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Client Project

AI Lead Qualification Pipeline

A scheduled system that identifies B2B companies showing signs of data management inefficiency, scores them by urgency and fit, and surfaces only the prospects worth a conversation.

The Problem

What needed solving

The client needed to find B2B companies experiencing data chaos — disorganised spreadsheets, broken reporting, siloed systems.

Doing this by hand meant hours of research each week, inconsistent quality, and leads that sat in an inbox long enough to go cold.

They needed the pipeline to run itself and surface only the most relevant, highest-urgency prospects.

The Build

How the system works

  1. Run on a schedule

    The workflow starts itself at set intervals. No one needs to remember to kick off the research.

  2. Score leads with AI

    Each potential lead is analysed for signals of data management pain — role, company size, industry, and other public indicators — then scored for urgency and fit.

  3. Filter and structure

    n8n drops low-score leads and structures the qualified ones into consistent records: company, contact, score, pain signal, and recommended action.

  4. Report and alert

    Results are written to a Google Sheets dashboard. High-priority leads trigger an immediate Slack notification so the team can act while the signal is fresh.

Stack

Tools used

n8n AI lead scoring Google Sheets Slack API REST APIs
Outcome

What the system delivers

The pipeline runs unattended and delivers qualified leads on schedule with no human input at any stage.

Hours of manual prospecting eliminated. The team moved from research to conversations with prospects that were already scored.

High-priority leads reach the sales team within minutes of entering the pipeline.

Have a process like this?

Tell me what your team keeps doing by hand and I’ll tell you what it would take to automate.