Free tool

The market size calculator.

Build your market from segments you can defend, then see which guess moves the total most. Ranges, not fantasies, and nothing you type leaves your browser.

How big is the market for my product?

Multiply the people you could reach by the share who would buy, what they would pay, and how often. That is your total addressable market in one line of arithmetic. The hard part is never the maths. It is defending each guess, which is what the sensitivity ranking below forces you to do.
The numbers below are placeholders. Every one of them is yours to replace, and the ranges only mean something once you have.

What each box wants

Heads:
how many people are in the group. A headcount, not customers yet.
Would buy (%):
your guess at the share who would buy this sort of thing from anyone, you included. Your own slice comes later, through the win slider.
Avg spend (R):
what one buyer spends per purchase, in rands.
Buys per year:
how often each buyer buys in a year.
We can serve these people:
tick it only for groups you can actually reach and serve today. Unticked rows count toward TAM, never toward SAM or SOM.

Your obtainable slice. Single digits keeps you honest unless distribution is already locked in.

How far off each guess could be, either way. The ranges assume every guess lands this far out at once.

TAM

Everyone who could ever buy.

R37.8m

Range R19.3m - R65.2m

SAM

The served slice. Same as TAM for now, because every segment is ticked as served.

R37.8m

Range R1.9m - R6.5m

SOM

The slice you could win.

R3.8m

Range R1.5m - R7.8m

The low end replays your whole estimate with every guess 20% worse: fewer heads, fewer buyers, smaller baskets, fewer repeat buys. Real misses point both ways and cancel each other out, so this floor is deliberately harsh. Plan your spending against it, and treat the high end as the prize, not the promise.

R0R2.0mR4.0mTotal SOM R3.8mShare we can winShare we can win±R755.2kCity commuters: any single guess ±20%City commutersany single guess ±20%±R547.2kSuburban families: any single guess ±20%Suburban familiesany single guess ±20%±R208.0k
How far each guess swings the obtainable market. Within one segment, any single guess moves the total by the same amount, so each segment gets one bar. The longest bar is the guess most worth researching.
Segment inputs and yearly revenue, with served segments marked
SegmentHeadsWould buyAvg spendPer yearYearly valueServed
City commuters400,0006%R3803×R27.4mYes
Suburban families250,0004%R5202×R10.4mYes

Everything runs in your browser. Nothing you type leaves your device.

What is the difference between TAM, SAM and SOM?

TAM is everyone who could ever buy. SAM is the slice you can actually serve, your regions, channels, languages. SOM is the slice of that slice you can plausibly win in the next few years. Founders pitch the first number and budget against the third. This calculator keeps all three on screen so the gap stays visible.

Which of my assumptions matters most?

The tornado chart ranks every guess by how far it swings your obtainable market when it wobbles. Usually one or two assumptions do most of the damage. Those are the ones worth researching before you commit budget, because shrinking their uncertainty shrinks the whole range.

The words, in plain English.

TAM
Total addressable market. Everyone who could ever buy what you sell, in rands per year. The biggest number and the least useful one, because you will never serve all of it.
SAM
Serviceable addressable market. The slice of TAM you can actually reach: your regions, channels, languages, price band. Tick the served box per segment and the calculator totals it.
SOM
Serviceable obtainable market. The slice of SAM you can plausibly win in the next few years. This is the number to plan against, and for newcomers it usually lands in single digits of TAM.
Penetration
The share of a segment who would actually buy in a year. The guess that most often decides the total, which is why it usually tops the sensitivity chart.
Sensitivity analysis
Wobbling each guess in turn to see which moves the answer most. The ranking tells you where research money buys the most certainty.

Why ranges instead of one big number?

A single market figure pretends a precision nobody has. Every input here is a guess with error bars, so honest output carries them too. The range is the answer: plan against the low end, size the prize by the high end, and spend research money narrowing the gap between them.

One honest note: the calculator takes your segments at face value and assumes they do not overlap. If two rows count the same people, the total double counts them, so keep the groups distinct. And if the wobble feels too wide everywhere, that is a sign the assumptions need evidence. Our market research and sizing service exists for exactly that, and the nine-step approach shows how a sizing study runs. For background, read how market research and UX research differ.

FAQs

Questions the calculator gets asked.

Bottom up: for each customer group, multiply heads by the share who would buy, by average spend, by purchases per year. Add the groups for TAM, keep the ones you can serve for SAM, and take the winnable share of that for SOM. The calculator does exactly this, live.

There is no good number, only a defensible one. SOM is your honest win share over the next few years, and small is fine if the maths behind it holds up. A modest SOM you can defend beats an impressive one you cannot.

Because every input is a guess with error bars. The low end replays your estimate with every guess worse at once: fewer heads, fewer buyers, smaller baskets, fewer repeat buys. Real misses point both ways and cancel each other out, so the floor is deliberately harsh. Plan your spending against it, and treat the high end as the prize, not the promise.

Yes. One row holding the whole market works fine, and the sensitivity chart still tells you which guess matters. Add segments when different groups clearly buy differently.

No. All the maths runs in your browser on your device. Nothing you enter is transmitted, stored, or logged, which keeps the tool comfortable to use under POPIA.

Calculator reviewed October 2026.

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