Pipeline forecasting

Will we hit the number?

Quota Lens runs thousands of Monte Carlo simulations of your open pipeline to turn a list of deals into a probability of hitting quota — and shows which deals actually move it.

Upload pipeline CSV Showing synthetic sample data · files stay in your browser

Try it: drag the Commit win rate down to 60% and watch the odds of hitting quota fall — then sort the table by swing.

Chance of hitting quota

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Most likely outcome (P50)

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Likely range (P10–P90)

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8 in 10 quarters land here

Pipeline coverage

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Distribution of quarter outcomes

Outcomes at or above quotaBelow quota

Deals that move the needle Swing = change in chance of hitting quota if this deal is won vs. lost

Deal	Owner	Stage	Amount	Close	Win prob.	Expected	Swing

Expected bookings by repProbability-weighted, this quarter

Open pipeline by stageRaw amount, closing this quarter

How it works

1 · Score every deal

Each open deal starts with its stage’s historical win rate. Deals that have sat in a stage for more than 45 days get a haircut, because stalled deals close less often.

2 · Account for timing

Winning isn’t enough — the deal has to land this quarter. Each deal carries a slip risk that is highest in early stages and smallest at Commit.

3 · Simulate the quarter

For each simulated quarter, every deal is randomly won or lost using its probability. Adding the wins to closed-won gives one possible outcome; repeating thousands of times gives the full distribution.

4 · Find the swing deals

Comparing quarters where a deal was won with quarters where it wasn’t shows how much each deal changes the odds — so a team knows where to spend executive time.

CSV columns: deal_id, deal, account, owner, stage, amount, close_date, days_in_stage. Stages: Discover, Qualify, Propose, Negotiate, Commit. Sample data is synthetic and for demonstration only.