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Marketplace traction forecasting model.

A cohort-based, two-sided projection across 24 months. Supply, demand, liquidity, unit economics and three sensitivity scenarios. Free, no sign-up, saved in your browser.

What this is

Most marketplace models break the same way. A founder projects demand, multiplies by an average order value and a take rate, and produces a number. That works for a business with one customer base. A marketplace has two, and the transaction only happens when both are present at the same time, in the same category, in the same place. Forecast one side alone and you will forecast revenue your supply cannot deliver.

This model runs supply and demand as separate cohorts, each with its own acquisition, activation and retention curve, then gates matched transactions on whichever side runs out first: buyer demand filtered by your match rate, capped by what your active suppliers can actually fulfil. Revenue is computed across three streams, take rate and a subscription on either side, so you can test what happens when you layer one on.

Who it is for

Founders building a model for a raise, and operators who need a board-ready projection that will survive a diligence conversation. It assumes you can put a number on your own funnel. If you cannot yet, the journey mapping workbook is the better place to start, because it surfaces which assumptions you are actually guessing at.

How the retention curve works

The most common modelling error after ignoring supply is assuming a flat retention rate. Real marketplace retention is a curve: it falls hard in the first three months, then flattens. This model takes three anchors, retention at months 1, 6 and 12, and interpolates between them, with a slow decay after the first year. You get a live preview of the shape as you type, which makes an over-optimistic assumption obvious before it compounds through 24 months of projections.

What you get out

A month-by-month projection of active users, transactions, GMV and net revenue. A set of computed unit economics: net contribution per transaction, lifetime value per side, and blended LTV to CAC. A sensitivity table showing pessimistic, base and optimistic cases side by side, because sophisticated marketplace investors read the pessimistic case first and want to know what survives if everything takes thirty percent longer than you said. And a one-page investor summary you can print straight into a data room.

If you want the assumptions pressure-tested before you put them in front of anyone, that is what the pre-development sprint covers.

Traction Forecasting Template · v2.0
A Marketplace Studio template · For founders raising or building a model
Marketplace traction forecasting model.

Most marketplace models break for the same reason: founders project demand without modeling supply, or model both without modeling liquidity. This template gives you a cohort-based, two-sided projection across a 24-month horizon, ready for a board meeting or a seed deck.

How this template works

Fill in the inputs across each section. Numbers update live. The example shown is a fictional marketplace, RigShare, a B2B heavy equipment rental platform, and you can clear it at any time using the topbar. When you are done, save as PDF for your data room.

Your marketplace

mo

What this template covers

01Supply cohortsAcquisition, activation, retention curves for the supply side
02Demand cohortsBuyer acquisition and frequency, modeled the same way
03LiquidityMatch rate, fill time, average booking value
04Revenue modelWho pays, what each side pays, and what you actually take
05Unit economicsCAC, LTV and payback by side, derived from the revenue model
06ProjectionRolled GMV, revenue, transactions and active users, month by month
07Sensitivity scenariosPessimistic, base and optimistic, side by side
08Investor summaryThe one page to put in front of someone
Section 01

Supply cohorts.

Supply growth is the harder side. Most B2B and service marketplaces fail because supply churns silently. They never come back to list new inventory. Model retention honestly here.

Acquisition

%

Activation and retention

%
%
%
%

Frequency and CAC

$

Retention curve preview

M188%
M376%
M662%
M955%
M1248%
M1843%
M2438%
Marketplace POV

The most common modeling mistake is assuming a flat retention rate. Real marketplace retention is a curve: supply churns hardest in months 1 to 3, then stabilizes. If your m1 retention is below 70%, your onboarding is broken. Fix that before forecasting anything.

Section 02

Demand cohorts.

Demand is loud. Sign-ups feel like progress. But sign-ups without first transactions are vanity. The activation rate is the number that matters, and frequency of use determines whether you build network effects or churn.

Acquisition

%

Activation and retention

%
%
%
%

Frequency and CAC

$

Retention curve preview

M175%
M361%
M645%
M937%
M1230%
M1827%
M2424%
Marketplace POV

For B2B marketplaces, expect 1 to 3 transactions per active buyer per month. For consumer leisure marketplaces (Airbnb-style), expect 0.1 to 0.3. If your number is between those, you have a frequency problem to solve before scaling acquisition.

Section 03

Liquidity.

Liquidity is what separates a marketplace from a directory. If a buyer searches and gets matched within hours, you have a marketplace. If they get matched after days, or never, you have a listings site that someone is calling a marketplace.

Match metrics

%
$
hr
Marketplace POV

The Cold Start Problem benchmark: match rate above 60% within 24 hours is healthy. Below 40% means demand is leaving for a substitute. The fix is rarely more demand. It is denser supply in the geographies and categories where buyers are actually looking. Solve liquidity before you solve growth.

Section 04

Revenue model.

There is no correct take rate, only a structure. Decide who pays before you decide what they pay, because the two are not independent: the side you charge is the side that feels the friction, and the side that feels the friction is the side that leaks.

Who pays

Marketplace POV

Say the rate out loud as each side would hear it. A supplier hearing “we keep 12.0% of what you earn” and a buyer hearing “we add 0.0% to your total” are two different conversations. Whichever one sounds worse is the side that will go around you first.

What each side pays

%
%

Everything else you charge for

Most marketplace revenue is not the headline rate. Each of these is computed separately and summed, so you can see what each one is actually worth.

Supplier subscription
$/month per active equipment owners (suppliers)
Recurring
$/mo
Buyer subscription
$/month per active contractors (buyers)
Recurring
$/mo
Payment markup
Basis points on top of the processing cost
Transactional
bps
Promoted listings
Share of active suppliers who buy placement, and what they pay
Recurring
% take-up
$/mo
Listing fee
Charged per listing created, not per supplier
Transactional
$/mo

Headline against realized

Headline take rate
12.0%
What you would say your rate is
Realized take rate
12.0%
Everything you take, as a share of GMV
The gap
+0.0 pts
Revenue you do not think of as take rate
Supply-side fee $7.9M

Which side is the constraint

Months supply-bound
5 of 24
Capacity gates transactions
Months demand-bound
19 of 24
Buyer demand gates transactions
What this means for your fee

Supply gates your transactions early and demand gates them from month 6. That means a fee rise costs you far more in the first months than it does later, because every point of retention you lose in that window removes capacity you do not have spare. The same rise after month 6 is close to free, because supply is sitting idle. If you are going to move the rate, moving it after the constraint changes hands is the cheaper trade.

If you raised the supply-side fee

pts

For every point you add to the supply-side fee, assume this many points come off supply retention at months 6 and 12. Leave it at zero if you have no evidence. This is your assumption, not a benchmark. It is stated as yours everywhere it appears, including in the printed model, so nobody reads it as analysis we did.

Section 05

Unit economics.

The fundamental question for any marketplace: does the take per acquired user pay back the cost of acquiring them, with margin to spare? We model both sides separately because the answer is rarely the same.

Per-transaction economics

%
$
%

Computed unit economics

Net contribution / tx
$133
After processing, support, refunds
Supply LTV
$1.4K
Lifetime contribution
Demand LTV
$1.3K
Lifetime contribution
Blended LTV / CAC
5.6×
Both sides combined
Marketplace POV

For a venture-fundable marketplace, target LTV/CAC of 3× or higher within 18 months, with payback under 12 months on at least one side. Pre-seed and seed founders often inflate LTV by assuming retention curves they have not earned yet. Model conservatively, then beat your model.

Section 06

24-month projection.

The rollup. Active users, transactions, GMV and revenue, projected from your supply and demand cohorts and gated by your match rate. The numbers below are computed live; they will move when you change any input above.

The last row is the one worth reading twice. It names which side is gating transactions that month: the side that runs out first is the side that decides how much volume you get, whatever the other side is doing.

MetricM1M3M6M9M12M15M18M21M24
Active suppliers1036951963797081,3042,3854,348
Active buyers26862063886781,1501,9233,1925,275
Transactions / month24862244227371,2512,0923,4735,739
GMV / month$44.4K$159.1K$414.4K$780.7K$1.4M$2.3M$3.9M$6.4M$10.6M
Net revenue / month$3.2K$11.4K$29.7K$56K$97.7K$165.9K$277.4K$460.5K$761K
Constraintsupplysupplydemanddemanddemanddemanddemanddemanddemand

Cumulative

Cumulative GMV
$66.1M
Across 24 months
Cumulative net revenue
$4.7M
All streams, after costs
Total transactions
35,710
Across 24 months
Exit-month run rate
$9.1M
Annualized M24
Section 07

Sensitivity scenarios.

Three scenarios derived from your base case: pessimistic (70% growth, 80% activation, 85% match), base (your inputs), and optimistic (115% growth, 110% activation, 105% match). The point is not which one is right. It is whether the pessimistic case is still survivable.

OutcomePessimisticBaseOptimistic
Cumulative GMV$23.3M$66.1M$107.6M
Cumulative net take$1.7M$4.7M$7.7M
Active buyers (exit month)1,7435,2759,026
Active suppliers (exit month)1,2074,3488,095
Exit-month MRR$213.8K$761K$1.4M
Exit-month ARR (run rate)$2.6M$9.1M$16.4M
How investors read this

Sophisticated marketplace investors look at the pessimistic case first. They want to know what survives if everything takes 30% longer than you projected. If your pessimistic case still gets you to product-market fit on a reasonable runway, you have a fundable model. If it does not, your base case is too aggressive. Go back and rebuild it.

If you raised the supply-side fee

The scenarios above vary things you influence slowly. This varies the one you can change on Monday. Each rung adds points to the supply-side fee and reruns the whole model.

Fee changeRateGMVNet revenueRealizedSupply-bound
As configured12.0%$66.1M$4.7M12.0%5 of 24
+3 pts15.0%$66.1M$6.7M15.0%5 of 24
+6 pts18.0%$66.1M$8.7M18.0%5 of 24
+9 pts21.0%$66.1M$10.7M21.0%5 of 24
Reading this

GMV does not move because you have assumed no retention response to a fee rise. That is the honest default, and it means this ladder is showing you the revenue upside with none of the cost. Set a response above to see the other half of the trade.

Section 08

Investor summary.

One-page snapshot. Drop this into a board update or include it as a slide in your seed deck.

Marketplace forecast · 24-month horizon
RigShare
B2B equipment rental marketplace · Canada (ON, expanding QC + BC)
Supply fee 12%
Cum. GMV
$66.1M
across 24 mo
Cum. net revenue
$4.7M
all streams
Exit ARR
$9.1M
M24 run rate
LTV / CAC
5.6×
blended both sides
Active suppliers
4,348
at M24
Active buyers
5,275
at M24
Match rate
68%
search to booking
Avg booking
$1.9K
per transaction
Want a second pair of eyes?

A model is only as good as its assumptions.

Book thirty minutes with us. We will pressure-test the retention curves, match-rate assumptions and CAC numbers, for free and with no strings, and tell you which inputs we would push back on if we were the lead investor on your round.

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