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What would be the possible reason of revenue gap of different stores?

This is what I found in a casebook. The answer key is a little bit confusing so I would like to know your ideas.

Q: Why the average annual revenue of stores in city is higher than of the ones in suburban area? The store is selling luxury product.

Answer key: Traffic, store size, target customer(household income), product allocation, product price.

My question is:

1. It is weird... it is supposed that the store size will be larger in suburban area right? why this will have have a negative impact on suburban stores' revenue?

2. What will you answer this question? How will you organize your thought? Thanks!

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Top answer
Anonymous B
edited on Nov 23, 2018

Recap. Store in city vs. store in suburbs. Luxury stuff. Double-confirm with interviewer, likely departmental store.

Here is where I am slow. Might tend to use personal experience. Like Harrods. Harrods in London vs. Harrods outside London. Better if have real-life and existing comparison, like M&S in London vs. M&S outside London. LOL, but M&S = luxury?

I'd then identify 'branches'. In this case, branches like customers, etc. Drill down. Lol, better phrase than the generic 'segment', right :)  Who goes to Harrods? Tourists? Spend per customer? Higher salary for London means greater disposable income? Footfall? Think both ways, e.g. store in suburbs? Like Bicester Village? Am sure you can continue from here. 

What the experts on here say is spot on. If you have no personal experience from which to draw, then look at a variety of cases. This example should be under retail. Or luxury retail. So maybe look at insights from firms like Kantar Worldpanel? 

OK then, time for coffee :)

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Vlad
Coach
on Nov 23, 2018
McKinsey / Accenture Alum / Got all BIG3 offers / Harvard Business School

Hi,

Probably they meant the generic factors to look at.

I would look at the following:

1) Average check

  • Length of the check
  • Product mix in the check

Key check drivers:store format (space and assortment / price / product quality), promo & discounts, personal sales (fashion, electronics), loyalty programs, merchandising, stock availability, etc.

2) Number of customers

  • Traffic
  • Conversion - important in fashion and consumer electronics. less relevant for grocery

Key customer drivers: Location, Time opened, brand awareness, store format (space and assortment / price / product quality), external factors (parking, signage, etc), in-store experience (queues, look and feel, etc)

Best

Anonymous B
edited on Nov 23, 2018

Was just thinking... can even use the usual revenue = product volume * average price paid format.

Then, model each. Don't need to be like a complicated model or anything. E.g. Volume is a function of footfall, conversion, branding, time of year (funnily enough, like Black Friday - LOL!), etc. Price is a function of type of customer, spend per customer, disposable income, etc.

Anyhoo... back to Black Friday. Who's buying me a Christmas pressie? :) 

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