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Market sizing

Hello all,

If I had to estimate the daily revenue of a nearby Starbucks store, I would look at the bottleneck (i.e number of cashiers) * max. number of customers served by 1 cashier (60 minutes / time to serve 1 customer (I'm assuming that the same cashier would collect payment, craft the customer's drink and serve it)) then adjust with peak & non-peak hrs and utilization rate for peak & non-peak (assuming a particular weekday). Then multiply with average ticket price.

Would you agree with the above solution?

And which bottleneck would be more reasonable? Number of seats or number of cashiers?.

Thanks

Hello all,

If I had to estimate the daily revenue of a nearby Starbucks store, I would look at the bottleneck (i.e number of cashiers) * max. number of customers served by 1 cashier (60 minutes / time to serve 1 customer (I'm assuming that the same cashier would collect payment, craft the customer's drink and serve it)) then adjust with peak & non-peak hrs and utilization rate for peak & non-peak (assuming a particular weekday). Then multiply with average ticket price.

Would you agree with the above solution?

And which bottleneck would be more reasonable? Number of seats or number of cashiers?.

Thanks

(edited)

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Hi,

Your approach is indeed a good one.

If you want to master your market sizing skills I suggest that you should focus on segmentations patterns. You can use the following segmentation for market sizes:

B2C:
- Demographics (Age, education, income, family size, race, gender, occupation, nationality)
- Behavioral (Purchasing behavior, customer journey stage, occasion & timing,
customer loyalty & interest, risk tolerance, user status)
- Psychographic (Lifestyle, personality traits, values, opinions, interests of consumers)
- Geographic (Geographical boundaries)

B2B:
- Company characteristics (Industry, company size, number of employees)
- Geography (Geographical boundaries)
- Purchasing Approach (Occasion & timing, customer capabilities, nature of existing relationship)
- Personal Characteristics (Loyalty, risk attitude, user status)

B2G:
- Demographics (Type of agency, size of budget, the amount of autonomy)
- Geographic (Geographical boundaries)
- Government Tier (Federal , State, Local, Quasi-governmental, International)
- Bid type (Closed, Open)

But sometimes you don’t need to segmentation. Here is an example of case that could be solved with high level top down approach - estimate the size of credit card market in the US:

In this case you should follow demand-driven approach to market sizing. By market size I would assume value of credit card debt in the U.S. (not the number of Credit Cards issued).

First of all you can start by outlying an algorithm which would consist of 3 big steps:

1. Total addressable market

X

2. Product penetration

X

3. Average ticket size

Now let’s see how to calculate each of these blocks:

1) Total addressable market = US population X % bankable population

2) Product penetration = number of credit cards per capita in US X % of active cards

3) Average ticket size = average credit card limit X %limit usage

  • average credit card limit is usually estimated though debt-to-income ratio. In case of credit cards it is 5 monthly salaries on average
  • limit usage could be derived from your personal experience but on average it is 20%

Let’s plug-in the data:

1. Total addressable market = 330 mln x 80% bankable population = 264 mln

X

2. Product penetration = 2 X 50%

X

3. Average ticket size = 4k USD X 5 X 20% = 4k USD

Thus credit card market size is 264 mln X 1 X 4k USD ~ 1tn USD

Let’s double check with official statistics. STATISTA.COM provides the following data: Value of credit card debt in the U.S is 0,93 tr USD. Thus our answer is super close

You can also make your calculations a bit more sophisticated if you add segments (e.g. by income or credit score). In this case you would have to provide detailed assumptions on product penetration and average ticket size for each segment.

As for the sources for your assumptions you can use:

  • Input from interviewer, well known facts
  • Statistical data
  • Personal experience, e.g. from casual everyday situations
  • Workplace experience, e.g. from working on projects in the industry
  • An educated guess

Best,

Anton

Hi,

Your approach is indeed a good one.

If you want to master your market sizing skills I suggest that you should focus on segmentations patterns. You can use the following segmentation for market sizes:

B2C:
- Demographics (Age, education, income, family size, race, gender, occupation, nationality)
- Behavioral (Purchasing behavior, customer journey stage, occasion & timing,
customer loyalty & interest, risk tolerance, user status)
- Psychographic (Lifestyle, personality traits, values, opinions, interests of consumers)
- Geographic (Geographical boundaries)

B2B:
- Company characteristics (Industry, company size, number of employees)
- Geography (Geographical boundaries)
- Purchasing Approach (Occasion & timing, customer capabilities, nature of existing relationship)
- Personal Characteristics (Loyalty, risk attitude, user status)

B2G:
- Demographics (Type of agency, size of budget, the amount of autonomy)
- Geographic (Geographical boundaries)
- Government Tier (Federal , State, Local, Quasi-governmental, International)
- Bid type (Closed, Open)

But sometimes you don’t need to segmentation. Here is an example of case that could be solved with high level top down approach - estimate the size of credit card market in the US:

In this case you should follow demand-driven approach to market sizing. By market size I would assume value of credit card debt in the U.S. (not the number of Credit Cards issued).

First of all you can start by outlying an algorithm which would consist of 3 big steps:

1. Total addressable market

X

2. Product penetration

X

3. Average ticket size

Now let’s see how to calculate each of these blocks:

1) Total addressable market = US population X % bankable population

2) Product penetration = number of credit cards per capita in US X % of active cards

3) Average ticket size = average credit card limit X %limit usage

  • average credit card limit is usually estimated though debt-to-income ratio. In case of credit cards it is 5 monthly salaries on average
  • limit usage could be derived from your personal experience but on average it is 20%

Let’s plug-in the data:

1. Total addressable market = 330 mln x 80% bankable population = 264 mln

X

2. Product penetration = 2 X 50%

X

3. Average ticket size = 4k USD X 5 X 20% = 4k USD

Thus credit card market size is 264 mln X 1 X 4k USD ~ 1tn USD

Let’s double check with official statistics. STATISTA.COM provides the following data: Value of credit card debt in the U.S is 0,93 tr USD. Thus our answer is super close

You can also make your calculations a bit more sophisticated if you add segments (e.g. by income or credit score). In this case you would have to provide detailed assumptions on product penetration and average ticket size for each segment.

As for the sources for your assumptions you can use:

  • Input from interviewer, well known facts
  • Statistical data
  • Personal experience, e.g. from casual everyday situations
  • Workplace experience, e.g. from working on projects in the industry
  • An educated guess

Best,

Anton

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Hi there,

I think this is a reasonable approach but it is limited.

You need to be careful to clarify that you're not talking bottleneck/capacity, but rather customer flow.

I think it is important to understand how quickly a given customer can be served, BUT you need to focus more on how many customers you think walk through the door across the morning/afternoon rushes and during quiet periods.

I would very much split by weekday/weekend and hour bands....then look at it from a customer perspective!

Hi there,

I think this is a reasonable approach but it is limited.

You need to be careful to clarify that you're not talking bottleneck/capacity, but rather customer flow.

I think it is important to understand how quickly a given customer can be served, BUT you need to focus more on how many customers you think walk through the door across the morning/afternoon rushes and during quiet periods.

I would very much split by weekday/weekend and hour bands....then look at it from a customer perspective!

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Hi Anonymous,

Your approach is fine, and looking at cashiers is reasonable (with seat you might omit take-away customers).

However, please be aware that you are immediately jumping into a bottom-up analysis. Before doing so, I'd recommend to clarify with your interviewer if that is fine!

Hope that helps - if so, please give it a thumbs-up with the green upvote button below!

Robert

Hi Anonymous,

Your approach is fine, and looking at cashiers is reasonable (with seat you might omit take-away customers).

However, please be aware that you are immediately jumping into a bottom-up analysis. Before doing so, I'd recommend to clarify with your interviewer if that is fine!

Hope that helps - if so, please give it a thumbs-up with the green upvote button below!

Robert

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Hello!

Overall is a good try.

However, carefull, since the bottleneck analysis also implicates that they are always -even with the corrections- operating at full capacity, and this is not always the case in a Starbucks.

Hope it helps!

Cheers,

Clara

Hello!

Overall is a good try.

However, carefull, since the bottleneck analysis also implicates that they are always -even with the corrections- operating at full capacity, and this is not always the case in a Starbucks.

Hope it helps!

Cheers,

Clara

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