide whether to seek higher volume at lower margins or higher margins at lower volumes.

Improving market position
The data also provides businesses with the opportunity to set prices to manage their market position and set themselves up to take advantage of an eventual rebound in business conditions. These are difficult decisions for business to make, but they can’t be avoided.

In the past, some businesses might have been fine making pricing decisions based on gut feel (although we would argue a data analytics approach will produce a better result), but conditions have changed and pricing strategies of the past won’t necessarily be so successful in the current environment.

By drawing on data and predictive analytics, businesses can be confident they’ll be making pricing decisions that will help them restore margins and trade profitably through the current economic challenges.