Function: Lead capture
Referral Form Intake
Deployment Brief
Start with referrer, referred person, relationship, permission, need, fit, attribution, owner, duplicate status, and next step.
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 referral form intake workflow captures who made the referral, who was referred, why the connection matters, whether outreach is permitted, and what should happen next. AI can structure the context and prepare owner tasks, but a person should review consent, sensitive context, reward eligibility, attribution, and warm-introduction language.
TL;DR
A referral form intake workflow captures who made the referral, who was referred, why the connection matters, whether outreach is permitted, and what should happen next. AI can structure the context and prepare owner tasks, but a person should review consent, sensitive context, reward eligibility, attribution, and warm-introduction language.
What is referral form intake?
Referral Form Intake 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 customer refers a peer at another company and says they are struggling with missed lead follow-up. The workflow checks referrer relationship, permission to contact, referred company, need, urgency, duplicate CRM status, and reward rule. It prepares a warm-introduction task for the account owner and flags reward eligibility for review.
What decision rules should govern this workflow?
- Require permission to contact or a clear introduction path.
- Capture why the referral is relevant, not just contact details.
- Deduplicate against existing account and partner records.
- Route attribution, rewards, and strategic referrals to review.
- Do not send outreach that implies endorsement beyond what the referrer provided.
What are the implementation steps?
1. Trigger: A customer, partner, employee, or advocate submits a referral form or sends a referral message. 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 referral owner reviews permission to contact, sensitive context, strategic referrals, reward eligibility, attribution disputes, duplicate records, and warm-introduction language before outreach. 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
- Referrer name, relationship, and contact details
- Referred person, company, role, and contact details
- Permission to contact and preferred introduction path
- Referral reason, need, urgency, and fit evidence
- Reward, attribution, partner, or source rules
- Duplicate account/contact match and assigned owner
Expected outputs
- Structured referral record
- Fit and context summary
- Owner task for warm introduction or outreach
- Consent or attribution review flag
- Referral reward or partner-credit review task
Human review point
A referral owner reviews permission to contact, sensitive context, strategic referrals, reward eligibility, attribution disputes, duplicate records, and warm-introduction language before outreach.
Risks and stop rules
- Contacting someone who did not consent
- Losing the relationship context that makes the referral valuable
- Misattributing referral credit
- Creating duplicate accounts
- Using awkward or over-automated warm introduction language
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 referrer, referred person, relationship, permission, need, fit, attribution, owner, duplicate status, and next step.
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 Referral Tracking
- AI Workflow for Partner Referral Management
- AI Workflow for Warm Introduction Tracking
- AI Workflow for Inbound Lead Qualification
- AI Workflow for Priority Lead Routing
Measurement plan
- Referrals with permission captured
- Referral-to-first-touch time
- Duplicate referral rate
- Warm introductions completed
- Referral attribution disputes
- Referral-to-opportunity conversion
What not to automate
- Do not contact referred people without permission or review.
- Do not approve rewards or attribution automatically.
- Do not invent relationship context.
- Do not send sensitive or overly familiar outreach without owner approval.
FAQ
What is referral form intake?
It captures referral context, permission, fit, attribution, and next step so referral leads can be handled carefully.
What should AI prepare from a referral?
AI can summarize the relationship, referral reason, fit, urgency, permission status, duplicate status, owner, and suggested next step.
What should stay under human review?
Consent, sensitive context, reward eligibility, attribution, strategic referrals, and warm-introduction language should stay under review.
What is the simplest first version?
Start with a referral form that captures referrer, referred contact, relationship, permission, need, owner, and attribution.
How should referral intake be measured?
Track permission completion, first-touch time, duplicates, introductions completed, attribution disputes, and referral-to-opportunity conversion.