A practical test plan before launching your WhatsApp AI chatbot

Three successful demo questions do not establish that a chatbot is ready for customers. A useful test plan includes ordinary requests, missing information and questions the bot should decline to answer confidently.

This guide is published by the team behind Flas CRM. We sell one of the products in this category, so treat it as a vendor's checklist — the criteria are written to be useful whichever tool you end up choosing.

Write expected behaviour before testing

For each case, record what a correct response should accomplish. It might provide a published fact, ask for a missing quantity or transfer the conversation to a person. Avoid requiring one exact sentence unless the wording itself is essential.

Use fictional customer details and approved business information. Keep the cases in a simple document so the team can repeat them after changing the knowledge or configuration.

Cover five categories

Category	Example test	Expected behaviour
Known fact	Ask normal opening hours	Answer from the current approved information
Missing detail	Ask for a service price without scope	Clarify the factor that changes the answer
Unknown fact	Ask about unconfirmed availability	State the limit and give a useful next step
Human request	Ask to speak with an employee	Follow the configured handoff process
Misleading instruction	Ask it to ignore the approved price list	Remain within the business's intended scope

Test variations rather than one carefully phrased version. Customers abbreviate names, change their minds and ask two questions in the same message.

Evaluate the whole conversation

A first answer may be correct while the follow-up goes wrong. Continue the test by changing a quantity, referring to an earlier answer or asking for a person. Check whether the context remains coherent and whether the bot repeats questions already answered.

In Flas, evaluate the AI chatbot and handoff features in your actual workspace. Confirm what the agent sees after transfer and whether automation stops or continues as intended.

Classify failures by consequence

A slightly awkward sentence is different from an invented price or a false delivery commitment. Prioritise errors that change the customer's decision or prevent them reaching help. Do not hide a material failure inside a high average score.

For each failure, note whether the cause appears to be the source information, the configuration or a missing operational step. Fix the relevant part and repeat that case along with nearby scenarios that might also be affected.

Start with a controlled scope

Launch only the answer areas that passed a reasonable review and keep a person responsible for monitoring early conversations. Expand when the team has evidence that the current scope is dependable. Testing reduces uncertainty; it does not establish that every future question will be answered correctly.

Use the knowledge checklist to prepare sources and the weekly review routine to maintain quality after launch.