Let the conversation fill in your CRM
Every WhatsApp conversation carries data — budget, timeline, product interest, objections. QualiBot extracts it as it happens and writes structured fields, summaries, tasks and stage changes straight to the CRM, so no one retypes a chat log by hand.
Why this costs you deals today
A great qualifying conversation is worthless if it stays trapped in a chat window. Agents end every WhatsApp exchange with the same second job: reread the thread, decide what mattered, and manually type it into the CRM as notes, fields and a next task. That work is slow, inconsistent between agents, and the first thing skipped when the day gets busy.
The result is a CRM full of gaps — deals with no budget field filled in even though the lead stated it clearly, no summary of what was actually discussed, no task created for an obvious next step, and a pipeline stage that was never moved even though the conversation made the lead's intent unmistakable.
The fix is to treat the conversation itself as the source of the data: extract the structured facts as they are said, summarize the thread, create the task the conversation implies, and update the score and stage — all without a human re-typing any of it.
The automated workflow, step by step
Budget, timeline, location/product preference, contact details and other qualifying facts are captured the moment the lead states them.
Extracted values are mapped to the corresponding contact and deal fields — no manual data entry, no re-typing a chat transcript.
A concise written summary of the thread is attached to the record, so anyone picking up the deal later gets the context instantly.
Where the conversation implies a next step — a callback, sending a document, a viewing follow-up — a task is created with the relevant due date.
Signals like budget confirmation, urgency and engagement update the lead score in real time, reflecting how qualified the lead actually is.
When the conversation clearly indicates progress — qualified, viewing booked, offer requested — the deal's pipeline stage updates to match.
What the conversation looks like
QualiBot handles the back-and-forth in natural language, captures the answers as structured data, and hands off to a human the moment it matters.
What lands in your CRM
Frequently asked questions
What kind of data gets extracted from a conversation?
Qualifying facts the lead states directly — budget, timeline, location or product preference, purpose (e.g. end-user vs. investor) — mapped to the fields configured on your CRM record.
Does this replace note-taking entirely, or add to it?
It handles the structured extraction, summary and task creation automatically. Agents can still add their own notes on top, but they no longer have to manually transcribe the conversation to populate basic fields.
How accurate is the field extraction?
Extraction is based on what the lead explicitly states in the conversation; ambiguous or unstated details are left blank rather than guessed, so the CRM reflects only what was actually said.
What triggers a pipeline stage change?
Stage moves are tied to clear signals in the conversation — such as confirmed qualification, a booked viewing, or a requested offer — configured to match your own pipeline definitions.
Can we control which fields get written automatically?
Yes, the field mapping between the conversation and your CRM schema is configurable, so only the fields you want populated this way are touched.
Which CRMs support this data entry?
Zoho, HubSpot, Salesforce and Bitrix24 are all supported for reading and writing fields, summaries, tasks, lead scores and stage changes.
Does this work for conversations in Arabic?
Yes — field extraction, summarization and scoring work across both Arabic and English conversations.
See your CRM fill itself in, live
We'll run a real conversation through QualiBot and show you the fields, summary, task and stage change it produces.