Generic Lists, Low Conversion
Purchased lead lists with no filtering. Cold-calling people who didn’t need wealth management.
From Open Data
to Acquired Prospects.
The Problem
Customer Acquisition Costs were High
Eitam Finance, a small Israeli financial services firm needed cheap targeted prospects (leads for cold-calling). The available enterprise data platforms didn’t serve the market (wrong language, wrong geography, wrong price point.) A new approach was required.
No Vendor for the Israeli Market
Enterprise platforms (ZoomInfo, Clearbit, Apollo) were US-focused and didn’t index Hebrew-language sources.
Geographic Targeting by Hand
Filtering by income tier, neighborhood, or postal code required a custom layer no off-the-shelf tool offered for this region.
The Solution
Local Leads Generation
Localized web-scraping of leads from highly targeted city-level web-directories.
[01]
Extraction
WebScraper extracted from registries, directories, and local sites. BrightData residential proxies handled anti-bot bypass and IP rotation.
[02]
Data Enrichment & Classification
Cities classified into income tiers using public demographic signals.
Records scored against weighted signals (geo-tier, profession, ownership) to produce a ranked prospect list.
[03]
Structuring
Custom VBA macros in Excel: normalization, enrichment, dedup, turning raw data into a structured, filterable index.
Retrospective
What This Project Taught
The iterative feedback loop from Eitam Finance team was the critical key to success as they helped with valuable insights into what worked/converted best and what not. Although it was a highly manual orchestration job, I understood how significant it is to automate the process, yet the feedback loop still required manual adjustments and continuous evaluations.
OUTPUT
The converted prospects represented over ₪50M in new asset-management client portfolio. Cost: a workstation and one engineer.