About the company

Tigerhall is a B2B learning and thought‑leadership platform that helps business audiences discover practical insights from industry leaders. Social content is a primary growth engine, with LinkedIn driving awareness, community engagement, and a steady stream of warm prospects. To turn that engagement into pipeline, Tigerhall prioritizes timely visibility into who interacts, clean, structured data for qualification, and personalized first touches that reflect each prospect’s role and context.

The problem

Each time Tigerhall published a post on LinkedIn, the team manually scraped details of users who liked or commented to identify potential prospects. For every engager, the POC looked up:

• Current job title and company

• Previous roles and seniority indicators

• Context for personalization (e.g., industry, function)

This workflow was entirely manual and consumed ~2 hours per day, diverting attention from higher‑value activities like messaging tests, campaign design, and meetings with qualified prospects.

Impact of the manual process

• Slow speed to engage as data collection lagged behind post performance.

• Inconsistent data quality due to copy/paste errors and missing fields.

• Opportunity cost with the POC spending significant time on repetitive tasks.

The solution

We built an automated LinkedIn engagement scraper that collects details of users who like or comment on Tigerhall’s posts and writes them directly to a Google Sheet that the team uses for outreach and tracking.

How it works

• Scheduled runs pull new post engagements at set intervals and de‑duplicate records.

• Lead enrichment captures name, job title, company, and prior roles, and normalizes fields for filtering.

• Google Sheets sync updates a shared worksheet with fresh, structured rows ready for outreach.

• Readiness by morning: The system completes overnight so the POC opens a sheet that’s already populated.

• Logging and alerts flag run status and any exceptions for quick follow‑up.

Success metrics

• 120+ hours saved per month for the POC, reclaiming time for strategy, messaging, and meetings.

• Faster outreach with engagement leads available the next morning after a post goes live.

• Higher data completeness across required fields, reducing manual corrections.

Business impact: More consistent follow‑through on warm LinkedIn signals, improved personalization at first touch, and more time for activities that drive revenue.