Transforming your syndicated data into business insight
In my last post, I laid out how Nielsen/IRI define each promotion condition they measure. Today I’ll tackle the difference between promotion presence measures and promotion impact measures. Understanding this distinction will help you sort through the long list of promotion facts and avoid common errors. In brief, presence measures tell you how much and […]
Trade promotion evaluation is one of the primary reasons CPG companies buy IRI and Nielsen data. At 10-20% of gross sales, trade funds are a big investment for most manufacturers. And even companies that don’t have direct-to-consumer marketing will still often have retailer driven in-store merchandising. IRI and Nielsen databases can include literally hundreds of […]
We have already discussed 2 key measures relating to distribution: % ACV Distribution and Average Items Carried. For product aggregations above the item level, % ACV Distribution provides a measure of distribution breadth and Average Items Carries covers depth. But what if you want to have one measure that summarizes distribution, taking into account both […]
Learn why Average Items Carried is important in this previous post. Even though Average Items Carried is pretty straightforward, here are some questions (and answers!) that often come up when the measure is new to an organization. Can I add together Average Items Carried across periods or geographies? NO! It is a non-additive fact , since it is […]
As mentioned in a previous post, shoppers cannot buy something if it’s not in the store! That’s why having good distribution is so important to your business. What can you do to increase distribution when your brand is already in at least 90% ACV distribution? Let’s look at an example. Say there are 3 brands […]
If Average Items Carried (or Average Items Selling) is not available on your database, it is easy to calculate in Excel. It is just the sum of % ACV Distribution of all the items divided by the % ACV Distribution of the brand. Here is an example: Say a brand is made up of 4 […]
