Case Study: How Data Automation Revolutionized a B2B Sales Team
Discover how one of our clients in the B2B logistics and distribution sector reduced active prospecting time by 90% and increased the conversion rate by 35% using real-time structured data.
The Previous Scenario
The client had a team of 15 SDRs (Sales Development Representatives) who spent 6 hours a day manually searching for new companies on portals like Google Maps, LinkedIn, and commercial association websites.
The problems were obvious:
- Low Quality: Outdated data (many companies had already closed).
- Slowness: Each SDR was only able to prospect 20 new companies per day.
- Lack of Context: The team made calls without knowing the actual size or needs of the company.
The DataShift Solution
We implemented a Commercial Intelligence Pipeline infrastructure consisting of three layers:
🎯 1. Mapping Government Sources
We configured bots to monitor official gazettes and commercial registry portals. Whenever a new company (CNPJ) with the target industry code was opened, our systems captured the data in less than 24 hours.
âš¡ 2. Data Enrichment
Raw company registration data is not enough. Our bots cross-referenced the company name with Google Maps to extract the rating (stars), photo volume, and official website, indicating the lead's level of digital maturity.
📊 3. Direct CRM Integration
The clean, enriched data was injected via API directly into the client's Salesforce, automatically distributed among salespeople by geographical region.
Results
| Metric | Impact |
|---|---|
| Manual Research Time | -90% |
| Conversion (Lead to MQL) | +35% |
The Practical Result
Today, the SDR team arrives at work with a list of 50 ultra-qualified leads per person, ready for outreach. They don't spend a single minute "hunting" for data. The focus shifted from "research" to "strategic selling".
"DataShift didn't just hand us a list of companies, they handed us a data-fueled sales engine that our competitors don't even know exists."
— Client's Commercial Director
To understand the technical foundation behind this success, see our guide to Web Scraping for Enterprises.
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