Neidio i'r prif gynnwys
Ticket Deflection

Reduce support tickets with a source-cited AI chatbot

ChattyBox helps users self-serve before opening a ticket by answering common questions from your existing docs, help center, product pages, and FAQs.

Crawls published docs pages
Source-cited answers
Embeds with one script
No docs migration required
Gofynnwch i ChattyBox
x
Ble ddylwn i ddechrau os oes angen ateb dibynadwy arnaf o'r wefan hon?
Dechreuwch trwy ychwanegu URL eich gwefan at ChattyBox. Mae'n cropian eich cynnwys, yn ateb o'r tudalennau y mae'n dod o hyd iddynt, ac yn dangos i ymwelwyr y ffynonellau y tu ôl i bob ymateb.
iFfynonellau3^
Support canllaw
chattybox.ai
Dadansoddeg
chattybox.ai
Cartref
chattybox.ai
Gofynnwch gwestiwn...
Wedi'i bweru gan ChattyBox
Adeiladwyd ar gyfer support teams

Lansio chatbot a ddyfynnwyd yn ffynhonnell heb ailadeiladu eich pentwr dogfennau

Mae ChattyBox yn cropian eich dogfennaeth bresennol, yn mynegeio'r cynnwys i'w adalw, ac yn mewnosod chatbot sy'n ateb gan ddefnyddio'ch docs yn lle cof model generig.

Ground answers in the content your team already publishes.
Send users back to source pages when they need the full guide or reference.
Use unanswered questions to discover missing docs and unclear onboarding flows.
Install the widget without changing your docs platform or support stack.
Cam llif gwaith

Identify repeated tickets that are already answered in public content.

Cam llif gwaith

Crawl the docs, help center, product pages, and FAQs that should answer those questions.

Cam llif gwaith

Test the highest-volume ticket themes and review citation quality.

Cam llif gwaith

Install the chatbot before ticket creation and monitor unanswered questions.

Three-step launch

Paste your Support URL, test cited answers, then install the widget.

Build a support chatbot
Deflection workflow

Deflect the questions your content already answers

The best first use case is not full support automation. It is giving users immediate answers to the repeat questions your team sees every week.

01

Start with repeat volume

Look for pricing, setup, troubleshooting, account, integration, and how-to tickets with existing docs.

02

Cite the article

A source link makes the answer more trustworthy and gives users a path to more detail.

03

Escalate missing context

If the docs do not contain an answer, the chatbot should avoid guessing and surface the gap.

04

Improve content over time

Use unanswered questions to update docs and increase future deflection.

Cwestiynau cyffredin

Cwestiynau cyffredin

1

Can an AI chatbot reduce support tickets?

Yes, when many tickets repeat information already available in docs, FAQs, help articles, or product pages.

2

What tickets are best to deflect?

High-volume, low-complexity questions with clear public answers are the best starting point.

3

Should the chatbot answer account-specific questions?

Not unless the answer is available in the indexed source content. Use escalation for private or account-specific issues.

4

How do I estimate deflection?

Use support volume, repeat-question percentage, and expected chatbot resolution rate to model monthly impact.