A leading payment software company wanted to improve account coverage across its target market.
While the sales team relied heavily on LinkedIn and traditional prospecting databases, a significant portion of qualified accounts remained difficult to identify. Valuable prospect information was scattered across company websites, business directories, maps listings, and other public sources that were not captured in a single platform.
Here’s how the company used Pintel.AI to aggregate multi-source data, uncover hidden opportunities, and expand account coverage by 36%.
Company Snapshot
| Company Snapshot | Details |
|---|---|
| Industry | Payment Software |
| Company Size | $800M+ ARR |
| Use Case | Multi-Source Prospect Discovery & Data Aggregation |
| Challenge | Limited Coverage from Traditional Data Sources |
| Data Sources | LinkedIn, Web, Maps & Proprietary Datasets |
| CRM | Salesforce |
| Outcome | 36% Increase in Account Coverage |
The Challenge: Valuable Prospect Data Was Hidden Across Multiple Sources
The company’s sales team relied primarily on LinkedIn and traditional sales intelligence platforms to identify target accounts.
However, many qualified businesses were missing from their prospecting workflows because important information existed across company websites, local business listings, maps data, industry directories, and other fragmented sources.
Manually researching and consolidating this information was slow, difficult to scale, and often resulted in incomplete account coverage.
Key Challenges
✓ Heavy reliance on LinkedIn and traditional databases
✓ Limited visibility into the full addressable market
✓ Prospect data scattered across multiple sources
✓ Manual research slowed prospect discovery
✓ Inconsistent and fragmented data quality
✓ Hidden opportunities remained undiscovered
✓ Account coverage was constrained by available research capacity
How Pintel.AI Helped
Multi-Source Data Aggregation
Pintel.AI aggregated prospect data from LinkedIn, company websites, Google Maps, business directories, and proprietary datasets to create a more complete view of target accounts.
Automated Prospect Discovery
Qualified accounts were identified automatically across multiple sources instead of relying on a single database.
Data Cleaning & Mapping
Data from different sources was standardized, normalized, and mapped into a unified structure.
Contact Enrichment
Prospect records were enriched with additional company and contact information to improve outreach readiness.
Automated CRM Sync
Cleaned and enriched records were automatically synced into Salesforce, eliminating manual uploads and data maintenance.
Results Achieved
36% Increase in Account Coverage
The sales team gained access to significantly more qualified accounts that were previously unavailable through traditional prospecting sources.
Expanded Total Addressable Market
Additional target accounts were discovered across multiple data sources, increasing market visibility.
Faster Prospect Discovery
Automated workflows replaced slow manual research processes.
Improved Data Quality
Multi-source validation improved data completeness, consistency, and reliability.
Better Prospect Readiness
Enriched company and contact records helped sales teams engage prospects faster.
Customer Quote
“Pintel helped us uncover a significant portion of our market that traditional prospecting tools missed. By aggregating data from multiple sources, we expanded account coverage by 36% while improving data quality across our CRM.”
Customer Outcome
What was once a fragmented and manual prospect discovery process became an automated workflow capable of aggregating, validating, enriching, and maintaining prospect data at scale.
The result was broader market visibility, 36% greater account coverage, cleaner CRM records, and faster prospecting execution without increasing research effort.
What Became Possible with Pintel.AI
✓ 36% increase in account coverage
✓ Hidden prospects discovered automatically
✓ Multi-source prospect intelligence consolidated
✓ Contact and company data enriched at scale
✓ Cleaner, more accurate CRM records
✓ Faster prospect identification and qualification
✓ Reduced dependence on LinkedIn-only data
✓ Expanded visibility across the addressable market
✓ Sales teams received outreach-ready records faster
Frequently Asked Questions
Why wasn’t LinkedIn enough for prospect discovery?
Many qualified accounts had valuable information available on company websites, directories, maps listings, and other sources that were not fully represented on LinkedIn.
What is multi-source prospect discovery?
Multi-source prospect discovery combines information from multiple public and proprietary sources to identify accounts that traditional databases may miss.
How did Pintel.AI expand account coverage?
Pintel.AI aggregated, validated, and enriched data from multiple sources, helping the company uncover additional qualified accounts.
How did contact enrichment help?
Contact enrichment improved record completeness by adding and validating company and contact information needed for outreach.
Can multi-source data improve CRM quality?
Yes. Combining and validating information from multiple sources helps create more complete and accurate CRM records.
How much did account coverage increase?
The company expanded account coverage by 36%, giving sales teams access to more qualified opportunities.
Can Pintel.AI identify prospects beyond LinkedIn?
Yes. Pintel.AI leverages web intelligence, maps data, directories, proprietary datasets, and other sources to identify prospects beyond traditional platforms.
How did automation improve prospecting efficiency?
Automated discovery, enrichment, and CRM synchronization reduced manual research and helped sales teams focus on engaging prospects faster.
