Exit Rate Calculator
From a page's exits and page views, compute the share of visits that leave the site from that page.
Input Data
Results
At a glance:Exit Rate is the percentage of a page's page views that ended the visit on that page — of all sessions that passed through the page, what share left the site from it, regardless of pages seen before. It judges each page's drop-off in the visitor journey. A high exit rate is not inherently bad — it depends on the page's role in the funnel.
Formula
Exit rate = exits from the page ÷ page views × 100%.
$$\text{Exit Rate} = \dfrac{\text{Exits}}{\text{Page Views}} \times 100\%$$How to Use
- Enter the exits (visits that left after this page).
- Enter the page views in the period.
- View the page's exit rate.
Exit rate worked examples
| Scenario | Exits | Page views | Exit rate |
|---|---|---|---|
| Baseline | 3,000 | 15,000 | 20.00% |
| Flow blocked (exits up) | 4,500 | 15,000 | 30.00% |
| More views | 3,000 | 20,000 | 15.00% |
Exit rate = exits ÷ page views × 100%. A page's exit rate is usually ≥ its bounce rate because it also counts sessions that saw multiple pages before leaving.
Case Studies
Case 1: Exit rate of a product page
A product page viewed 15,000 times in a month, of which 3,000 visits left the site after viewing it (regardless of earlier pages).
Exit rate = 3,000 ÷ 15,000 × 100% = 20%.
20% means 1 in 5 views ends the visit here. Whether to worry depends on the page's funnel role — if it is a relay to the next step, 20% is acceptable; if it is the key pre-checkout page, watch for friction.
Case 2: Spotting the problem page in the funnel
Analysing the cart page: exits rose to 4,500 (views still 15,000): exit rate = 4,500 ÷ 15,000 × 100% = 30%, 10 points above baseline.
The cart page should not be a natural endpoint (visitors should continue to checkout), so 30% is a warning — shipping/total price revealed only here, missing trust, or unclear checkout button.
By contrast, a checkout-complete page at 90% exit is perfectly normal — it is the endpoint. So exit rate must be read against the page's funnel role: find 'should-not-be-high-exit yet high' pages (usually high-value mid-funnel), then use heatmaps/recordings/surveys to find why, and prioritise those. Pair with the conversion-rate calculator.
FAQ
What is the difference between exit rate and bounce rate?
Bounce rate counts only single-page sessions — visitors who left after one page. Exit rate counts, of all sessions that passed through the page, the share that ended there, regardless of pages seen before. A page's exit rate is usually higher than or equal to its bounce rate. Tell them apart to avoid misreading page performance.
Does a high exit rate mean the page is bad?
Not necessarily — it depends on the page's role. A checkout-complete, thank-you, download-complete or contact page naturally has a high exit rate because it is the journey's endpoint; that is success. But a cart page or mid-checkout page with a high exit rate is a warning — friction, unexpected cost or low trust. Ask first: is it reasonable for visitors to leave here?
How do I lower an undesirable page's exit rate?
First use heatmaps, recordings and surveys to find where and why visitors get stuck, then act: simplify the flow, show costs upfront, add trust signals (reviews, guarantees, security badges), and give a clear next-step CTA and related recommendations. Validate with A/B tests and prioritise high-value pages.
Does a high exit rate mean this page performed poorly?
Not necessarily — reading exit rate always starts with 'is it reasonable for visitors to leave the site from this page?' Its meaning depends entirely on the page's role in the journey/funnel. Some pages are natural endpoints, where a high exit rate is normal and even ideal: checkout-complete (order placed, satisfied exit), thank-you, download-complete, contact (got the phone/address and left). A high exit rate there means the task succeeded. But other pages should not be endpoints — visitors should continue to the next step — and a high exit rate there is a warning: cart page (should continue to checkout), mid-checkout pages, category pages (should click into a product). A high exit rate on those suggests friction, cost revealed only here, missing trust signals or unclear next step. So: (1) split pages into 'reasonable endpoints' vs 'should-not-end-here'; (2) only diagnose pages that 'should not be endpoints yet have high exit rate'. Exit rate only says where, not why — pair with heatmaps, recordings and surveys. Never compare exit rates of pages with different roles.
How to find and optimise a problem page's exit rate?
Finding and fixing a problem page is 'locate, diagnose, validate'. Step 1 locate high-impact problem pages: prioritise 'high traffic × abnormally high exit rate × key funnel relay', which give the best ROI. Rank pages by views and exit rate, target the top-right (high traffic, high exit) that should not be high-exit. Step 2 diagnose why: exit rate says where, not why — use qualitative tools: heatmaps (where they stop/click), session recordings (where they stall), exit surveys ('why are you leaving?'). Common reasons: too many steps, shipping/extra fees revealed only here, registration required to continue, slow load, missing trust signals, unclear CTA. Step 3 act and A/B test: simplify flow, reveal costs early, add trust, highlight the next-step CTA and recommendations; then A/B test exit rate and final conversion, roll out only after confirmed. Reminder: lowering exit rate is not the goal — the goal is higher overall conversion; sometimes lowering a mid-page exit rate without lifting final orders means the problem is elsewhere. Pair with the conversion-rate and churn-rate calculators.
Related Tools
References
Content review: Calculatorism Finance Team. Results are for reference only; please refer to the relevant authorities for the official figures.