Data Enrichment Workflow for Lead Scoring and Segmentation
Marketing AutomationintermediateClaude 3.5 Sonnet or GPT-4o. Claude excels at structured, multi-part workflows and provides clearer implementation frameworks. GPT-4o offers faster processing for large prompts and excellent integration recommendations. Both handle complex B2B marketing logic equally well.
When to Use This Prompt
Use this prompt when you're building or redesigning your lead management infrastructure and need a comprehensive data enrichment strategy. It's ideal for marketing ops leaders planning CRM optimization, sales enablement teams improving lead quality, or teams preparing for a marketing automation platform migration.
The Prompt
You are a marketing operations expert helping design a data enrichment workflow. I need to enrich our [COMPANY_TYPE] customer database with behavioral and firmographic data to improve lead scoring and segmentation.
## Current Situation
- We have [NUMBER] contacts in our CRM with basic fields: name, email, company, title, phone
- We use [CRM_PLATFORM] as our primary system
- Our sales team needs better lead prioritization
- We want to segment by [BUSINESS_GOAL: e.g., "company size and industry vertical"]
## Data Enrichment Goals
1. Identify high-intent signals from web behavior and engagement
2. Append firmographic data (company size, revenue, industry, growth rate)
3. Detect buying committee members and decision-maker roles
4. Flag accounts matching our ideal customer profile (ICP)
## Required Output
Provide a step-by-step data enrichment workflow that includes:
### 1. Data Sources
Recommend 3-5 specific data sources or tools that integrate with [CRM_PLATFORM]. For each, explain:
- What data it provides
- Integration method
- Cost considerations
- Data freshness/update frequency
### 2. Enrichment Sequence
Outline the optimal order for enriching data fields, explaining dependencies and why sequence matters.
### 3. Scoring Model
Design a lead scoring framework that weights enriched data points. Include:
- Explicit signals (firmographic match to ICP)
- Implicit signals (engagement, website behavior)
- Scoring formula or point allocation
- Threshold for sales handoff
### 4. Segmentation Strategy
Create 4-5 audience segments based on enriched data, with:
- Segment name and definition
- Size estimate
- Recommended marketing treatment
- Success metrics
### 5. Implementation Roadmap
Provide a 90-day implementation plan with:
- Week 1-2 priorities
- Week 3-4 milestones
- Week 5-12 optimization phases
- Resource requirements
- Risk mitigation
### 6. Governance and Maintenance
Explain how to:
- Keep enriched data current
- Monitor data quality
- Handle duplicates and conflicts
- Comply with privacy regulations
Format the workflow as a practical, actionable document that a marketing ops manager could present to leadership and execute immediately.
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Tips for Best Results
- 1.Replace all [BRACKETS] with your actual company details before running the prompt. Specificity drives better recommendations—generic inputs produce generic outputs.
- 2.If your CRM isn't mentioned in the output, ask a follow-up: 'How would this workflow differ for [YOUR_CRM]?' to get platform-specific integration guidance.
- 3.Request the scoring model in spreadsheet format by adding: 'Format the lead scoring model as a table I can import into Excel for testing different thresholds.'
- 4.Test the enrichment workflow on a small segment first (500-1000 contacts) before full rollout. Ask: 'What metrics should I track during a 2-week pilot to validate this approach?'
Example Output
## Data Enrichment Workflow for SaaS B2B Company
### 1. Data Sources
**ZoomInfo** - Provides company size, revenue, employee count, industry, tech stack. Integrates via API with Salesforce. ~$5K-15K annually. Updated monthly.
**6sense** - Intent data showing buying signals, account engagement, industry trends. API integration. ~$50K+ annually. Real-time updates.
**Apollo.io** - Email verification, phone numbers, decision-maker identification. Native Salesforce integration. ~$500/month. Weekly updates.
**LinkedIn Sales Navigator** - Decision-maker identification, role verification, engagement tracking. Manual + API. $99/month per user. Real-time.
### 2. Enrichment Sequence
1. **Phase 1**: Append firmographic data (ZoomInfo) - establishes ICP match
2. **Phase 2**: Verify contact accuracy (Apollo) - ensures deliverability
3. **Phase 3**: Layer intent signals (6sense) - identifies buying readiness
4. **Phase 4**: Identify decision-makers (LinkedIn) - maps buying committee
### 3. Scoring Model
- ICP Match (40 points): Company size match (15) + Industry match (15) + Revenue fit (10)
- Engagement (35 points): Email opens (10) + Website visits (10) + Content downloads (15)
- Intent (25 points): 6sense buying signal (15) + Decision-maker title (10)
- **Threshold**: 60+ points = Sales qualified lead
### 4. Key Segments
**Enterprise High-Intent**: 500+ employees, matching industry, active intent signals. Treatment: Direct sales outreach.
**Mid-Market Growth**: 50-500 employees, revenue $10M-$100M, moderate engagement. Treatment: Account-based marketing.
**SMB Explorers**: <50 employees, early-stage engagement, high growth potential. Treatment: Nurture campaigns.
### 5. 90-Day Roadmap
**Weeks 1-2**: Select and contract data providers, plan API integrations.
**Weeks 3-4**: Implement ZoomInfo and Apollo, enrich existing database.
**Weeks 5-8**: Deploy intent data, build scoring model, test in sandbox.
**Weeks 9-12**: Launch to production, monitor quality, optimize thresholds.
### 6. Governance
- Monthly data quality audits (duplicate rates, field completion)
- Quarterly ICP refinement based on win/loss analysis
- GDPR/CCPA compliance: Maintain consent records, honor opt-outs
- Establish data steward role for ongoing maintenance
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Get the Full AI Marketing Learning Path
Courses, workshops, frameworks, daily intelligence, and 6 proprietary tools — built for marketing leaders adopting AI.
Trusted by 10,000+ Directors and CMOs.