Copyright © 2017 CPGAnalytics101
Your brand doesn’t rank too high?
Try using Dollars per item selling - A type of velocity ranking in analytics
Let's look at a brand rank for Retailer X for the latest 24 weeks. Let's assume your product is BOB's 32oz. Right now it ranks 4th best selling out of 5 brands in all. That is fairly low, but also consider your brand has more limited distribution in the chain vs. other brands except for Crunchy 32oz. We can show this to the buyer at Retailer X as is, but it does not show the full picture, this is just topline.
I want to look at this further to see how our items under the Bob's 32oz brand is performing too. We can simply do an item rank too, but I can also use some calculations from this table to look at what our average $ per item selling is. Let's look at what the average # of items selling is. One of the basic calculations to get this (if not in the database as a measure) would be:
AIS = Brand TDP / Brand %ACV
Let's add in this column in the table below shown in blue. For the sake of the exercise, we will round up to nearest whole # and leave out the decimal.
The category sells an average of 14 items while some brands have more or less items selling in the category. Bob's 32oz has 2 items on average (1.5 but rounded up) selling in the category. Let's dissect this out some more. I want to see what the average dollars per item selling is. Let's add in another column to the right is AIS and calculate it.
The calculations for $ per item selling is:Avg $ per item selling =Brand $ / Avg # of items
Once we calculate $ per item selling, we can rank it and show how Bob's 32oz ranks as 2nd best-selling on a $ per item selling basis. This also helps show item/sku productivity where Bob's 32oz out-sells MOST other branded on a per sku basis. So from a brand rank Bob's 32oz ranks 4th, but on a per item selling basis, it ranks 2nd best-selling.
If all things remained constant (very hypothetical) and state that for each item selling, Bob's 32oz produces $513k, then by adding one more item could potentially make it #1 brand overall in sales based on a hypothetical "size of prize" factor. But again this has to do with other factors not measured e.g. velocity, promotional reliance & support, as well as pricing. See green box added in table below.
With adding in the last box in green above, Bob's 32oz is the only brand to reflect a change in sales because we applied the "1 more item added" factor to just Bob's 32oz only. All the other brands sales were carried over from the dollars column. To calculate Bob's 32oz hypothetical size of prize calculation we used the formula:
Opp $ with 1 more item =($ per item selling x 3)
We use 3 because we are adding one more item to its portfolio. It goes from the current # of items being 2 and adding one more to make it 3, then multiplying it out by the $ per item selling. Now again re-ranking on this factor, we see Bob's 32oz brand ranks # 1 in the category based on the hypothetical scenario. Bob's 32oz out ranks the current top selling brand by +$473k, and now we can say....
....From a $ per item selling, Bob's 32oz ranks #1....