12 Hours Saved Every Week: How We Automated Lead Enrichment for a SaaS Team

The Setup: A mid-market B2B SaaS company with 3 SDRs who were spending their mornings manually enriching leads instead of selling.

The Before State

Every morning at 8 AM, three sales development reps logged into their CRM to find 40-60 new inbound leads from the previous day. Good news, right?

Not quite.

What followed was a 2-hour ritual nobody enjoyed:

1. Open lead record in HubSpot
2. Copy company domain
3. Search LinkedIn for company page
4. Manually add: employee count, industry, headquarters location
5. Google the company to find funding status
6. Search LinkedIn again to find the lead's actual title and seniority
7. Update CRM with all findings
8. Mark lead as "enriched" and ready for outreach
9. Repeat 40-60 times

Total time investment: 6 hours per day (2 hours × 3 SDRs) = 30 hours per week on pure data entry.

At an average SDR salary of $60,000/year, that's roughly $900/week in labor cost just to make leads usable.

And that's before we talk about the opportunity cost. According to MechaBee's 2025 marketing research, marketers waste an average of 328 hours per year duplicating work — and this team was on track to exceed that significantly.

The Challenge

The VP of Sales approached us with three constraints:

1. Budget: No $50K/year data enrichment platform budget
2. Tools: They already had HubSpot and weren't switching
3. Timeline: Needed results within 2 weeks, not 2 months

The typical solution would be Clearbit or ZoomInfo. But at roughly $0.75 per enrichment, enriching 1,000 leads per month would cost $750-900/month minimum — and that's assuming perfect data quality.

Plus, these tools don't solve the workflow problem. They just automate the lookup. The SDRs would still need to manually trigger enrichments and review the data.

The Solution

We built a three-stage automated enrichment pipeline using tools they already had (plus one free API):

Stage 1: Instant Company Enrichment (Power Automate + Clearbit Free Tier)

When a new lead enters HubSpot:

• Trigger: New contact created
• Action: Extract company domain from email
• API Call: Clearbit Company API (free tier: 20 requests/day)
• Fallback: Hunter.io domain search (free tier: 50 requests/month)
• Update HubSpot with: company size, industry, location, tech stack

Implementation time: 3 hours
Cost: $0/month (stayed within free tiers)

Stage 2: LinkedIn Profile Enrichment (OpenClaw + Apify)

For leads without complete job title data:

• Trigger: Contact marked as "needs enrichment"
• OpenClaw agent orchestrates:
  • Apify LinkedIn scraper finds profile
  • Extracts current title, seniority level, tenure
  • Validates against common job title patterns
  • Updates HubSpot custom fields

Implementation time: 5 hours
Cost: $49/month (Apify actor usage)

Stage 3: Lead Scoring & Routing (HubSpot Workflows)

After enrichment completes:

• Calculate lead score based on:
  • Company size (50-500 employees = +20 points)
  • Industry match (SaaS, fintech, consulting = +30 points)
  • Seniority (Director+ = +25 points)
  • Tech stack alignment (+15 points if using Salesforce or HubSpot)
• Auto-assign to appropriate SDR based on territory and availability
• Send Slack notification with enriched lead summary

Implementation time: 2 hours
Cost: $0 (native HubSpot functionality)

The Results

Week 1 after go-live:

• 96% of leads auto-enriched within 5 minutes of entering CRM
• 4% required manual review (unusual job titles, private companies)
• Zero hours spent on manual data entry by SDRs

After 1 month:

• Time saved: 12 hours/week → 48 hours/month
• Cost avoided: ~$720/month in SDR labor (12 hrs/week × 4 weeks × $15/hr blended cost)
• Tool cost: $49/month
• Net monthly savings: $671
• Annual ROI: $8,052 saved for a $588/year investment = 1,369% ROI

But the numbers don't tell the full story.

The Hidden Wins

SDR morale improved dramatically. One rep told the VP: "I forgot what it's like to start my day actually selling instead of playing detective on LinkedIn."

Lead response time dropped from 18 hours to 23 minutes. Leads were enriched, scored, and assigned before the SDRs even saw them.

Data quality improved. Humans make typos. APIs don't. The error rate on company data dropped from ~12% to <2%.

Sales leadership got better visibility. For the first time, they could filter their pipeline by accurate firmographics and see which company profiles actually converted.

Lessons Learned

What Worked

1. Start with free tiers. We tested the entire workflow on Clearbit and Hunter.io's free plans before committing to paid tools.

2. Orchestration > individual tools. OpenClaw as the coordinator meant we could swap out data providers without rebuilding workflows.

3. Prioritize accuracy over completeness. We enriched 96% of leads automatically but flagged the 4% edge cases for human review. That's better than enriching 100% with 20% garbage data.

What Didn't Work (At First)

LinkedIn scraping was fragile. Our first attempt used a brittle web scraper that broke every time LinkedIn updated their HTML. Switching to Apify's maintained actor solved this.

Lead scoring was arbitrary. Our initial scoring model was based on guesses. After 2 weeks, we revised it based on actual conversion data and the model got 30% more accurate.

We over-automated notifications. The first version sent a Slack message for every single enriched lead. The SDRs muted the channel after day 1. We changed it to send a daily digest instead.

Your Turn: How to Implement This

If you're drowning in manual lead enrichment, here's your starting point:

Week 1: Audit & Map

• Track how much time your team actually spends on enrichment (use a timer, not estimates)
• List the data fields you're manually filling in
• Identify which fields actually matter for qualification vs. "nice to have"

Week 2: Build the Basics

• Set up a Power Automate (or Zapier) flow for company enrichment
• Start with free API tiers to prove the concept
• Test with 50 leads before going live

Week 3: Add Intelligence

• Layer in lead scoring based on enriched data
• Build auto-assignment rules
• Add human-in-the-loop for edge cases

Week 4: Measure & Refine

• Compare time spent before/after
• Track data accuracy
• Survey your team: "Is this actually better?"

The whole project took us 10 hours to build and saved 12 hours per week. Payback period: less than one week.

The Bottom Line

Lead enrichment is the perfect candidate for automation because:

1. It's repetitive (same 8 steps for every lead)
2. It's rules-based (if domain exists, look up company data)
3. It's high-volume (happens dozens of times per day)
4. It's low-judgment (APIs can do 95% of it)

Your SDRs didn't go to sales training to become LinkedIn detectives. Let the robots handle the busywork.

According to DemandScience's 2026 State of Performance Marketing report, 25% of marketing budget is wasted on efforts that fail to drive outcomes. Manual lead enrichment is a textbook example.