You probably consider dollars the most important measure and it IS the bottom line. But the number one driver of dollar sales is distribution. After all, shoppers cannot buy something that’s not in the store!
Used properly, % ACV Distribution will give you the answer to crucial business questions like:
 Are there any retailers that are not carrying our #1 item?
 Are we meeting the distribution goals we set for our new product? Which retailers are selling at least one of the new items?
 My broker is saying sales are down because we are losing distribution. How can I tell if this is true? What is really happening in the stores?
So what exactly does % ACV Distribution mean and how is it calculated?
% ACV Distribution is often just abbreviated “% ACV,” especially when talking about it verbally. It can generally be thought of as “% of stores selling,” but with stores weighted based on their size. In other words, you get more credit for being in larger stores than in smaller ones. The size of a store is based on annual sales of everything the store sells, called All Commodity Volume. When Nielsen and IRI calculate ACV, they don’t count things like pharmacy, lottery, and gasoline since not all stores have those features.
% ACV Distribution is calculated as the dollar value of stores in which a product has scanned in a geography divided by the dollar value of all the stores in that geography. Let’s repeat that: A product must scan in a store for it to count as being in distribution there. If it is on the shelf but does not sell or it is supposed to be there but is out of stock, it doesn’t count as being in distribution. In this picture, this retailer is out of stock on several items. Even though there are shelf tags for these items, in Nielsen and IRI, these products are not counted as “in distribution” because they won’t scan at the register.
Here is an example of how % ACV is calculated. Let’s say Anytown USA is made up of 3 retailers, as follows:
# of stores 
ACV $ 
% of stores 
% ACV $ 

Fun Foods 
60 
$200MM 
30% 
50% 
Happy Grocery 
40 
$40MM 
20% 
10% 
Smart Stores 
100 
$160MM 
50% 
40% 
Total Anytown USA 
200 
$400MM 
100% 
100% 
If Brand A has scanned in Fun Foods and Smart Stores, then it is in 80% of the stores (30+50), but has 90% ACV Distribution (50+40).
So just remember, % ACV is like % of stores selling but you get more credit for big stores than small ones.
Want more tips and watchouts for using % ACV Distribution? Read Part 2 here.
Hi Robin,
My question might sound silly, but why the product being “scanned” an important component in %ACV Distribution calculation? For e.g., in the table above, say for some reason the Brand A didn’t also move in all of the 60 stores of Fun Foods and that if we know for a fact that it exists in those stores in that timeperiod (not out of stock) — does that mean now the %ACV distribution is only 40% (160/400)?
In this scenario, one can’t attribute the lack of movement of Brand A in Fun Foods to lack of distribution, can they?
I’m of the opinion the very presence of the product in the store at a given point in time should constitute as distribution (adjusting for store size).
I suppose there is a strong reason for the way it is calculated. I’d appreciate if you can explain what I am missing.
Best regards.
There is lots of confusion around authorization vs. distribution and how IRI/Nielsen measure them. A product is “authorized” when a retailer agrees to sell it. Authorizations are a key measure when tracking a new product introduction and Sales is often evaluated on how many retail customers authorize a new item. But…just because a retail has authorized a new item it doesn’t mean that every store in the chain will stock and sell that item. You are correct that technically speaking, an item is “in distribution” in a given store if there is a space on the shelf and a shelf tag for it. The only way to know if there is space and a shelf tag would be to audit every single store, which is not feasible. There are over 30,000 grocery stores alone in the US and the cost to send auditors to every store and record every shelf tag would obviously be prohibitive. Therefore, both IRI and Nielsen use the fact that an item scanned as proof that it is in distribution. Most users of the data realize that the distribution numbers can be understated, especially for slowermoving items and categories that are not purchased very often. Some of the very big CPG manufacturers do actually pay for annual or biannual shelf audits of their specific categories, but even those only send auditors into about 10% of all stores.
Hope this helps!
Question please…If I have a company that grew 7.2% to almost $20mm, but the competition grew 2 points more at 9.3% ($141,907,715) how do they arrive at a $208K share loss?
Hmmm…the numbers you refer to in the question are a bit confusing. First, a “share loss” would be in terms of points, not a dollar amount. So something like “share was down 1.5 points” So I’m not sure what you mean by “a $208K share loss.” It is possible for a brand to grow sales but still lose share – that happens when the category is growing faster than the brand. In this example, you don’t say what the category growth rate is, so I can’t tell if either company gained or lost share. If category growth is less than 7.2% then both gained share. If category growth is greater than 9.3% then both lost share. If category growth is something in between 7.2% and 9.3%, then the competition gained share and your company lost share. There is no feasible scenario where your company could gain share while the competition lost share, given the numbers in your example.
Hi Robin
What happens when Brand A is scanned in only some of the Fun Foods stores, say in around 30 of them? In such a case, will the % ACV still remain the same or will it be calculated based on each individual store size?
If Brand A is scanned in fewer Fun Foods stores, that will lower the % ACV. The % ACV will be recalculated based on individual ACV of each Fun Foods store. So if the 30 stores where it lost distribution were bigger than average, then % ACV will fall more than if the 30 stores where it lost distribution were smaller than average.
Thanks for the clarification!
This doesn’t make sense to me.. Can you clarify doing this scenario on the same table above?
As Robin states in her post, if Brand A scans in Fun Foods and Smart Stores, then Brand A is in 80% of the stores (30+50) but has 90% ACV Weighted Distribution (50+40).
OK, now let’s say Fun Foods discontinues Brand A. If that happens Brand A is in 50% of stores and has 40% ACV Wtd Distribution. But if, instead, it’s Smart Stores that discontinues Brand A, then Brand A will be in 30% of stores and have 50% ACV Wtd Distribution. Even though Smart Stores has more stores, they are smaller (on average) than Fun Foods stores. So distribution changes at Smart Stores have a lesser impact on Brand A’s ACV Wtd Distribution.
You can calculate average store size by dividing Total ACV by Number of Stores.
how does %ACV differ form classic Weighted Distribution (%) metric calculated on sales value?
I think we are talking about the same thing. Depending on your database, it may be called Avg Wtd ACV or ACV Distribution (or some other variation). There is a difference if the word “Weekly” appears in the fact name, which is a topic for another post!
%ACV is similar to %WD to tell about the quality of distribution. The key difference, however, is that %WD is based on category sales comparison while % ACV is based on, as the name suggest, all commodity value ie. total sales of the store.
Although there are some nuances to measuring distribution, %ACV is definitely the most commonly used measure. As far as I know, not every database has %WD as a measure so it would have to be calculated whereas everybody has access to %ACV. Please confirm that “%WD” stands for “% weighted distribution.” That is a valid measure but I have not seen it used that often at manufacturers or with retailers in selling stories in the US.
I need further explanation for the following:
% ACV Distribution is calculated as the dollar value of stores in which a product has scanned in a geography divided by the dollar value of all the stores in that geography.
What exactly is this dollar value? The price of all Brand A items, or the price of the Brand A items that were scanned?
If Happy Grocery did not sell or scan any Brand A items, then where is it’s ACV $ from?
In any case, it seems like with ACV information, we can know which retailers have sold Brand A, not necessarily which particular stores.
Dear Susmita,
The “dollar value” referred to here is the total dollar sales for the store ACROSS ALL PRODUCTS. That is the definition of store ACV. This number is independent of Brand A distribution – it’s a total store number.
So % ACV for Brand A = Total dollar sales across all products for stores where Brand A is scanning DIVIDED BY the total dollars sales across all products for all the stores in that geography.
You might find this article helpful:
All About ACV
This is easily explained by the following. If a retailer only had 2 stores. the first sold £8m of goods and the second store sold £2m of goods. If your product was listed/ranged on the £8m store your product would be in 80% ACV despite being in 50% of stores
If a product, lets say cookies, sells only at WalMart and grocery stores, does the ACV measure include only ACV of WalMart and grocery stores, or does it include all potential markets where there is currently no distribution (i.e. drug stores, Target, etc)?
The % ACV Distribution measure includes all potential stores in the denominator but only the stores where the product has actually sold in the numerator. So if a product is in Walmart and Grocery and you are looking at %ACV in the total market (MULO or xAOC), then %ACV probably won’t be over 80% – and that’s if it’s in full distribution in those 2 channels.
Dear Robin,
Your post helped a lot to understand %ACV. I have a quick question, and hope I will get the clarification –
Question: Suppose there are 4 channels in a market. We know Maximum Weighted Distribution for all these three channels say 99, 98 & 14. In this case can we calculate Maximum Weighted Distribution for the Market. if yes please let me know how?
Thanks in Advance
So it looks like there is no distribution in the 4th channel. Unfortunately there is no easy way to get to a market total from the channels in that market unless you know the relative size of the channels. If your database has ACV $ as a measure then you could do it, otherwise you can’t. It is not that common for you to have the channels but not the total market! It is probably more common to have the total market without the channel detail.
Yes Robin, we can assume there is no distribution in 4th channel. In the database, we have facts like “$ Value Sales” and “Count of Stores in Universe”, and “Distribution – Number of Stores” etc. for each channels. So can this help for the aggregation?
One more query: if I am correct, maximum weighted distribution can be defined as highest distribution across the database. So, can we say maximum weighted distribution for the market in above case will be 99 (max. of 99, 98 & 14)?
Thanks once again for quick response….
I’m not sure you can calculate the total market distribution from the channel distribution using the facts you mention. Count of stores and number of stores do not help in this case – you need something about ACV (all commodity volume). I am not familiar with the fact “$ Value Sales” but maybe that is the same thing as ACV here in the US.
No, you cannot say that the maximum weighted distribution for the market is 99! In fact we know that maximum distribution for the market must be somethig less than 99 since it will be a weighted average of the distribution in the 3 channels (plus the 0 in the 4th channel).
What is the fact of scanning product in store? Visual control on the shelf or sell out from store 1 item?
For scan data, distribution is based on whether the item sold. Whether it is physically on the shelf does not factor into the scan metrics. That’s because the distribution measure is completely passive – it’s simply derived from the data, not requiring any human auditing.
OK – I understand ACV – but a new metric has started appearing on reports: ACV Reach – what is this and how is it measured
There are now a whole bunch of facts available in Nielsen with the word “Reach” in the name. (I think in IRI they have the word “Max” in the name.) All of them have to do with ACV or are derived from ACV. You may have noticed the following 2 things about the Reach facts: 1. They are always bigger than the corresponding fact without Reach in the name (except for a single week, when they are the same and 2. the values of Reach facts get larger the longer the period.
For %ACV Reach, it’s the %ACV where the product was sold AT ALL during the period. The regular %ACV is the average weekly %ACV where the product sold. So…you may see %ACV for an item during a 12week period at 72% but %ACV Reach at 81%. That means that in an average individual week during that period the item sold in 72% but over the entire 12week period, the item sold in 81%. The more weeks in the period, the higher the difference will be between the Reach fact and it’s regular counterpart. The facts will also be more different when the purchase cycle for the product is longer (people do not buy the product as often).
Hope that helps!