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AI Chatbots

Support and Pre-Sales Chat for SaaS

Software products suit chatbots: answer from the documentation, cite the page, separate pre-sales from support, and measure more than ticket deflection.

Updated 2 min readBy SpiderHunts Technologies

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Quick answer — TL;DR

Software products have documentation, which makes them unusually good candidates. Answer from the docs, cite the page, and separate pre-sales questions from support so both go to the right place.

Documentation is the advantage

Software businesses already have written documentation, which is exactly what a retrieval-based bot needs. Most other sectors have to write it first.

That means a software product can usually get to a good answer rate faster than anyone else.

Separate pre-sales from support

  • Pre-sales: pricing, limits, integrations, security — route to sales
  • Support: how do I, why is it doing that — route to support
  • Bugs: raise a ticket with the details captured
  • Account: billing and cancellation — always to a person
Mixing pre-sales and support in one queue means paying customers wait behind evaluators, which is exactly the wrong order.

Cite the documentation

Every answer should link the page it came from. Users who can read the full page solve their own next question without asking.

It also makes wrong answers immediately checkable, which is what builds trust in the bot.

What it should never do

  1. Promise a feature that is not shipped
  2. Give a date for anything on a roadmap
  3. Answer a security questionnaire
  4. Handle a cancellation or refund

Deflection is not the only metric

Ticket deflection is easy to measure and it is not the whole picture. A bot that deflects tickets by frustrating people into giving up is a loss disguised as a win.

Watch satisfaction and churn alongside deflection, and read the conversations that ended without resolution.

FAQ

Frequently asked questions

The questions readers ask us after this guide.

Still have a question?

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Ask about your project

What answer rate should a software product expect?

Higher than most — 80–90% is achievable where documentation is good and current.

Should it answer technical questions in depth?

From the documentation, yes. Where the answer requires reasoning about a customer's specific setup, hand over.

Can it help with onboarding?

Very effectively. New users ask predictable questions and a bot answering them at 11pm materially improves activation.

What about API questions?

It answers from your API documentation well. Debugging someone's specific implementation still needs a person.

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Start here

Support tickets that the docs already answer?

A bot over your documentation deflects those instantly. Start at spideychat.com.

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