Make.com for Lead Generation: Automated Prospect Research Pipeline (2026)
Define your ideal customer profile (ICP), scrape LinkedIn and company directories with Apify, enrich and score in Make.com, then push qualified leads to HubSpot, Salesforce, or Airtable. This guide walks through a full lead-generation pipeline: Apify for data collection, Make.com for orchestration, enrichment, scoring, and CRM sync. No code required for the workflow — only configuration.
The Pipeline at a Glance
[Schedule / Webhook] → [Apify: Scrape LinkedIn/Directories]
→ [Make: Filter by criteria]
→ [Make: Enrich via Clearbit/Hunter]
→ [Make: Score by ICP]
→ [CRM: Add contact]
→ [Slack: Notify team]
Each step is a Make.com module. Apify supplies raw leads; Make.com transforms and routes them.
Step 1: Apify — Collect Raw Leads
Use Apify Actors for lead sources:
- LinkedIn Company Scraper — Company pages by search, industry, size
- LinkedIn Sales Navigator Scraper — Advanced filters (if you have Sales Nav)
- Company Directory / Crunchbase — Startups, funding, contacts
- Google Maps Scraper — Local businesses with contact info
In Make.com, add Apify: Run Actor. Configure inputs:
- Search query or URL list
- Max results (e.g. 100)
- Proxy: residential recommended for LinkedIn
Store the run ID. Use Apify: Get Dataset Items in the next module to fetch the scraped records.
Step 2: Filter by Criteria
Use a Make.com Iterator over dataset items. Add Filter or Set variable to keep only records that match:
- Company size (e.g. 11–50 employees)
- Industry (e.g. SaaS, fintech)
- Location (country, city)
- Presence of email or contact URL
Drop records that don't match. Pass filtered array to the next step.
Step 3: Enrich with Clearbit or Hunter.io
Clearbit — Domain → company info (employees, industry, tech stack). Use Clearbit Enrichment API.
Hunter.io — Domain → email addresses. Use Hunter Domain Search.
Add HTTP: Make a request in Make.com:
- Clearbit:
GET https://company.clearbit.com/v2/companies/find?domain=example.comwith Bearer token - Hunter:
GET https://api.hunter.io/v2/domain-search?domain=example.com&api_key=KEY
Map response to new fields: company_size, industry, email, confidence. Merge with original lead record.
Add error handling: if enrichment fails, keep the lead with partial data or skip.
Step 4: Score Based on ICP
Use Set variable or Tools > Data Store to define scoring rules. Example:
- +20 if industry = target industry
- +15 if company size in range
- +10 if email found
- +5 if location = target region
Sum the score. Add a Filter to keep only leads with score ≥ 30 (or your threshold). Pass to CRM step.
Step 5: Push to HubSpot, Salesforce, or Airtable
HubSpot — Use Make.com HubSpot module: Create or update contact. Map email, company name, custom properties. Enable deduplication by email.
Salesforce — Use Salesforce module: Create record (Lead or Contact). Map fields. Use duplicate rules in Salesforce or check before create in Make.com.
Airtable — Use Airtable module: Create record. Add to a "Leads" table. Use formula or lookup to avoid duplicates.
Route only scored leads. Optionally add a Router to separate high vs. low scores into different lists or owners.
Step 6: Notify Sales in Slack
Add Slack: Create a message:
- Channel: e.g.
#leads - Text:
New lead: {{company_name}}. Score: {{score}}. {{crm_link}} - Optional: format as block with link to CRM record
Run once per lead or aggregate into a daily digest (use Aggregator to collect, then one Slack message).
Full Scenario Module Breakdown
| # | Module | Purpose |
|---|---|---|
| 1 | Schedule | Trigger weekly or daily |
| 2 | Apify: Run Actor | Scrape LinkedIn/company data |
| 3 | Apify: Get Dataset Items | Fetch scraped records |
| 4 | Iterator | Loop over items |
| 5 | Filter | Keep by company size, industry, location |
| 6 | HTTP: Clearbit/Hunter | Enrich domain |
| 7 | Set variable | Calculate ICP score |
| 8 | Filter | Keep score ≥ threshold |
| 9 | HubSpot/Salesforce/Airtable | Create contact/record |
| 10 | Slack | Notify team |
Add Error handler on critical modules (Apify, enrichment, CRM) to catch failures and optionally retry or alert.
Cost per Lead
- Apify — Compute per Actor run. ~$0.01–0.05 per lead depending on Actor and proxy.
- Make.com — Operations count. Each lead = multiple ops (filter, enrich, CRM, Slack). Paid tier for volume.
- Clearbit/Hunter — Per API call. Free tiers available; scale with usage.
Rough order: $0.05–0.20 per qualified lead at moderate volume, excluding CRM subscription.
Make.com vs n8n vs Manual Lead Gen
| Aspect | Make.com | n8n | Manual |
|---|---|---|---|
| Setup | No code, visual | Low code, self-host or cloud | Spreadsheets, manual search |
| Apify integration | Native | Native | Manual export/import |
| Enrichment | HTTP module | HTTP node | Manual lookup |
| CRM sync | Native HubSpot, Salesforce, etc. | Native + HTTP | Copy-paste |
| Cost | Ops-based | Self-host free, cloud paid | Time only |
| Scalability | Good for 100s–1000s/mo | Same | Limited |
For automated lead gen, Make.com + Apify is a strong no-code combo. See Make.com Apify guide, n8n vs Make, and Make.com review for more.
Begin with one Apify Actor (e.g. LinkedIn Company Scraper) and one enrichment step. Get end-to-end flow working before adding scoring and CRM. Iterate on ICP criteria.
Use LinkedIn Company Scraper or LinkedIn Profile Scraper from the Apify Store. Configure with search terms, industry filters. Use residential proxies for better success. Check Actor docs for input format.
Use email or domain as unique key. In HubSpot/Salesforce, enable 'create or update' to merge duplicates. In Make.com, add a Router to check existing contact before create.
Hunter.io has a free tier with limited searches. For higher volume, use paid plan. Make.com HTTP module works with Hunter API. Same pattern for Clearbit.
Weekly is common for outbound. Daily if you need fresh leads quickly. Balance with Apify and enrichment API limits. Avoid LinkedIn rate limits.
Apify ~$0.01–0.05/lead, Make.com ops, enrichment API costs. Total ~$0.05–0.20 per qualified lead. Scale with volume and enrichment depth.
Yes. n8n has Apify nodes and HTTP for enrichment. Flow structure is similar. Choose based on your team's preference and hosting (n8n self-host vs Make.com cloud).