Case Study — Belgium

B2B Exhibition Lead ROI Optimization

A data pipeline that scores and ranks B2B exhibition leads by investment capacity. Built with Python for data simulation and SQL for scoring logic — identifying the highest-potential prospects in a Belgian market dataset of 200+ companies.

Top High-Potential Leads — Belgium (B2B)
Company 188
€189,402
Company 146
€173,964
Company 130
€127,402
Company 119
€126,790
Company 94
€104,657
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Technical Execution

How It Was Built

Three-stage pipeline: data simulation in Python, scoring logic in SQL, visualization for strategic output. The result is a ranked list of prospects with estimated investment capacity — ready for sales prioritization.

01
Data Simulation
Realistic B2B exhibition dataset generated using Python and Pandas. 200+ company records with sector, size, and engagement signals.
02
SQL Scoring
Investment capacity scoring logic applied via SQL transformations. Companies ranked by weighted ROI potential.
03
Strategic Output
Visualization layer translating raw scores into an actionable prospect ranking for market entry prioritization.