Most comprehensive measure of distribution, accounting for both the %ACV Distribution (reach) and Average # of Items Carried (depth, sometimes abbreviated as AIC). TDP is often available right on your database but it can be calculated for a brand (or category) by summing the %ACV Distribution of the individual items that make up the brand (or category). Example: Say Brands A and B both have 200 TDPs. If Brand A is in 50% ACV Distribution and has 4 AIC and Brand B is in 20% ACV Distribution but has 10 AIC, then Brand A is distributed more broadly but Brand B has deeper distribution in the fewer places where they are.

Learn more in this article:

Total Distribution Points: Master of All Distribution Measures

Hello,

I was wondering if it is possible to calculate item weekly average $ Sales Per MM ACV for a category. I would like to use the category avg. as a benchmark when I’m charting new item weekly $ Sales Per MM ACV. The issue is that I am comparing apples and oranges. The category weekly $ Sales Per MM ACV figure is much higher than any 1 item weekly $ Sales Per MM ACV figure. Is it possible to get an apples to apples comparison?

Thank You,

Joe

Hi Joe, In your database, the $ Sales per MM ACV for the category is for all items combined. In other words, its the velocity for the entire category, not the velocity for the average item in the category. As far as I know, there is no database measure for average item velocity but you could calculate that yourself to establish a benchmark. You might want to exclude items with very low distribution because sometimes their velocity estimates can be a little funky.

How do you interpret the TDP of 200?

For example, the %ACV of 50%, you would interpret as “Brand A is carried in 50% of the stores in the market”

Thanks for your question!

First off, on your % ACV example, the interpretation would more precisely be “Brand A is selling in 50% of the market ACV”. That may or may not translate into 50% of the stores.

TDP is hard to put into a comparable, interpretive sentence because you can calculate TDP across markets, products and over time. And, since it’s not bounded by 0% and 100%, there’s no intuitive feel for what the absolute number indicates.

Using your example, I would say: “In this market, the sum of % ACV across all Brand A’s UPC’s is 200”.

But I would never put that sentence in a presentation or report because I don’t use absolute values for TDP. Instead, I report how it changes over time (I use % change versus year ago), turn it into an average items number which is more intuitive, or index it so I don’t have to show the absolute value. Then if I think people aren’t familiar with the measure, I add a footnote with the definition of TDP: “TDP is the sum of % ACV across items over time”.

What does Base $ per TDP tell you?? and if the output shows a negative % change- what should I take from that?

Thank you!

Hi Julie,

Base $/TDP is one type of velocity measure (velocity is also known as sales rate). Velocity measures tell you how well you are selling, adjusting for distribution. If you aren’t familiar with velocity as a concept, I suggest you read some of the articles on our sight to address this measure.

In this case, your numerator is base dollars. Base dollars is an estimate of your sales without the incremental impacts of trade promotion. So a negative trend for this measure would suggest declines in your base business where your product is available – not something anyone likes to see in their data. What causes base dollar declines? Everyday price increases, competitive activity, reduced consumer promotion, and many other factors.

However, it’s important to remember that even though velocity measures adjust for distribution, that doesn’t mean they aren’t impacted by distribution changes. If you increase your distribution (a good thing) but your velocity in your new accounts is weaker than your velocity was in your established account, you overall velocity will go down. So when you investigate this trend, be sure you not only look into what might be impacting the numerator (base dollars) but also investigate trends in the denominator (TDP).

Great information. I understand TDP is additive. Trying to understand this better. I pulled TDP for a manufacturer in 27 different retailers. I also created a aggregate total for the 27 retailers. The TDP for the aggregate was not a sum of the aggregate (like dollars was summed). I didn’t expect that. It isn’t a straight average either. Wondering what it represents? TDP reach for the 27 are as follows but the aggregate value provided by Nielsen AOD data pull was 629.

668

338

517

437

684

328

613

1,090

343

353

365

595

1,048

682

497

364

393

849

569

741

314

779

674

583

636

281

1,184

Thanks for the question! TDP is additive across products but only

withina market, not across markets. TDP for the aggregate of markets is like a weighted average across the markets, which is what the data you have looks like. Fortunately AOD does this calculation for you – in the older systems there was no way of knowing the true TDPs of an aggregate that was not already in the database. If you want to compare the 27 retailers to each other or to their aggregate you should do an index of each retailer’s TDPs vs. the aggregate. So, for example, the first retailer in your sample data would have an index of 106 (668/629 * 100) and the second retailer would have index of 54 (338/629 * 100). Saying that Retailer 1 has 6%moreTDPs than the average and Retailer 2 has 46% (1 – 54)fewerTDPs than the average should make sense to most audiences.Hope that helps!

I didnt get this post completely. What is AIC?

AIC is the abbreviation for “average items carried.” Other terms used that mean the same thing are: average items selling, average items, average number of items. Keep in mind that this measure (whatever you call it) is based on items that actually scan. So technically, “average items carried” is a bit misleading since a retailer can carry items on the shelf that do not sell in every store every week.

It is calculated for a brand by summing the %ACV Distribution of the individual items and dividing by the % ACV Distribution of the brand?

Now in the example above; 50*4 and 20*10=200. I am multiplying it here where is division?

Sorry but please elaborate.

Yes, AIC (average items carried) is calculated by summing the %ACV f the individual items and dividing by the distribution of the total brand. In the example, there are 2 different brands both with 200 TDPs. I’m just showing that one brand has much better %ACV (50 vs. 20) while the other has more items carried (10 vs. 4). The division comes in when calculating AIC since that is not always available as a fact on all databases. %ACV for items and brands is available so sometimes you have to calculate AIC.

Hope that helps!

Does the number of facings of any given SKU have anything to do with the calculation of Points of Distribution?

The number of facings is usually closely related to the measure “average items carried” (AIC). Keep in mind that you can’t really know facings unless there is a comprehensive audit where people actually go into stores and count the number of facings. A small number of companies do get this information but usually not more often than once a year – it’s pretty expensive to do a national audit. Average items carried is based on the items

actually scanningin a store and is the closest surrogate for facings. See this post on the relationship between TDP, average items carried and %ACV.Hope this helps!

Hi Robin,

I understand the TDP calculation. But lets say you have SKU level weekly data from Nielsen, for that TDP will be same as %ACV. But if you were to aggregate the 4 weeks of data at SKU level, TDP will be sum of %ACV for those 4 weeks. I know you can aggregate for Brand, I was not sure if you can aggregate it at SKU level across weeks.

Can you clarify this?

You are correct that you can aggregate across items to get brand TDPs or even add brands to get to category TDPs. I usually do not aggregate TDPs (same as %ACV at weekly item level) across weeks even for items. As far as I know, almost all databases have both weekly and 4-week periods available so you should be able to pull TDPs for the 4-week period instead of adding across the 4 weeks. Here’s an example: Let’s say an item has the following TDPs for 4 weeks – 54, 49, 52, 52. The sum of that would be 207, which is kind of difficult to interpret. If you pull TDPs for that same 4-week period you would probably get something in the range of 55-60. This is because during the 4-week period there is more opportunity for the item to scan than during any individual week. Sometimes the ACV or TDP for periods longer than one week is called “reach.” For longer periods there is sometimes a measure called “average weekly %ACV” which, in this example, would be 51.75 (essentially the average of the 4 weeks). Hope this helps!