Does my brand contribute more or less than its fair share of dollars relative to share of space? Analyze using POS Data.

Does my brand contribute more or less than its fair share of dollars relative to share of space?

The Share of Assortment vs. $ Share is also referred to as "Space to Sales", except our version is from POS data. Unless you are a buyer or an analyst for a retailer, most of the time you will not receive schematic input or have the lack of space planning software.

What we are essentially doing is looking at the products TDP (depth of distribution) relative to the products $ share of the category. We use TDP to calculate share of items or depth of items by dividing the products TDP into the category TDP to derive to a percent. Dollar share is derived in the same manner.

Let's assume your product is Bob's chips which is more of a regional brand since it has the least amount of distribution whereas all other brands are in the 90% range. So Bob's Chips is more like a regional brand trying to expand and grow in Retailer X, but the buyer is not convinced your brand deserves more facings or additional distribution. At the moment Bob's Chips ranks #4 (out of 5) in dollars from a standard brand in rank report. There are several analysis out there you could use to spin it, but in our example we will be using the Share of Assortment vs. $ Share report to relate how efficient Bob's Chips is, and how productive it can be with the allotted space it has on shelf vs. other brands.

Result:

Bob's Chips has a 17.5% share of category dollar using just 5.5% of the shelf space. This means Bob's Chips generates more than 3x the dollars relative to its share of space. This makes Bob's Chips an extremely efficient brand for the retailer. You can then state that Bob's Chips is under-spaced and should have more facings of its best-selling items in addition to increasing its breadth of distribution for the retailer. It is a proven brand performer.

The buyer might come back with saying that other brands are also under-spaced too and they rank higher than you. In this instance, you can state the differences in the indices. I mentioned earlier that Bob’s Chips sells more than 3x its dollars vs. its share of space. I simply calculated the (share of dollars / Share of items) x 100 to get an index number showing the relationship between the two factors. Bob’s Chips has a share over space index of 321 which is higher than any of the other brands under-spaced in the category. For example, Blue Chips ranks 2^nd best-selling brand and is under-spaced. But the $ Share over item index shows Blue Chips generates 2x the dollars vs. share of space while Bob’s does more than that and its share of the category is not too far behind Blue’s share, so we can help validate this point.

This is just one factor you can use among many other analysis out there that you can compile into a story and build a sales deck.

Calculations:

Share of items = (Products TDP / Category TDP)

$ Share = (Products dollars / Category Dollars) this should be a standard measure available to you in a database.

Share / item index = ($ share / share of items) x 100

See the example charts below.

 

 Whenever a brand or product has a higher share of items over $ share, it is over-spaced. When reversed, it is under-spaced. See Excel table below with the data.

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Why would a product’s Dollar Sales Velocity decrease if ACV Distribution increased?

Why would a product’s Dollar Sales Velocity decrease if ACV Distribution increased?

Measures referenced: Dollars per $MM ACV, %ACV

This is a scenario that can happen. The product could have gained breadth of distribution in a retailer that is less productive in moving the product off the shelf because they took in the product at a later time vs. retailers where the product has long established distribution, thus selling for a longer period of time and has had levels of promoted support to drive sales.

In our example, I am referencing sales velocity stated as Dollars per $MM ACV (“Dollars per Million”). This measures how fast a product is moving where it is in distribution or it is the Dollar sales of a product for each $1 million of annual ACV for stores selling the product. This is a standard velocity measure used in ranking reports compared across multiple markets. We can also use it for units and volume as well.

Conversely, it is also possible to see the opposite effect too. Sales velocity can increase while the product’s ACV distribution drops. The product may have lost distribution in a slow moving retailer while the remaining retailers the product has distribution left in may move the product faster off the shelf.

 One example could be if the product lost distribution in Kroger and the product did not secure new distribution anywhere else to compensate. Assuming the product has a large presence in Kroger, its distribution as well as its sales would definitely decline. But if the product maintains distribution among several dozen retail chains where it is highly trade driven and responds well to trade while not as frequently promoted in Kroger, then what is left are chains where the product moves quicker due to its trade or other promoted reliance. Of course this impact would not necessarily be seen right away. Our sales velocity might peak higher during the continuation cycle in Kroger due to the retailer running a closeout price in order to deplete their remaining inventory of the product. Once depleted and order cease, then we may begin to see the scenario play out.

However, over time, the product may regain that lost distribution elsewhere, and sales velocity will adjust accordingly. If running the data in Total US Food, then you would need to drill down to the retailer level to see where the changes are happening. However, you still might not be able to isolate the retailers because not all retailers are visible in either IRI of Nielsen due to lack of releasing data, exclusivity, or those not participating in the collective. In addition, there is a sizeable portion of wholesalers not always accounted for either. So if the product has a strong presence among wholesalers, then isolating the issue will be limited and rely on word of mouth from your sales force. 

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