How is funnel drop-off calculated?

Subtract stage 2 users from stage 1, divide by stage 1, and multiply by 100. For 5,000 to 1,250 users the drop-off is 75.0%.

How does this become a revenue figure?

The calculator prices the users recovered by cutting drop-off at your value per conversion, turning the percentage into dollars you can weigh against the cost of fixing the step.

What is a typical drop-off rate?

It varies sharply by transition, so compare a step to its own history and to similar funnels rather than a universal target. Cart-to-checkout and checkout-to-purchase often leak most.

Which drop-off should I fix first?

Start with the transition that combines a high drop-off rate with high downstream value, since recovering users there returns the most revenue per unit of effort.

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Revenue Loss From Funnel Dropoff

Measure the drop-off between two funnel stages and what it costs — and decide whether to fix the transition or accept the loss.

Stage 1 users

count

Stage 2 users

count

Funnel drop-off rate

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Average

Scenario lens Current · Benchmark · Optimized

Value / conversion

Leverage

Formula

Drop-off rate = (Stage 1 − Stage 2) / Stage 1 × 100

Understanding revenue loss from funnel drop-off

Reference material — the calculator above stays the primary tool.

What this measures

This is the share of users who leave between two funnel stages, paired with the revenue that drop-off costs at your value per conversion. It localizes a leak to a single transition and prices it, turning a behavioral gap into a recoverable revenue figure.

The value assumption is what makes it a revenue tool rather than an analytics metric: a drop-off percentage is abstract, but the same drop expressed as dollars sizes the fix.

How to read your result

The result places drop-off against a fixed benchmark and models the users recovered by cutting it, then prices that recovery so the metric resolves into a decision about whether the transition is worth fixing.

Use the scenario lens to weigh what reaching benchmark and optimized retention is worth before committing effort to the step.

Where drop-off concentrates

Most loss sits at a few transitions. Treat these as orientation for where to look.

Context	Typical median
Landing to engagement	Relevance & clarity
Cart to checkout	Cost & friction surprises
Checkout to purchase	Form & payment friction
Signup to activation	Time-to-value gap

Levers that recover users

Recovering users comes from reducing the effort and surprise at the transition: remove unexpected steps or costs, simplify the action, reassure with proof, and fix anything slow. Model the recovery as a scenario above to see the revenue it returns.

Is all drop-off recoverable?

No — read this alongside conversion rate and revenue per visitor, which the related tools cover. Some users were never going to proceed, so size the realistically recoverable portion before treating the full drop as lost revenue.