Function: Lead capture
Social Inquiry Lead Capture
Deployment Brief
Start with one social inbox. Capture platform, message, profile, company, topic, consent, safe reply, and owner review for public or sensitive replies.
Related Field Report
- Speed-to-lead AI workflow: A field report on faster lead response without losing evidence, routing, consent, or owner review.
Quick Answer
A social inquiry lead capture workflow turns DMs, comments, and profile messages into structured lead records when the inquiry shows real business context. AI can summarize the message and suggest routing, but a person should review public replies, unclear identity, complaints, pricing questions, sensitive topics, and customer-visible promises.
TL;DR
A social inquiry lead capture workflow turns DMs, comments, and profile messages into structured lead records when the inquiry shows real business context. AI can summarize the message and suggest routing, but a person should review public replies, unclear identity, complaints, pricing questions, sensitive topics, and customer-visible promises.
What is social inquiry lead capture?
Social Inquiry Lead Capture is a lead intake workflow that captures enough context to decide what should happen next. The useful version does not just create a contact record. It records the source, intent signal, consent, owner, duplicate status, and any promise made before follow-up.
Who is this workflow for?
This workflow is for service businesses, agencies, SaaS companies, consultants, construction firms, event teams, and sales teams that receive leads from forms, events, social channels, referrals, or demo requests. It is most useful when speed matters but bad routing wastes sales time.
What breaks in the manual process?
Lead capture breaks when every name looks the same. A badge scan, a referral, a social comment, and a demo request need different handling. Without consent, context, owner, and next step, teams either over-follow up weak leads or miss the leads that were ready to talk.
How does the AI-enabled process work?
AI cleans the record, summarizes the source context, checks duplicates, classifies fit and intent, and suggests the next route. A person still reviews high-value accounts, unclear consent, disqualification, public replies, referral attribution, pricing questions, and any customer-visible promise.
What does this look like in practice?
Example scenario: A LinkedIn commenter asks whether the company helps construction teams with AI workflows. The workflow captures platform, profile, company, message, topic, and prior interaction. It drafts a short public reply inviting a private conversation, flags it for review because it is public, and creates an owner task only after the person confirms interest.
What decision rules should govern this workflow?
- Separate casual engagement, complaint, support issue, and sales inquiry.
- Review public replies before posting.
- Confirm identity and consent before CRM creation when needed.
- Route sensitive, pricing, legal, or complaint topics to a person.
- Do not make service promises in an automated social reply.
What are the implementation steps?
1. Trigger: A social DM, comment, mention, profile inquiry, ad reply, or public thread indicates possible interest or need. 2. Inputs collected: capture contact details, source context, consent, fit evidence, duplicate status, owner, and requested next step. 3. AI/system action: clean the record, summarize intent, enrich context, check duplicates, suggest route, and flag missing evidence. 4. Human review point: A human reviews public replies, unclear identity, complaints, sensitive issues, pricing or service promises, high-value opportunities, and any move from public thread to private sales conversation. 5. Output generated: create the approved CRM record, owner task, follow-up route, safe reply, referral task, or demo routing action. 6. Follow-up or next action: assign owner, log consent, track first response, and measure whether the lead reached the right path.
Required inputs
- Platform, message, thread, and timestamp
- Profile, company, identity match, and prior interactions
- Topic, urgency, sentiment, and service fit
- Consent or permission to move channels
- Public vs private reply context
- Owner, routing rule, and CRM match
Expected outputs
- Inquiry summary and suggested lead status
- Safe reply draft or clarification question
- CRM record or owner task
- Public-reply review flag
- Spam, complaint, or sensitive-topic flag
Human review point
A human reviews public replies, unclear identity, complaints, sensitive issues, pricing or service promises, high-value opportunities, and any move from public thread to private sales conversation.
Risks and stop rules
- Treating spam or casual comments as leads
- Replying publicly with pricing or promises
- Misidentifying the person or company
- Ignoring complaints because they look like inquiries
- Moving conversations to CRM without consent or context
Stop the workflow when consent is missing, source context is too thin, identity is unclear, duplicate ownership conflicts, the route affects a strategic account, or the next action would make a pricing, timing, scope, referral, or public-facing promise.
Best first version
Start with one social inbox. Capture platform, message, profile, company, topic, consent, safe reply, and owner review for public or sensitive replies.
Advanced version
The advanced version connects forms, CRM, enrichment, calendar routing, source attribution, consent, and follow-up performance. It can prioritize and route faster, but it still needs review for strategic accounts, disqualification, attribution, and customer-visible commitments.
Related workflows
- AI Workflow for New Form Submission Response
- AI Workflow for Inbound Lead Qualification
- AI Workflow for Speed To Lead Response
- AI Workflow for Support Escalation Summaries
- AI Workflow for CRM Activity Logging
Measurement plan
- Qualified social inquiries
- Response time
- Public-reply reviews
- Spam or false-positive rate
- CRM records created with context
- Booked conversations from social inquiries
What not to automate
- Do not post public replies with pricing or promises without review.
- Do not scrape private or restricted profile data.
- Do not treat complaints as sales leads.
- Do not create CRM records from weak or unclear identity matches without review.
FAQ
What is social inquiry lead capture?
It structures business-relevant DMs, comments, and social replies into lead or owner tasks when there is enough context.
What should AI capture from a social inquiry?
AI should capture platform, message, profile, company, topic, urgency, sentiment, consent, identity match, and suggested owner.
What should stay under human review?
Public replies, complaints, pricing questions, sensitive topics, unclear identity, and customer-visible promises should stay under review.
What is the simplest first version?
Start with a social inbox workflow that drafts safe replies and routes only qualified inquiries to an owner.
How should social inquiry capture be measured?
Track qualified inquiries, response time, public-reply reviews, false positives, CRM context completion, and booked conversations.