Who should use the Automate lead research workflow?
Teams or solo builders working on marketing tasks who want a repeatable process instead of one-off tool experiments.
AI Workflow · Marketing
Practical execution plan for automate lead research with clear steps, mapped tools, and delivery-focused outcomes.
Deliverable outcome
Sales team receives a ready-to-act-upon list of high-priority leads with full context, updated weekly.
30-90 minutes
Includes setup plus initial result generation
Free to start
You can swap tools by pricing and policy requirements
Sales team receives a ready-to-act-upon list of high-priority leads with full context, updated weekly.
Use each step output as the input for the next stage
Step map
Instead of relying on a single generic AI model, this pipeline connects specialized tools to maximize quality. First, you'll use HubSpot AI (Breeze) to a clear, machine-readable icp and scoring model that will drive all lead sourcing and prioritization. Then, you pass the output to Zapier to a steady stream of raw leads from 2-3 sources, automatically collected and deduplicated in a central repository. Then, you pass the output to Clay to every lead has a complete, verified contact profile with at least 80% field completion, including email and phone. Then, you pass the output to HubSpot AI (Breeze) to a prioritized list of leads ranked by likelihood to convert, with automated routing to sales or nurture sequences. Then, you pass the output to Findymail to lead database remains >95% accurate and fresh, with invalid contacts removed and duplicates merged. Finally, Make is used to sales team receives a ready-to-act-upon list of high-priority leads with full context, updated weekly.
Define Ideal Customer Profile (ICP) and Lead Scoring Criteria
A clear, machine-readable ICP and scoring model that will drive all lead sourcing and prioritization.
Set Up Automated Lead Sourcing from Multiple Channels
A steady stream of raw leads from 2-3 sources, automatically collected and deduplicated in a central repository.
Enrich and Append Data for Each Lead
Every lead has a complete, verified contact profile with at least 80% field completion, including email and phone.
Score and Prioritize Leads Automatically
A prioritized list of leads ranked by likelihood to convert, with automated routing to sales or nurture sequences.
Validate and Cleanse Lead Data Periodically
Lead database remains >95% accurate and fresh, with invalid contacts removed and duplicates merged.
Deliver Final Lead List to Sales Team
Sales team receives a ready-to-act-upon list of high-priority leads with full context, updated weekly.
Start by documenting the firmographic, technographic, and behavioral attributes of your best customers. Translate these into a weighted scoring model (e.g., company size, industry, job title, engagement signals). This step ensures every subsequent automation filters for quality, not just quantity.
Why HubSpot AI (Breeze): HubSpot AI (Breeze) offers predictive lead scoring and autonomous prospecting, which directly supports defining ICP and scoring criteria within a CRM environment.
Configure data connectors to pull prospects from LinkedIn Sales Navigator, industry databases (e.g., ZoomInfo, Apollo), and web scraping sources (e.g., BuiltWith). Use API-based triggers to run daily or weekly imports, deduplicating against your CRM. This creates a continuous inflow of raw leads.
Why Zapier: Zapier is a leading automation platform that can connect multiple lead sourcing tools (e.g., Apollo, ZoomInfo) to centralize lead capture from various channels.
Run each raw lead through enrichment APIs (e.g., Clearbit, Hunter, Lusha) to fill missing fields: verified email, phone, LinkedIn URL, company revenue, and recent news. Append enrichment results back to the lead record. This step transforms anonymous contacts into actionable prospects.
Why Clay: Clay specializes in lead enrichment and can append data from multiple APIs, making it ideal for enriching lead records with additional information.
Apply the scoring matrix from Step 1 using a rules engine or AI model (e.g., in HubSpot, Salesforce, or a no-code tool like Clay). Set up automated actions: leads above threshold move to 'hot' list, others go to 'nurture' or 'archive'. This ensures sales only sees the best prospects.
Why HubSpot AI (Breeze): HubSpot AI (Breeze) includes predictive lead scoring, which is exactly what is needed to automatically score and prioritize leads within a CRM.
Schedule weekly or monthly automated checks to re-verify email deliverability, detect role changes (e.g., via LinkedIn scraping), and remove duplicates. Use tools like NeverBounce for email re-verification and Dedupe.io for CRM cleanup. This prevents wasted outreach on stale data.
Why Findymail: Findymail provides email discovery and LinkedIn scraping, which can help validate and cleanse lead data by finding accurate contact information.
Export the scored, enriched, and validated leads into a shared CRM view or a Google Sheet that sales can access. Include a summary dashboard showing total leads, average score, and source breakdown. Send an automated notification (e.g., Slack or email) with the top 10 leads of the week.
Why Make: Make enables cross-platform data synchronization and automated reporting, which can deliver the final lead list to CRM, reporting tools, and notification platforms like Slack.
§ Before you start
Teams or solo builders working on marketing tasks who want a repeatable process instead of one-off tool experiments.
No. Start with the top pick for each step, then replace tools only if they do not fit your pricing, compliance, or output needs.
Open the mapped task page and compare top options side by side. Prioritize output quality, integration fit, and predictable cost before scaling.
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