Client Snapshot

Introductions GIF

  • Industry: Multi-vertical B2B sales
  • Product: Advanced data analytics solutions for enterprise accounts ($5–10M+ revenue)
  • Buyer: Head of Sales + outbound SDRs/BDRs.

Key results summary

  • 10% sales lift
  • <3% false positives
  • 500–1,000 leads/day
  • $0.06 per enriched lead

The Challenge

Challenged GIF

Selling into high-stakes enterprise accounts demands more than surface-level data. Off‑the‑shelf tools (Clay/Apollo) missed critical context like:

  • Hiring signals (open roles)
  • Executive/media/webinar appearances
  • Org-level figures (e.g., analyst headcount)

Without this context, outreach felt generic, research was slow, and strong prospects slipped through.

“We tried existing platforms, but the costs were too high and the answers were often not good enough.”

The Goal

Build a fast, flexible enrichment system (in under one month) that:

  • Pulls company and contact intelligence beyond basic firmographics.
  • Standardizes outputs for immediate use in outreach and CRM.
  • Fits current workflows (Google Sheets + CRM).
  • Is easy to run at scale and simple to self-host.

Solution at a Glance

Homer GIF

A production-grade n8n pipeline that turns a LinkedIn URL or company domain into a standardized, data-rich profile—ready for outreach, logging, and alerts.

  • Inputs: LinkedIn URL / domain pasted into Google Sheets
  • Sources: Apify scrapers, targeted research via AI, curated public web data
  • Outputs: Hiring signals, appearances, org insights, normalized job titles, deduped company/contact fields
  • Operations: Error handling, retries with backoff, run logs, Slack alerts

System architecture diagram — from Sheets to n8n to enrichment to CRM Sheets → n8n Orchestrator → Data Sources (Apify/AI) → Normalizer → CRM/Sheets → Alerts

Lightning-Fast Process

Ship Timeline — prototype, iterate, standardize, ship

Four sprints: prototype in 48h, two rapid iterations, standardize and ship.

  1. Clickable Demo in 48 Hours
    • Delivered a working prototype in 2 days to test on live leads.
    • Immediate feedback on speed, fields, and output format.
  2. Rapid Iteration for True Fit
    • 2–3 touchpoints/week; three major iterations.
    • Lightweight dashboard controlled from Google Sheets—paste a LinkedIn URL and run.
    • Each iteration shipped in ~3–4 days; final milestone reached 2 weeks early.
  3. Standardize & Ship
    • Clean, reusable n8n workflow (JSON) for self-hosting.
    • Dashboard for smoother interaction.
    • Loom walkthroughs + quickstart docs.
    • Seamless handoff—team started using it the same day.

Results

  • Sales increased by 10% within the first month.
  • Faster, higher-quality outreach with richer prospect understanding.
  • Delivery time cut in half versus the initial plan.
Before (Clay/Apollo) After (Custom Automation)
Surface-level data Deep enrichment (hiring, appearances, org signals)
Slow, manual enrichment Automated in under two minutes per lead
Generic lists Standardized, actionable profiles
Missed prospects Sharper targeting and stronger follow-up

Before vs After — depth and speed of enrichment. Better context, faster research, clearer targets.

Performance & Reliability

  • One-click runs from Google Sheets; standardized JSON/CSV outputs.
  • Retries with exponential backoff; Slack alerts on failures.
  • Logging and run history for quick troubleshooting.
  • Designed to scale from hundreds to thousands of leads with batching and rate-limit awareness.

Reliability & monitoring — retries, alerts, logs. Reliability built-in: retries, alerts, and traceable runs.

Compliance & Data Ethics

  • Public web sources only; robots-aware collection, no credentialed scraping.
  • Rate-limit friendly; respects provider ToS.
  • Optional deployment in client VPS or on self-hosted n8n.

Compliance & data ethics summary. Transparent collection, respectful automation.

Deliverables

Jump

  • n8n workflow (JSON) for cloud or self-hosted deployment.
  • Custom dashboard for reviewing leads and inputting new prospects.
  • Field mapping and data dictionary for CRM consistency.
  • Loom training videos and quickstart documentation.

Tech Stack

  • Orchestration: n8n
  • Data: Apify, curated public web sources
  • AI: Targeted research and synthesis
  • Ops: Google Sheets, webhooks, retries, logging, Slack alerts, HTML, CSS, JS

The Client Says

“When we started, we didn’t really quite know what the end product should look like… but Noah made sense of our rough ideas, built exactly what we needed, and delivered more than we expected. The iterative process was a lifesaver.”

Like These Results?

Let’s build your enrichment pipeline and start improving conversions this month.

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