# Lead Qualification & Enrichment — AI Workflow export
# https://invitationbuddy.com/workflows/lead-qualification-enrichment
schema_version: "1.0"
exported_at: "2026-08-16T10:16:01+00:00"
source: "https://invitationbuddy.com/workflows/lead-qualification-enrichment"
workflow:
  name: "Lead Qualification & Enrichment"
  slug: "lead-qualification-enrichment"
  version: "1.0.0"
  tagline: "Score, enrich and route every inbound lead within seconds"
  summary: "Fires on lead creation, enriches from public sources, scores against your ICP and routes to the right owner with a briefing note attached."
  description: |-
    Inbound leads decay fast. This pipeline enriches and scores each one within seconds of creation, so the right rep gets the right lead with context already attached rather than a name and an email.
    
    It is fully automated by design — the judgement lives in the scoring rubric, which a human owns and tunes.
  category: Sales
  type: API Pipeline
  difficulty: intermediate
  automation_level: fully_automated
  pricing: paid
  language: en
  trigger:
    type: crm_event
    detail: New lead created
  input_types:
    - email
    - api
    - json
  output_types:
    - dataset
    - summary
  author: null
  company: null
  last_updated: "2026-07-07"
overview:
  purpose: |-
    Inbound leads decay fast. This pipeline enriches and scores each one within seconds of creation, so the right rep gets the right lead with context already attached rather than a name and an email.
    
    It is fully automated by design — the judgement lives in the scoring rubric, which a human owns and tunes.
  business_value: "Cuts lead response time from hours to seconds and removes manual research from every rep's day."
  expected_outcome: "Every lead scored, enriched and routed with a briefing note, within seconds of arriving."
  problems_solved:
    - Reps spend the first ten minutes of every lead researching the company
    - Hot leads sit in a queue behind cold ones
    - Scoring is inconsistent between reps
    - "CRM records stay thin, so reporting is unreliable"
  ideal_users:
    - Sales teams with meaningful inbound volume
    - RevOps teams standardising qualification
    - Founders handling their own pipeline
  benefits:
    - Response time measured in seconds
    - Consistent scoring against one rubric
    - Reps open a lead with context already there
    - CRM data quality improves as a side effect
  limitations:
    - Enrichment quality depends entirely on the data provider
    - The scoring rubric needs periodic retuning as the ICP shifts
    - Enriching personal data has real GDPR implications — check your lawful basis
    - "Junk in, junk out: bad form data still produces bad scores"
  success_metrics:
    - Median time from lead creation to routed
    - Percentage of leads correctly routed first time
    - Meeting booked rate versus the manual baseline
    - Cost per enriched lead
metrics:
  estimated_minutes: 4
  estimated_cost: 0.18
  cost_currency: USD
  estimated_tokens: 6000
  success_rate: 94
  automation_percent: 95
  human_review_percent: 5
industries:
  - SaaS
  - Finance
  - Recruitment
  - Marketing
tags:
  - Enterprise Ready
  - "Real-time"
  - High ROI
  - GDPR Aware
ai_skills:
  - Data Analysis
  - Reasoning
  - Function Calling
tools:
  -
    name: ChatGPT
    role: primary
    required: true
    url: "https://invitationbuddy.com/ai-directory/chatgpt"
models: []
integrations:
  -
    name: OpenAI
    kind: ai_provider
    auth_type: api_key
    required: true
  -
    name: HubSpot
    kind: crm
    auth_type: oauth
    required: true
  -
    name: Salesforce
    kind: crm
    auth_type: oauth
    required: false
  -
    name: Webhook
    kind: protocol
    auth_type: webhook
    required: false
  -
    name: REST API
    kind: protocol
    auth_type: api_key
    required: false
prerequisites:
  -
    kind: api_key
    label: LLM API key
    detail: For the scoring and briefing steps.
    required: true
  -
    kind: account
    label: CRM with webhooks
    detail: "HubSpot, Salesforce or Pipedrive."
    required: true
  -
    kind: account
    label: Enrichment provider
    detail: "Clearbit, Apollo or Clay."
    required: true
  -
    kind: permission
    label: Lawful basis for enrichment
    detail: Confirm your GDPR/CCPA position before enriching personal data.
    required: true
steps:
  -
    number: 1
    title: Lead created trigger
    description: CRM webhook fires with the raw form submission.
    tool: HubSpot
    input: Lead record
    output: Job payload
    estimated_minutes: 1
    difficulty: intermediate
    automation: auto
    manual_review: false
  -
    number: 2
    title: Normalise and deduplicate
    description: "Clean the email and domain, then check whether this contact or account already exists."
    input: Raw lead
    output: Clean lead + duplicate flag
    estimated_minutes: 1
    difficulty: intermediate
    automation: auto
    manual_review: false
    warnings:
      - "Merge rather than create when a duplicate is found, or reporting drifts immediately"
  -
    number: 3
    title: Enrich from public sources
    description: "Pull firmographics: size, industry, funding, tech stack, location."
    tool: Clearbit
    input: Domain
    output: Firmographic record
    estimated_minutes: 1
    difficulty: intermediate
    automation: auto
    manual_review: false
  -
    number: 4
    title: Score against the ICP
    description: "Apply the scoring rubric and produce a score with written justification, so a rep can challenge it."
    model: "GPT-4o"
    prompt: |-
      Score this lead against our ideal customer profile.
      
      ICP:
      {{icp_definition}}
      
      Lead:
      {{enriched_lead}}
      
      Return JSON:
      {
        "score": 0-100,
        "tier": "hot|warm|cold",
        "reasoning": "two sentences on why",
        "disqualifiers": ["any hard blockers"],
        "talking_points": ["three specific angles for the first message"]
      }
      
      Be strict. A lead that only partially matches is warm, not hot.
    input: Enriched lead + ICP rubric
    output: Score + reasoning
    estimated_minutes: 1
    difficulty: intermediate
    automation: auto
    manual_review: false
    tips:
      - "Ask for the reasoning, not just the number — it is what lets you debug a rubric that has drifted"
  -
    number: 5
    title: Write the briefing note
    description: Produce a short brief the rep reads before their first touch.
    model: "GPT-4o"
    input: Scored lead
    output: Rep briefing
    estimated_minutes: 1
    difficulty: intermediate
    automation: auto
    manual_review: false
  -
    number: 6
    title: Route to owner
    description: "Assign by territory, tier and capacity, then notify in Slack with the brief attached."
    tool: Slack
    input: Scored lead + brief
    output: Assigned lead + notification
    expected_result: "The right rep notified with context, within seconds of the form submit."
    estimated_minutes: 1
    difficulty: intermediate
    automation: auto
    manual_review: false
prompts:
  -
    title: Score against the ICP
    kind: user
    body: |-
      Score this lead against our ideal customer profile.
      
      ICP:
      {{icp_definition}}
      
      Lead:
      {{enriched_lead}}
      
      Return JSON:
      {
        "score": 0-100,
        "tier": "hot|warm|cold",
        "reasoning": "two sentences on why",
        "disqualifiers": ["any hard blockers"],
        "talking_points": ["three specific angles for the first message"]
      }
      
      Be strict. A lead that only partially matches is warm, not hot.
    variables:
      - icp_definition
      - enriched_lead
    model_hint: "GPT-4o"
use_cases:
  -
    title: Inbound demo requests
    description: Route demo requests to the right rep with account context already gathered.
    industry: SaaS
    outcome: Faster first response
  -
    title: "Event lead follow-up"
    description: Process a conference list overnight so outreach starts the next morning.
    industry: Marketing
    outcome: "Same-week follow-up"
  -
    title: Partner referrals
    description: Score referred accounts consistently rather than by relationship.
    industry: Finance
    outcome: Consistent qualification
faq:
  -
    question: "Is this GDPR compliant?"
    answer: "The workflow can be, but compliance depends on your lawful basis for enriching personal data and on your provider's terms. Confirm both before switching it on in the EU or UK."
  -
    question: "What if the scoring is wrong?"
    answer: "That is why step 4 returns written reasoning. Sample a week of scores against actual outcomes and tune the rubric — the model applies your definition, so a bad score usually means a vague ICP."
  -
    question: "Can it work without a paid enrichment provider?"
    answer: "Partially. You lose firmographics, which is most of the signal. Domain-only heuristics are noticeably weaker."
