Growth Engine: Intelligent LinkedIn Prospecting

The Challenge

Outbound sales teams often face a "Volume vs. Quality" paradox. Manual prospecting is slow and unscalable, but standard automation often feels robotic, leads to low response rates, and risks account bans. The client needed a way to:

• Identify Intent: Find prospects based on specific triggers (hiring, funding, or niche keywords).

• Personalize at Scale: Send messages that feel researched, not templated.

• Maintain Safety: Bypass platform limits by simulating natural human browsing patterns.

The Solution (The Criyx Approach)

We developed a proprietary "Growth Intelligence" stack that treats LinkedIn as a structured database for targeted outreach:

1. Precision Scraping: Custom Python-based scripts that extract data from Sales Navigator, filtering by ultra-specific criteria that standard tools miss.

2. Behavioral Emulation: The system uses randomized delays, "human-like" mouse movements, and varying activity windows to ensure the automation is indistinguishable from a real user.

3. The "Lead-to-CRM" Bridge: Using n8n, we connected the outreach engine to the client's CRM. If a prospect replies, the automation pauses and instantly notifies a human sales rep to take over.

4. AI Personalization: Integrated LLMs (GPT-4) to scan a prospect's recent posts or profile sections and generate a unique "hook" for the first connection request.

The Tech Stack

• Languages: Python (Selenium/Puppeteer), JavaScript

• Orchestration: n8n / Make.com

• AI/NLP: OpenAI API (for dynamic message personalization)

• Storage: Supabase / Google Sheets

The Impact

• 20+ Qualified Meetings: Consistently generated for clients on a monthly basis.

• 85% Time Savings: Sales teams shifted from "finding leads" to "having conversations."

• High Deliverability: Achieved a 35%—45% connection request acceptance rate by avoiding "spammy" patterns.