Introduction
Most brands include a selection of sub-brand names. Examples are Suave and Suave Naturals shampoo; Coke, Diet Coke and Coke Zero; Colgate and Colgate Total. The main reason to have sub-brands is to cover market needs with appropriate variety. The sub-brand name (e.g. often adding words like Diet, Extra, Lite, Premium) signals a functional difference as well as the similarity to the other sub-brands, and capitalises on the recognition of the overall brand name. Sub-brands usually embody some feature intended to differentiate one sub-brand from the others in the range, and attract new users. A basic question is, the extent to which buyers of one sub-brand also buy others sold under the same parent name. If many buyers of one also buy the other, the sub-brands are not expanding the overall brand’s penetration as much as they could be. Therefore, we wish to know two things:
- Do sub-brands show high rates of purchase duplication, and if so how much?
- If sub-brands have high purchase duplication, how much does this reduce their combined actual penetration (which is effectively the penetration for the brand as a whole).
Question 1. Purchase Duplication of sub-brands
The term purchase duplication means the extent to which buyers appear in both brand’s buyer bases (hence, the buyers are ‘duplicated’). Another term for the same phenomena is cross-purchasing. An example of purchase duplication: 35% of the buyers of A also bought B over the course of a year.
We first examine whether there is more, or less, purchase duplication between sub-brands such as, for example, Colgate and Colgate Total than there is between toothpaste brands generally. If there is less duplication, it would indicate that the sub-brands are rather differentiated from each other – buyers of one are less likely to buy the other. In turn, this means that they are each appealing to different buyers and are thereby expanding the brand’s total penetration base. Conversely, if there is heightened purchase duplication between the sub-brands it strongly suggests that they are actually more substitutable with each other than with the rest of the market. Their common brand name is trumping whatever functional difference they possess; and they may well be excessively cannibalizing each other.
Analysis Method: Duplication
We examined 25 sub-brands in a variety of consumer goods categories. Our analysis method was straightforward:
- We selected brands and their sub-brands in a range of categories in the UK and US.
- We calculated the penetration and purchase duplications for all the sub-brands.
- We calculated the ‘Purchase Duplication Coefficient’ also known as the ‘D coefficient’ for each category, and between the sub-brands. The D coefficient is an index of the extent to which buyers of one brand also buy another. The higher the D, the greater is the extent of cross-brand purchasing.
- We compared the D coefficients between the sub-brands in each category with the D for the market generally. This controls for the fact that some categories simply show more purchase duplication than others.
Duplication: Results
Our results show that a brand’s sub-brands generally show high levels of purchase duplication between each other. On average, the rate of purchase duplication between sub-brands is 76% higher than the general rate of duplication in their category. The maximum was 263% and the minimum was -9%. Full results are shown in the Table on page 3. The result suggests that despite marketers’ attempts to create sub-brands that are differentiated from others in the range, their common brand name does make them frequently substituted with each other.
Next, we see the extent of duplication is far stronger for some sub-brands than others. We speculate this reflects the extent to which the sub-brands are functionally different to each other. For example, the sub-brands with the highest level of extra duplication, Gourmet Gold and Gourmet Solitaire cat food, are barely distinguishable from each other; sold in the same small, almost identical-looking, 85g cans. Conversely, several laundry detergent sub-brands sold under the Persil name have slightly lower purchase duplication with each other than exists in their category generally. This could be due to them having a more meaningful functional difference in terms of pack size and formulation (the reason might have been that they are distributed in different retailers, but a check confirmed this was not the case). That all said, on average, the results show that if you launch an additional sub-brand, it is very likely it will certainly appeal to buyers who already buy your other sub-brands sold under the same name.
Question 2. Impact on the combined penetration of the sub-brands
The second step was to calculate the combined penetration of the sub-brands. We calculated this empirically from household panel data, and using a formula. Both produced the same results.
The formula for the calculation is, using an example of two sub-brands A and B:
Combined Actual Penetration AB = Penetration A + Penetration B – (Penetration A * Penetration B * D).
D in this formula is the Duplication coefficient.
Across our sample of 25 pairs or groups of sub-brands, the combined actual penetration was on average 83% of the simple sum of each sub-brand’s penetration. So for example, if sub-brand A has a penetration of 10%, and sub-brand B has a penetration of 10%, their actual combined penetration is on average (20% x 83%) = 16.6%. So certainly there is some combined penetration loss due to one being substituted for the other, but the sub-brands do add penetration for the brand overall. In actual fact, the figure of 83% for sub-brands is not dramatically different to what it is for brands generally. On average, if we take any pair of rival brands in a category their combined penetration is 89% of the simple sum of their penetrations.
The next finding is that the combined actual penetration is lower when the sub-brands themselves are bigger. For example, for two sub-brands each with 20% penetration and a typical D coefficient of 2.5, their combined actual penetration averages 75% of the simple sum of each’s penetration (i.e., it is 30% instead of 20+20=40%).
Summary
Sub-brands do show high rates of purchase duplication on average. This suggests they are frequently substituted for each other and appeal to similar users, rather than to unique or different user groups. However, even with that higher substitution, sub-brands do add penetration to the brand as a whole: on average, 83% of their summed penetrations. A useful benchmark for brand portfolio management is therefore: two sub-brands should have an actual combined penetration of at least 80% of their simple summed penetrations. If they are both large sub-brands, it should be at least 75%.
More Institute research will extend these initial findings. There is much more to do. First, we only examined successful sub-brands, the pattern might be different for sub-brands that failed. Further investigation will go back to look at sub-brand launches and examine if the penetration of the rest of the brand dropped as the new sub-brand grew. Third, we will examine more categories and countries. The results will help us better understand brand portfolio management.
Technical note:
The D coefficient is (average duplication / average penetration). A higher D between say, brand 1 and 2 means means a higher proportion of each brand’s buyers also buy the other. Thanks to Kantar and IRI for data.