In the last chapter, you learned how to move through a case with direction: form a working view, test it, update, and move.
Market sizing is what happens when the next thing you need is not handed to you.
There is no exhibit. No clean dataset. No perfect number waiting on the page. The interviewer simply asks: How big is this market?
And for a moment, it can feel like you are being asked to pull a number out of thin air. You are not. You are being asked to build a reasonable estimate from logic.
The intuition
Market sizing is not guessing the right number.
It is estimating the unknown with a clear path.
Nobody expects you to know exactly how many takeaway coffees are sold in a city every year, or how large the protein powder market is, or how many gym memberships exist in Chicago. The point is not database memory. The point is whether you can say:
I think the market is probably around $2 billion.
I will define the market, choose a top-down or bottom-up path, make reasonable assumptions, calculate cleanly, sanity-check the result, and explain what the number means.
That is why market sizing can actually become comforting once you learn the process. You are not trying to be psychic. You are building a bridge from what you know to what you need.
Why it matters
Market sizing tests several case skills at once: clarifying an ambiguous question, structuring an estimate before doing math, making assumptions without apologizing for them, segmenting instead of using one giant average, and turning the estimate into a business implication.
That is why interviewers use it. It is a fast way to see whether you can think with incomplete information, which is real consulting work. Clients ask questions before perfect data exists: Is this market big enough to enter? How much revenue could we capture? How many stores could this city support? Is this opportunity worth a deeper analysis?
The core moves
Market sizing leans on the math discipline you already built in Chapter 3: set up before you calculate, work in clean chunks, track units, sanity-check, and interpret. What this chapter adds is the part that comes before the math: when no data is handed to you, how do you build reasonable inputs yourself?
- 1ClarifyWhat exactly are we sizing?
- 2Pick a pathTop-down or bottom-up, then build the formula.
- 3SegmentWhere would one average mislead?
- 4AssumeRounded, defensible inputs, then calculate.
- 5Sanity-checkCross-check from the other direction.
- 6InterpretSo what for the client?
Throughout this chapter, we will use a coffee-related example that fits the rest of the handbook:
1. Clarify: make sure you are sizing the right thing.
This is where market sizing connects straight back to the Clarifying Questions chapter. Before you estimate anything, define the target.
- annual consumer spend
- or number of cups
- one large city
- or country / region
- coffee bought away from home
- exclude grocery and at-home
- residents
- tourists and commuters if relevant
- annual market size
- not a one-day snapshot
Said out loud, useful clarifying questions might sound like:
- Are we sizing the number of cups sold or the dollar value of consumer spend?
- Should I include only coffee bought away from home, or also grocery and at-home coffee?
- Are we looking at one large city, the full U.S., or a specific region?
- Should I count only residents, or include tourists and commuters as well?
For this chapter, let us define the market as:
2. Pick a path: top-down or bottom-up, then build the formula.
Most estimates can be built from two directions.
Neither approach is automatically better. If you are unsure, pick the one you can explain most cleanly, then use the other as your sanity check.
3. Segment: do not let one average carry too much weight.
Market sizing gets weak when candidates pretend everyone behaves the same. Some people buy coffee every workday, some once a month, and some never. One giant average might be directionally fine in a very fast estimate, but segmentation usually makes the logic stronger.
- 1ResidentsStart with the city population.
- 2AdultsRemove children if they are unlikely buyers.
- 3Coffee drinkersKeep only people likely to drink coffee.
- 4Takeaway buyersKeep only buyers of coffee away from home.
- 5Frequency and priceConvert people into cups and spend.
You can segment by customer type, age, channel, price tier, or occasion. You do not need all of these. Choose the segmentation that changes the answer most.
4. Assume: use rounded, defensible inputs, then calculate.
This is what interviewers actually grade. A defensible assumption beats a precise-looking one every time. Assumptions are not a confession that you do not know the answer. They are the tool that lets you estimate when exact data is missing.
So the estimate is about 315 million takeaway coffees per year, or roughly $1.6 billion in annual consumer spend. But the work is not finished.
5. Sanity-check: cross-check from the other direction.
An estimate without a sanity check is fragile, and the most powerful check in sizing is to rebuild the number from the other direction.
- fewer than 1 in 10 residents daily
- plausible for a large city
- ~875K cups/day
- x 365 x $5 = ~$1.6B
- revisit assumptions
- find the biggest driver of the gap
6. Interpret: turn the estimate into a business implication.
Do not end on the number alone. This is the same so-what move from Math and Synthesis, now applied to an estimate: connect the size to the client's actual decision.
A small library of useful reference numbers
You do not need to memorize a giant fact book. But a few rounded anchors make sizing faster.
What weak looks like
What strong looks like
The exact number is not the magic. The path is.
Common traps
- Sizing the wrong thing because you did not clarify unit, geography, or time period.
- Choosing assumptions before building the formula.
- Using one giant average when segmentation would help.
- Over-segmenting until the math becomes impossible.
- Chasing false precision instead of rounded, defensible numbers.
- Losing units or forgetting to round.
- Skipping the sanity check.
- Stopping at the final number without saying what it means.
The most common trap is trying to be accurate before being structured. Do not aim for exact. Aim for reasonable, transparent, and useful.
How to use this later in CaseLab
When a live case later includes market sizing, use this chapter as your feedback lens. For now, the goal is to understand the arc: scope, path, assumptions, estimate, sanity check, and implication.
Later, in a CaseLab rep, review whether you:
- Clarified the market, unit, geography, and time period.
- Chose a sensible top-down or bottom-up approach and built the formula first.
- Used reasonable, rounded assumptions.
- Segmented where it improved the estimate.
- Kept units and math clean.
- Sanity-checked the final number from the other direction.
- Explained the business implication.