Alle Fragen zum Tag Market sizing - Consulting Q&A - PrepLounge.com

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

Hello!

Totally!

Indeed, it´s not "it would be nice to clarify about the segments..." but it´s a must!

You always need to know your market, and segmenting it (B2B vs. B2C, determined aged groups, etc.) is the way to advance towards the solution.

Hope it helps!

Cheers,

Clara

Hello!

In the Q&A you have many many old post with interesting cases, that were solved and commented by many users and many experts.

It´s easy to filter them with "market sizing"

You can also use that tag filter in the Cases tab of PrepL.

Hope it helps!

Cheers,

Clara

Hi,

I would suggest that you should present your own approach and I would be happy to review.

Meanwhile please see below my approach to segmentation in market sizing as well as examples of solved cases:

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,

It's less about the quantity, but rather about the tools that you use:

1) First of all, there are 2 ways to structure market sizing:

• Formula - basically a math formula to come up with a solution. The problem with the formula is that it is easy to forget something or get lost.
• Tree - same as with regular cases you build a tree. A very simple example: you need to calculate the number of dogs on manhattan. A number of dogs = share of households having a dog * # of households. # of households = population / average household size. In the end, you'll have a pyramid where you have to fill the numbers on the base of the pyramid. This approach is much easier and help you track all the numbers

2) You should learn the key market sizing techniques:

• Making assumptions based on personal experiences (Use the example of your house where out of 100 apt-s 10 have dogs)
• Adjusting numbers (NY is a busy city thus fewer people have dogs)
• Sanity check - try to apply your calculations to the real environment
• etc.

3) You should learn the key tools:

• Using age even age split (suppose life expectancy is 80 years. Assuming even age split we have 4 mln people in US of each age)
• Using 80/20 split (suppose 20% people earn 80% wealth and the average salary is xx...)
• Using approximations (Length of NY-SF flight and plane speed to calculate US length)
• etc.

4) Learn key numbers: populations, gas price, gas consumption, Boeing speed and nmber of seats, average salary, # of gates in the airport, GDP growth rate, inflation, etc.

5) Practice 10-15 cases and you'll be fine. Almost all casebooks have good market sizing examples and the solutions

Feel free to PM for clarifications

Good Luck!

• UK population (= 60 Mio)
• # of women (~50% = 30 Mio)
• those in the marriable age (age group 20-60, i.e. 50% of all women if 80 y.o. is assumed as life expectancy = 15 mio)
• Out of those women % getting married while being in the age group (maybe also 50% = 7.5 Mio)

1. Out of those % getting divorced (50% = 3.75 Mio)
2. Out of those who are not getting divorced % who sell their wedding dress (10% = 0.75 Mio)

Total women selling their wedding dresses over their lifetime = 4.5 Mio

Divided by the number of "marrigeable years" we assumed: 4.5 Mio / 40 years = 112.5 k second-hand dresses per year

Hello Viktoria!

I would approach the problem as following:

• Estimate number of t-shirt per man
• Estimate percentage of white t-shirt
• Estimate the "expected life" of a shirt from Zara
• Number of white t-shirt sold per year= # men * # t-shirt per man * % white t-shirt / Expected life
• Estimate the market share of Zara
• # white tshirt sold by zara = Mkt share * # white t-shirt sold per year

Feel free to text me if you want to discuss it further,

Luca

Hello!

I agree with the overall approach, and it´s very detailed.

I agree the numbers end up being a bit high, but this would probably mean that some of the assumptions are overstated.

In any case, what the interviewer looks into here is the methodology, and this one is solid.

Furthemore, this problem is far too complex for an MBB interview.

Well done in any case!

Cheers,

Clara

Hi!

I would go from the consumer perspective:

• Approximately 300 Mio people in the US
• Out of them: 75% who go to the stores (total population divided into 4 age groups: 0-20; 20-40; 40-60; 60-80 -> those who are 20 to 80 go to the stores) = 225 Mio
• I would divide those 225 Mio into urban (80% = 180 Mio) and rural (20% = 45 Mio) because they have a different frequency of going to the stores and different demand for plastic bags
• We could assume urbanites go to the stores at least several times a week (buying small quantities of food), let’s say 3 times using on average 1 plastic bag per visit = so, 180 Mio * 3 = 540 Mio plastic bags a week for urban population. Multiply it by ~50 weeks in a year and you get = 27 bn plastic bags a year for urban population
• Rural population visits to the store are probably less frequent, like 1 every two weeks, so we could calculate with 0,5 times a week but they probably use more plastic bags, let’s assume 5. So, 45 Mio * 0,5 times * 5 bags = ~ 112 Mio plastic bags a week. Multiply this by 50 weeks and you get = 5,6 bn plastic bags a year for rural population
• Overall yearly demand for plastic bags in the US = ~ 33 bn per year, or around 110 plastic bags per capita per year – which sounds realistic.

Hope this helps! If you want to brainstorm more on this feel free to reach out!

Best,
Daniel

Hi Piyush,

I would not worry too much about your estimation error, a 50% estimation error would not be a big deal, you just need to get magnitude of a number.

Interviewer don’t want you to get the exact number, they are more worried about your reasoning.

Looking at your estimation process I think you should pay attention to the question: you are asked to estimate the number of houses (including single family houses and condos).

From your calculation seems you estimating the number of homes, (same as estimating the number of households), rather than the number of houses.

A different approach to this question could be the following:

• Hypothesis:
  • Avg. household size: 3 people
  • People leaving in single-family house: 70%
  • People leaving in condos: 30%
  • Avg. number of apartments per condo: Avg. number of floors * Avg. number of apartments per floor
    • Avg. number of floors = 5
    • Avg. number of apartments per floor = 5
• Number of single-family house = Total population * people living in single-family house / household size
• Number of condos: Total population * people living in condos / households / Avg. number of apartments per condo

Please reach me out if you want to discuss it further,

Thanks,

Ale

Hi Piyush,

I've read carefully all your assumptions, looks very good! In the real estimation within the case probably the second part would be left out (dividing demand by # of rides) because it becomes too cumbersome. You would probably just need to estimate it from the population top town, would arrive at 9.6 M and the interviewer would already stop you there.

Best,

Daniel

Hi PK,

Overall a good and logical approach!

Just some small points on assumptions.

(1) 70% penetration of ride-hailing seems high. While it could be possible in the big metropolitan cities like NY or SF, outside the handful of big cities the penetration rate would be rather low.

(2) Don't forget there is Lyft also. So besides the 70% penetration rate, you probably need to think about market share as well. At the moment Lyft probably is comparable or just a bit smaller than Uber?

Cheers,

Emily

Hi Piyush, you are getting better at this, good job :)

just out of curiosity: what company are you preparing for? I'm asking because at MBBs estimations are not that frequent (at McKinsey they can sometimes come in the second round, but also rarely) and it's better to focus your time and efforts on practicing the standard cases (structuring, analyzing exhibits and doing case math).

Best,
Daniel

Hi Khushi,

this is (at least) the third market sizing question you post in a short time. Without any context, an ask for help or a thank you.

So, how about you do the work, present two or three ways, and then ask for feedback?

We're not your personal case assistants, we're experts who provide advice and feedback.

best,

Elias

Yes they are - it's not as common and often buried within a case but they are definitely a tool that people use.

Hello!

Indeed, you are right. Usually you find market-sizing exercises inside of other big exercises (e.g., profitability, etc.)

It´s very rare that you find a market sizing case just by itself, without other content, in MBB interviews.

The way to prep this particular piece, if it´s the one making you struggle and consuming all the time, is to do as many as possible:

1. In this Q&A, you can filter dozens of them by typing market sizing, commented by experts
2. There are tons in Google, with solutions
3. PM if you want some MBB-like, since I have 3 self-contained exercises precisely for a coachee of mine who used to struggle with this part too

Hope it helps!

Cheers,

Clara

Hi

You can expect to have 3 types of market sizing questions:

1) Top down market sizing questions

• Calculate the number of gas stations in the US
• Calculate the size of credit cards market in the US
• How much domestic trash is collected each year in the US (in m3 or tons)?

2) Bottom up market sizing questions

• You know that Citi bank has a portfolio of 200 bln credit cards in x country. Calculate the size of the market
• You know that there are 40 tube stations in the Centre of Moscow. Calculate the number of Starbucks cafes in Moscow

3) Guesstimate questions

• If all the humans in the world were crammed together, how much area would we require? Compare this to the area of a large city, a state or a small country, the US, Asia
• How many golf balls would it take to circle the Earth at the equator?

I have answered a similar question and provided a detailed solution to a market size.

Have a look here: https://www.preplounge.com/en/consulting-forum/how-should-i-approach-the-following-question-estimate-the-market-size-of-credit-cards-in-the-us-6695

Best,

Anton

Hi Anonymous,

As mentioned earlier, there are many different ways one can approach this problem. I typically approach this following way:

1. What is the total demand for gas stations?

2. What is the demand for one gas station?

3. -> Find the total number of gas stations

To start with number 1, while I have no idea about the real numbers, let's assume that population is 400M, and there is 1 car per 4 people. Thus we would have 100M cars.

Now we need to estimate the total demand for a day/week/year, let's go ahead with day. From my personal experience, I visit gas stations once every two weeks. Assuming this is the case for the entire population, 100M cars would visit gas stations every two weeks. This means that about 7M cars visit gas stations every day. -> This is the total demand.

Now we are at number 2, we need to understand the number of cars visit a gas station during one day. To keep it simple, we can assume (again, based on personal experience) that there are always 3 cars occupying the gas station for 5 minutes throughout 18 hours (and the remaining of the time, the gas station is empty). This would give us ~600 cars every day. -> This is the demand for one gas station.

We can find the number of gas stations by diving total demand (7M) by local demand (600), and reach ~12000 as our final answer.

I have quickly checked on google, and the real answer is about x10 higher than my answer. HOWEVER, it really is not important to get a precise answer to impress the interviewer. It is all about sharing your train of thought and laying out your assumptions very explicitly.

I hope this was helpful.

Have a good day,

Deniz Ahmet

Hi, Peter!

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