We’ve had several questions over the last few months regarding some facts that people are starting to notice are available in their Nielsen, IRI and/or SPINS databases. The names are very similar, but it’s not obvious how the measures are different or when you’d want to use one or the other. (With apologies to Homer Simpson, who probably never had to use a Nielsen or IRI database!)
Since these potentially confusing facts are all related to or derived from ACV, you may want to read these previous posts that talk about ACV and other Distribution measures:
- All About ACV
- The 2 Most Important Measure %ACV Distribution, Part 1 and Part 2
- Total Distribution Points: Master of All Distribution Measures
Now that you’re an expert on ACV, Average Items and Total Distribution Points (TDP), I’ll get to the point of this post!
First of all, as with lots of terminology in the world of CPG data, there are differences between the different data suppliers. If you have access to Nielsen data, you may have seen many facts with the word “Reach” in the name. If, however, you are an IRI client, then the equivalent term in fact names is “Max.” Note that if you are a SPINS client and get any data for the Conventional channel then you will also see “Max” in some fact names (because IRI actually supplies the Conventional data for SPINS). You may see the word “Avg Weekly” in front of distribution measures from all 3 suppliers. Warning: The terminology in this post may not be exactly correct here for all suppliers, so check your database for what’s there and ask your client service rep if you have specific questions about your database.
2 Versions of Each Measure
Let’s look at some real data for the measure “%ACV” for one brand in one retailer. Here’s data for 4 different periods – 1-week, 4-week, 12-week and 52-week:
Brand A in Simon’s Supermarkets
Comparison of %ACV Measures
Periods ending 10/28/17
Things to notice about the numbers:
- For a single week, the 2 measures are always the same – in this case 78.
- For all periods longer than 1 week, the measure on the right is larger than the one on the left – for 4-weeks 82 vs. 76, for 12-weeks it’s 89 vs. 81 and for 52-weeks it’s 93 vs. 83.
- The values of the measure on the left are all pretty similar – ranging between 78 and 83.
- The measure on the right gets bigger the longer the period – 78 for 1-week up to 93 for 52-weeks.
Using the 52-week period as an example, the key concept here is:
So over the course of the whole year, Brand A sold, on average, in 83% of Simon’s Supermarkets in a week but sold in 93% of Simon’s Supermarkets at some point during the year.
Here’s a very extreme example: Say you’re looking at a 52-week period. If the product sold in 20% of the ACV during the first week of the period, in 10% the 2nd week, 5% third week and then 0 the other 49 weeks then Max ACV for the product would be 20 but average weekly ACV would only be 0.7 (= (20+10+5)/52 wks).
Which to Use When?
This basically depends on a combination of:
- The purchase cycle for the product
- Where the product is in it’s life cycle – new, stable, declining
As we saw in the graph above, the longer the period gets, the more different the 2 measures will be. That means if a product has a long purchase cycle then the avg weekly and Max ACV will be more different – it’s possible for an item to sit on the shelf and not sell in every single week if people don’t buy the category that often. This is less of an issue for refrigerated products with a shorter shelf life and more of an issue for things like cleaning products that people may only buy a few times a year.
If a product is steadily gaining or losing distribution over a period, then be careful about which measure you use! Using Max would be better for a new product that had much lower distribution at the beginning than at the the end of a period. But looking at Max for a product that has been discontinued or delisted would be artificially high since distribution would be much lower at the end than at the start of the period.
Same Concept for Other Distribution Measures
Since many other measures are derived from ACV, they also have 2 different versions. Here are examples for Avg # Items and TDPs:
Brand A in Simon’s Supermarkets
Periods ending 10/28/17
These same principles hold for Avg # Items and TDPs:
- For a single week, the 2 types of measures are always the same
- For all periods longer than 1 week, the measure on the right is larger than the one on the left
- The values of the measure on the left are much closer together than those on the right
- The measure on the right clearly increases the longer the period
Here’s how to describe what’s happening with Avg # Items over the last year using the data above: On average over the last year, Simon’s Supermarkets sold between 15 and 16 items every week. Between 19 and 20 items sold at Simon’s Supermarkets sold at some point during the last year.
I hope this helps to clear up the differences between the versions of the distribution measures.
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MK says
Very interesting article as always, thanks a lot for the inspiration!
One thing I don’t get though: while it’s perfectly clear that max ACV is overstated for declining items I can’t wrap my head around why it would understate new products’ ACV. Suppose a 4 week period with 10%, 10%, 30% and 30% stores selling product ‘x’ in the respective weeks.
– With Avg. ACV: 10+10+30+30/4= 20
– With Max ACV: 30% (as that’s the maximum ACV during the period) –> so overstating, too
What do I miss?
And also: how is it possible that Avg. ACV is higher for the 12 vs the 4 week period? How can an average of 81% of stores sell an item during every week for the last 12 weeks, while only 76% sell that item for every week during the last 4 weeks?
Thanks, Sincerly,
MK
Robin Simon says
Thanks for the questions! In re-reading the part of the post regarding new and delisted products, it was not written correctly. I fixed it so it makes more sense now.
In response to your 2nd question…there is no specific pattern that happens between time periods for avg weekly ACV. In the example you mention, the most recent 4 weeks could be 77-76-76-75 (avg = 76%) but the week could be several weeks in the 80s and then the most recent 4 weeks that same 77-76-76-75 to average out to 81% for the entire 12 weeks.
Nirmal CHANDRAHAS says
Hi
Thank you for these wonderful articles clarifying CPG concepts
I had one doubt on the measurement of distribution
Would %Numeric Distribution for a product, in a certain period, be measured based on % of stores where the product was sold in that period or simply based on the % of stores carrying (holding) the product during the measurement period?
Would the same logic apply to %weighted distribution?
Thanks again
Nirmal
Robin Simon says
Any distribution measures (weighted or not) are based on the stores where the product actually sold. The only way Nielsen/IRI knows if the product is “in distribution” is if it scans. In order for them to know what is carried, there would have to be audits (or some automated way) to see every single shelf in the store to account for items that did not scan in a given week. An item may not scan because either it is out of stick or nobody bought it.