AI lead warming over WhatsApp
An assistant qualifies a new lead on WhatsApp, then hands over to a person.
Concept: a guided WhatsApp conversation in which an assistant qualifies a new lead, understands a voice note, writes the answers to the CRM and hands over to an agent.
The idea
Sales teams often receive more inquiries than they can call back quickly, and the first hours matter. This concept explores how an assistant could keep a conversation moving, in the business's tone, until a person is available, without pretending to be that person.
The design question
Leads that wait go cold. But an automated conversation that doesn't know when to stop does more harm than good. The question is how to warm a lead honestly: collect what the team needs, be useful to the customer, and step aside at the right moment.
Components
- Guided conversation
- The assistant asks a few qualifying questions in the client's tone and understands both text and voice messages, writing structured answers to the CRM.
- Personalised landing page
- A page assembled from the lead's answers, showing the relevant details, so the customer sees something specific to them rather than a generic brochure.
- Follow-up and stop rules
- Scheduled nudges when the lead goes quiet, with explicit rules for when to stop: the lead asks, a limit is reached, or the conversation isn't progressing.
- Human handoff
- At the agreed moment the conversation and a summary are passed to a named salesperson, who continues with the qualification already done.
Status
This is a proposed capability, shown as a demonstration with fictional data. Its parts build on assistant work I have done, including intent handling, structured extraction and CRM access through tools, but the flow as a whole has not been delivered to a client.
Design goals
- Design goal: every lead gets a first response and a clear next step
- Design goal: a person joins with the context already collected
- Design goal: the assistant stops when the lead asks or the rules say so
Tools
WhatsApp Business Platform, Fireberry, LLM-based assistant, Webhooks and custom APIs