What you will need:
ePOS Sell-out data is the main source used for price elasticity analyses. This data contains the selling price (paid by the consumer) and the volume of sales. Ideally, this data should be as granular as possible. Getting just the total volume and average price from 20 stores is less valuable than receiving the data from every single store separately; this will give you more data points to use.
Because price elasticity analyses typically involve a (regression) model to create a ‘best-fit’ curve, those analyses will benefit from more (historic) data points. A decent amount of data is essential to start with, otherwise, the modeling process won’t be possible or yield usable results.
The data points should also be as close to the subject you are trying to analyze as possible, but even data that is adjacent to your subject is also usable in some cases.
Let’s take an example: your material costs have gone up and you are wondering if you can increase the price of product X without harming your profits. Sales data on product X would be very valuable, but also comparable products that may have declined or increased in price. The overall average price of the category is also important data to include; for example, is there overall price erosion or not?
Other data and KPIs could be useful to make sure that you are attributing the right effect to price. For example, you should isolate regular price effects from promotion price effects, if possible, as promotion prices are temporary and are supported by various marketing efforts which are not always the case with permanent (MSRP) price changes.
A typical analysis dashboard
You have decided on the analysis framework, collected and harmonized the data and are now ready to design your dashboards and overviews. So, what are some of the best-in-class dashboards on price elasticity that you could use to analyze the situation and determine actions to take?
As outlined in the previous blog in this series, you start at a high level on brand or category and then work down into segments and single SKUs. The following examples are two important anchor dashboards for price elasticity that specifically serve that purpose.
These graphs are particularly useful in your analysis to evaluate a price change for a certain SKU. However, price elasticity is not the only thing you need to look at when you make a price decision. You will also need to evaluate where this product will end up in the (retailer) assortment. For instance, you might increase your performance on the single SKU you analyzed, but it may cannibalize one of your other products!
Price elasticity in a vacuum is interesting, but to make good decisions you need to investigate other aspects of the product as well.
In our next blog, we will look at Pricing Analytics and how to use them to grow your business. Subscribe now to receive notifications for the next blog in this informative Master Class series.