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Suppose that I have 3 soda makers and I want to know their share of market. I am just given the total sales in a period (ex. this year) for all the soda makers and the total sales per soda maker. However one of the data points register very low sales and thus if I perform a simple average I will get a significant decrease of the share of market for that given soda maker. So I was wondering in my case how should I perform a weighted average (or if I need to perform something else) in order to avoid that data point that is skewing my data. As an example imagine I have the following data:

soda maker   Sales_in_store_1  Sales_in_store_2   Sales_in_store_3
coke          $500k                 $550k            $4k
pepsi         $400k                 $450k            $4k
bigcola       $100k                 $0               $2k

in this case I have a total sales of $2,010,000 and using a simple average I would get a share of market of approx 52%,42% and 5% for coke, pepsi and bigcola respectively. However the low sales volume in store 3 is skewing my data. My question is, should I use a weighted average to calculate a more realistic share of market? and if so, How should I do it? (I am confusing myself with which should be my weights)

Any insight that you could provide me I will appreciate it

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This was better conveyed as a comment but alas I can't.

How is this "skewing" your data? What is your definition of significant decrease?

If you exclude Store 3, you get 52.5%, 42.5% and 5.0% respectively, up to a single decimal point.

If you include it, you get 52.4%, 42.5% and 5.1% respectively, which I would hardly call significant (about 0.2% decrease for coke, about 2% increase for bigcola). This might be subjective though.

Anyway, it really doesn't matter where those sales were done. You might move half of Store 1 sales onto Store 3 and get exactly the same market share. Which makes sense: the (overall) market share is defined by the comparison of the total sales.

(If I worked in bigcola, though, I would seriously investigate what's happening at Store 2...)

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  • $\begingroup$ Thanks @polettix, I explained myself incorrectly saying "skewing" my data. Now that I think about it is that it is not representative of the percentage of market share that I want to study. by significant decrease I meant that because I have a low amount of pepsi sales in store 3 this might not be as representative as sales from store 2, so I was wondering if maybe applying a weighted mean I could decrease the significance of store 3 with respect to sales. However I don't know which would be my weights in this case $\endgroup$ – Oliver Sep 5 at 0:45
  • $\begingroup$ @Oliver to be honest I still don't get what you are after, the fact that Store 3 has low numbers is already by itself decreasing its importance with respect to the other places - in fact, its impact on the market share calculation is at most in the first decimal digit of the percentages. Isn't this sufficient? $\endgroup$ – polettix Sep 5 at 5:48
  • $\begingroup$ what I am trying to accomplish is to infer the share of market of a population by just analyzing 3 stores (what I mean is imagine that in Texas there are 1000 convenience stores, however I only own 3 of them and I want an estimate of specific brand share of market by just analyzing the sells of that brand in my 3 stores). I know that just using 3 stores is not something accurate but that's all I got. If you know another method or could reccomend me to do something else I will appreciate it. $\endgroup$ – Oliver Sep 5 at 14:14
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The average is telling you exactly what you want, the mean share for each soda maker. You could use a weighted average to account for the total customer number for each store, since it is expected that smaller stores will sell less products. However, I think it would be more informative for you to use the total (sum) share for each soda maker.

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