QuackbackTicket deflection calculator
Enter a month of help-center views, searches and tickets. You get an estimated deflection rate, how many questions your help center answered, and the support hours that saved. Free, with no sign-up.
A month of help-center numbers
Estimated deflection rate
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Enter searches and tickets to see your estimate.
- Support hours saved a month
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- Article views per ticket
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How to estimate ticket deflection
You can't count tickets that were never sent, so every deflection rate is an estimate. Use this one to watch the trend.
Deflection rate = (searches − tickets) ÷ searches × 100
Take one month of numbers
Help-center searches and article views from your help center's analytics, and new tickets or conversations from your inbox.
Subtract tickets from searches
What's left is the questions people answered themselves, assuming each ticket was a search that came up short.
Turn it into time
Multiply the answered questions by your average handling time to see the hours the help center saved.
- Help-center searches
- 3,000
- Tickets
- 600
- Questions answered without a ticket
- 2,400
- At 12 minutes a ticket
- 480 hours
- Deflection rate
- 80%
How to deflect more tickets
The searches that fail tell you exactly what to write next.
Help center in Quackback
See what customers search for, and what they don't find
Quackback's help center lists the terms visitors search for over the last 30 days, with how often each search returned nothing. Article performance shows views and how many readers found each article helpful. This is a demo workspace: click around.
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Common questions
What is ticket deflection?
Ticket deflection is a question answered by self-service, such as a help-center article, a search or an AI answer, that would otherwise have become a ticket. The deflection rate is the share of those questions that never reach your team.
How do you calculate the deflection rate?
There's no single standard, because you can't see the tickets that weren't sent. This calculator treats each help-center search as a question and each ticket as a search that didn't find its answer: (searches − tickets) ÷ searches. With 3,000 searches and 600 tickets, that's 80%.
How accurate is this estimate?
It's a rough guide. It assumes every ticket came from someone who searched first. People who write in without searching push the true rate up; people who search several times for one question push it down. Track the trend from month to month, not the single number.
What is a self-service score?
It's help-center use divided by tickets, here article views per ticket. A score of 20 means 20 article views for every ticket. It's a simple ratio to watch over time: if it rises while tickets fall, self-service is doing more of the work.
What is a good deflection rate?
It depends on how you measure it, so compare your own trend rather than another company's number. Watch it alongside the searches that return nothing and the articles readers mark unhelpful: those show where the next gain is.
How do I increase ticket deflection?
Write articles for the searches that return no results, fix the articles readers mark unhelpful, suggest articles while customers type their message, and put search where customers already are, in your product and on your contact page.
Have another question? Talk to the team.