A market-sizing answer becomes convincing when someone can follow how the business works through your calculation. The size of the final number comes second.
Start with the thing the client needs to decide. An installer hiring crews needs annual installation demand. A manufacturer assessing its long-term opportunity may care about homes that could eventually switch. Those questions use some of the same information and produce different answers.
I would spend more effort getting that distinction right than memorising another population statistic. A tidy calculation of the wrong market is difficult to rescue.
Say exactly what you are estimating
Before drawing a tree, complete this sentence: “I’m estimating ___, in ___, over ___.” Include the unit, geography and period.
For example: “Residential heat-pump installations in this city over the next year, excluding new construction.” That gives you a count of installations per year. It also tells you what to leave outside the calculation.
If the client asks for revenue, add an appropriate price after estimating units. If it asks how much revenue it can win, add a defensible route to customers. The whole market does not become the client’s sales simply because the client intends to enter it.
Build the equation before choosing the numbers
For this fictional city, use:
Homes × share in scope × annual replacement rate × heat-pump choice = annual installations.
This equation makes the logic visible. Homes are the purchasing units. The replacement rate converts an installed base into annual buying occasions. The final share describes what people choose on those occasions.
Other questions need different equations:
| Question | Useful starting equation |
|---|---|
| Annual coffee sales | Buyers × purchases per buyer per year |
| Reusable containers needed | Uses per day × days before reuse |
| Lounge demand | Eligible departures × probability of visiting |
| Peak digital traffic | Requests in the busy window ÷ seconds in that window |
Choose the structure that follows the activity. Starting every estimate with a national population creates unnecessary work for questions about factories, enterprise software or infrastructure.
Give assumptions a reason
Suppose the interviewer supplies one million residents. You estimate 2.5 people per home, giving 400,000 homes. You then assume 60% fall within the installer’s target housing segment, leaving 240,000.
Explain what the 60% represents. Perhaps the client initially serves a particular property type and heating system. Avoid using a mysterious “suitability factor” that quietly bundles property access, affordability, customer interest and installation timing.
Now assume 5% of these homes replace their heating system during the year. That creates 12,000 buying occasions. If 40% choose a heat pump, demand is 4,800 installations per year.
The useful explanation sounds like this:
“I’ve separated the homes we could serve from those making a purchase this year. The annual result depends most directly on replacement timing and the share choosing a heat pump.”
A reasoned assumption can be challenged and improved. An unexplained percentage merely fills a cell.
Quick Answer Repair Drill
A premium espresso-machine supplier is sizing yearly sales to independent cafés in one city before hiring sales staff.
- Independent cafés
- 2,000
- Machine replacement cycle
- About every 8 years
- Buyers choosing premium
- 30%
An analyst estimates 600 premium machines a year. What is the main flaw?
Keep the calculation easy to audit
Write the intermediate totals and units:
| Step | Result |
|---|---|
| 1,000,000 residents ÷ 2.5 residents per home | 400,000 homes |
| 400,000 × 60% in scope | 240,000 homes |
| 240,000 × 5% replacing this year | 12,000 replacement decisions |
| 12,000 × 40% choosing heat pumps | 4,800 installations this year |
This helps you recover if an assumption changes. If the interviewer replaces 40% with 30%, only the final step changes: 3,600 installations.
Round numbers when doing so simplifies the calculation without changing the decision. If the client’s capacity is 4,400, rounding 4,800 to “roughly 4,000” erases the problem you are trying to solve. Retain enough precision to distinguish options near the decision threshold, then test the assumptions that could reverse the ranking.
Check the answer through a different route
Suppose the region has 20 available crews, each completing 220 installations a year. Capacity is 4,400 installations.
You now have demand of 4,800 and capacity of 4,400. Averaging them into a 4,600 “market estimate” would destroy useful information. They measure different things. The gap suggests an opportunity to increase delivery capacity, shift timing or investigate which demand will go unserved.
An independent check should expose a disagreement you can explain. It should not make two numbers agree by arithmetic.
Make the check specific to the business: crews for installations, seats for visits, or purchase frequency for annual demand.
Quick Guesstimate Drill
A firm that cleans restaurant kitchen extractors has sized annual demand in its region and is checking it against crew capacity.
- Estimated annual demand
- 6,000 cleans
- Cleaning teams
- 4
- Cleans per team
- 1,200 a year
What should the firm conclude from this check?
Test the assumption that could change the recommendation
In this example, capacity is filled when heat-pump choice reaches:
4,400 ÷ 12,000 = 36.7%.
At 30%, demand is below current capacity. At 50%, demand reaches 6,000 and exceeds capacity by 1,600. The next piece of research should sharpen adoption around that threshold, perhaps through recent quotes and conversion among the target homes.
You do not need to build a sensitivity table for every input. Ask which uncertain input might reverse the action. That is where another minute of analysis earns its place.
Finish with an answer the client can use
“I estimate about 4,800 installations next year within the defined segment. Existing crews can deliver about 4,400, so I would investigate additional capacity. The decision turns on whether at least 37% of replacement customers choose heat pumps; recent quote conversion would be my next check.”
That ending gives the number, its meaning and the next investigation. Before recommending hiring, translate the installations into productive hours and compare them with the available workforce. The market-sizing framework explains how an estimate fits into a broader investment case.
For practice, try Fast-Charging Plugs on an Interstate Corridor. Before calculating, write down whether the question needs vehicles, charging sessions or installed plugs. Your equation should preserve that distinction all the way to the answer.
Market sizing drill
Could you defend your estimate to an MBB interviewer?
Fast-Charging Plugs on an Interstate Corridor
Estimate corridor charging demand with Casey, Case Room’s AI interviewer. Distinguish demand from the plugs needed to serve it and explain your largest assumption.
Frequently asked questions
Framing the estimate around the client's decision
How should I phrase the scope at the start of a market-sizing case?
Complete the sentence “I'm estimating ___, in ___, over ___,” covering unit, geography and period. For example: residential heat-pump installations in this city over the next year, excluding new construction. That fixes the output as installations per year and shows what sits outside the calculation.
Why would an installer and a manufacturer get different market sizes?
They face different decisions. An installer hiring crews needs annual installation demand, while a manufacturer assessing its long-term opportunity may care about homes that could eventually switch. Both draw on some of the same information, yet the quantity being estimated, and so the answer, differs.
When should I bring price into the estimate?
Only after you have the unit count, and only if the client asks for revenue. Estimate installations per year first, then multiply by an appropriate price. Keeping volume and price as separate steps makes it easier to see which assumption is driving the final figure.
Building and explaining the calculation
What role does the replacement rate play in the equation?
It converts an installed base of homes into annual buying occasions. In homes × share in scope × annual replacement rate × heat-pump choice, homes are the purchasing units, the replacement rate creates this year's decisions and the final share describes what people choose on those occasions.
Can I use the same equation for every market-sizing question?
No. The equation should mirror how the specific business generates purchases, and the guide notes that other questions need different starting equations. An installed-base structure suits a replacement-driven product like heating, but would be the wrong shape for a question where buying occasions arise differently.
What's wrong with using a single “suitability factor”?
It quietly bundles separate assumptions, such as property access, affordability, customer interest and installation timing, into one unexplained percentage. Instead, say what each factor represents. The guide's 60% in-scope share, for example, might reflect the property type and heating system the client initially serves.
Should I write down intermediate results or just the final answer?
Write each intermediate total with its unit. The guide moves from 400,000 homes to 240,000 in scope, then 12,000 replacement decisions and 4,800 installations. Labelling every step lets an interviewer audit the logic quickly and point to exactly which figure they would challenge.
Checking, testing and presenting the result
If demand and capacity differ, can I average them into one estimate?
No. Demand of 4,800 and capacity of 4,400 measure different things, so averaging them into 4,600 destroys useful information. The gap is the insight: it suggests increasing delivery capacity, shifting timing or investigating which demand would go unserved.
How do I find the assumption that really matters?
Work out where the recommendation flips. Capacity of 4,400 is filled when heat-pump choice reaches 4,400 ÷ 12,000, about 36.7%. At 30%, demand stays below capacity; at 50%, it reaches 6,000 and exceeds capacity by 1,600. Adoption around that threshold is the input worth researching.
Do I need a sensitivity table for every input?
No. Concentrate on the assumption that could change the recommendation. In the heat-pump example that is adoption near the capacity threshold, so the next research would sharpen it, perhaps through recent quotes and conversion among target homes. Flexing inputs that cannot alter the decision adds little.
How should I end a market-sizing answer?
Give the number, what it means and the next investigation. The guide's example states about 4,800 installations next year in the defined segment, notes existing crews deliver about 4,400, suggests investigating capacity and names the 37% adoption threshold, with quote conversion as the next check.
Is an installation shortfall enough to recommend hiring?
Not on its own. Before recommending hiring, translate the installations into productive capacity requirements rather than reading headcount straight off the gap. The recommendation also depends on whether adoption actually clears the threshold, which is why quote conversion is the suggested next check.