Revenue Accelerator: Consolidated Contact Intelligence

The Problem (The Before)

The Environment: Contact data lived across scattered spreadsheets and tools, in inconsistent formats, across multiple clients.

The Friction:

• Fragmentation: Data was spread across sources and formats, making it hard to reuse.
• Redundant Spend: Teams repeatedly purchased fresh data from expensive sources.
• Low Reuse: No centralized system to identify which contacts performed best.
• Data Debt: Inconsistent formatting and duplicate records slowed outreach.

The Pain: Data costs kept rising while teams lacked a reliable, searchable source of truth.

The Plumbing (The Fix)

Strategy: Consolidate and normalize all contact data into a single Zoho CRM database.

The Stack: Zoho CRM, Python/Pandas normalization, and structured imports from multiple sources.

The Execution:

1. Inventory: Collected contact data from spreadsheets and external sources.
2. Normalization: Used Python and Pandas to normalize and import 2,000+ CSV files.
3. Deduplication: Merged overlapping records and resolved conflicts.
4. Searchability: Built a searchable CRM structure tied to engagement history.

Technical Approach:

• Field mapping across varied source schemas
• Normalization rules for consistent formatting
• Deduplication logic to eliminate overlap
• Tagging for engagement performance and reuse

The Flow (Results & ROI)

Quantifiable Impact:

• 40% data cost reduction from reuse vs. repeated purchases
• 3M+ contacts consolidated into a searchable database
• 3-month delivery timeline for full consolidation
• Faster targeting by identifying high-performing contacts
• Faster new engagements by building lists without re-sourcing data
• Higher reuse across clients with consistent data structure

The Breakthrough: A centralized, searchable database turned data debt into reusable leverage across engagements and improved client satisfaction (not formally measured).