Transforming your syndicated data into business insight
Many people are familiar with the analysis known as a volume decomposition (or due-to) that uses POS data. This allows you to explain a change in sales and attribute gains and losses to specific business drivers like distribution, pricing, trade promotion and some other things. We have a series of posts on this, starting with […]
This is the sixth and final post in my series on quantifying the impact of business drivers on sales volume. The first post in the series explains more about when you would want to do an analysis like this. A volume decomposition analysis allows you to explain why your volume changed by allocating the total […]
This is the fifth in a series of posts on quantifying the impact of business drivers on sales volume. Please review these posts first to get more context: Part 1 – Overview of this very useful analytical technique that helps answer the question Why did our volume change? Part 2 – Impact of Distribution Part […]
This is the fourth in a series of posts on quantifying the impact of business drivers on sales volume. Please review these posts first to get more context: Part 1 – Overview of this very useful analytical technique that helps answer the question Why did our volume change? Part 2 – Impact of Distribution Part […]
Has this happened to you? Sales of your brand are down vs. the same period last year and management wants to know why. Sales is saying it’s because there is less advertising this year but Marketing is saying it’s because you’ve lost distribution and the retail price and merchandising are not as competitive. Another, more […]
Elasticity is a key concept when determining how much a change in a business driver results in a change in volume. For simplicity, you multiply the % change in the driver times the elasticity to get the % change in volume. (The formula for applying elasticity can be more complex, especially for pricing, but this […]
