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AI Automation2024

Lead Automation System

From chaos to conversion in zero clicks

Client
B2B SaaS Company (50-person sales team, $5M ARR)
Role
Automation Architect
Duration
6 weeks
Year
2024
25h/week
Time Saved
4h → 8min
Response Time
+42%
Lead Quality
1.4x
Close Rate

Overview

A fast-growing SaaS company hit a painful growth bottleneck: their sales team was drowning in leads but couldn't convert them. With 200+ inbound leads weekly from multiple sources (website, LinkedIn ads, webinars, referrals), their 5-person SDR team spent 6+ hours daily just copying data between tools. The VP of Sales reached out desperate for a solution before they had to hire 3 more SDRs just to manage the chaos.

!

The Challenge

Leads came in via Typeform, HubSpot forms, Calendly bookings, and LinkedIn, ending up scattered across platforms. SDRs manually copied each lead into Airtable, then Googled the company, checked LinkedIn for employee count, and guessed whether they were qualified. Average response time was 4 hours (industry best practice: <5 minutes). With no scoring system, reps wasted time on tiny companies while enterprise leads went cold. Two SDRs had already quit from burnout.

The Solution

I built a central nervous system for their leads using Make as orchestration, Airtable as the single source of truth, and AI for intelligent routing. Every lead—regardless of source—flows through the same pipeline: captured → enriched with Clearbit (company size, tech stack, funding) → scored by GPT-4 (analyzes fit based on ICP criteria) → routed to the right rep → Slack notification with full context. Reps now get leads in under 5 minutes with all the research done for them.

The Process

1

Lead Source Audit & Mapping

Shadowed 3 SDRs for a day, documenting every tool and manual step. Discovered they were using 7 different platforms with zero integration. Mapped out the ideal workflow: capture → enrich → score → route → notify. Got buy-in from VP Sales on success criteria: <5min response time, 80%+ lead quality score.

2

Airtable Schema & ICP Scoring Model

Built Airtable base with custom fields for enriched data (company size, industry, tech stack, funding stage). Created scoring rubric with VP Sales: 10 points for 50+ employees, 8 points for VC-backed, 5 points for using competitor tools, etc. Target: 30+ points = hot lead.

3

Make Automation Workflows

Built 8 Make scenarios covering all lead sources. Each scenario: 1) Captures lead data 2) Enriches via Clearbit API 3) Calls GPT-4 API with scoring prompt 4) Routes based on territory rules 5) Creates HubSpot contact 6) Sends Slack notification with prospect research summary. Added error handling for API failures with fallback to manual review.

4

Testing, Training & Launch

Ran parallel systems for 2 weeks—automation running alongside manual process. Caught edge cases (international leads without Clearbit data, leads from mobile forms missing fields). Trained SDR team on new Airtable views and Slack workflow. Full cutover after hit 98% accuracy vs manual scoring.

Tech Stack

MakeAirtableSlack APIOpenAIClearbitHubSpot
We were about to hire more SDRs just to manage lead chaos. This system freed up our team to focus on closing instead of data entry. The response time improvement alone has made a noticeable difference in our pipeline.
C
Client feedback
VP Sales
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