0
%
Reduction in duplicate identification time
0
%
Accuracy achieved in duplicate detection through smart matching
$
0
B+
AUM of the private equity firm served
Building a Trusted CRM: An AI-Powered Contact De-Duplication Agent for a $10B+ PE Firm
About the Client
A private equity firm strengthening the reliability of its CRM database engaged TresVista to improve the quality and reliability of its CRM database by addressing duplicate contact records, with the goal of establishing a trusted source of contact information, reducing manual review effort, and improving the effectiveness of downstream sales and marketing activities.
Business Challenge
Four barriers to a clean, reliable CRM
1. Duplicate records from fragmented entry
CRM data contained duplicate records caused by fragmented data entry and maintenance processes across the organization, accumulating over time
2. Error-prone manual de-duplication
Manual de-duplication required extensive record-by-record review and was prone to errors, particularly as the volume of contacts grew
3. Cross-referencing overhead
Identifying duplicates often required cross-referencing external sources, increasing the effort and turnaround time needed to confirm a match
4. Downstream reporting impact
Duplicate and inconsistent records impacted reporting accuracy and CRM reliability, undermining confidence in downstream sales and marketing data
Strategic Approach
TresVista's Solution: A Claude-powered Contact De-duplication Agent with analyst validation
TresVista designed and deployed a Contact De-duplication Agent leveraging Claude, combining AI-based smart matching with structured human-in-the-loop validation to deliver a clean, trusted contact database
01
Deployment of the de-duplication agent
TresVista deployed a Claude-based agent to identify and compare potential duplicate records across the CRM platform, automating the initial matching phase across the full contact database
02
Automated matching and pattern recognition
The agent applied predefined matching rules and pattern recognition to flag likely duplicates, drawing on external data sources including LinkedIn to strengthen match confidence where CRM data alone was insufficient
03
Human-in-the-loop validation
Analysts reviewed flagged matches to confirm true duplicates and executed final record merges, ensuring accuracy before changes were made to the live CRM database
04
Standardized contact database
TresVista used the validated output to establish a clean, standardized contact database, improving data integrity and usability across sales and marketing workflows
TresVista Impact
A cleaner CRM. Faster de-duplication. A scalable model.
Before
100%
Baseline Effort
After
70%
Of Baseline Effort
18%
less time
~30% Reduction in duplicate identification time
Reinvested in higher-value CRM and outreach activities.
Outcome
- Reduced end-to-end duplicate identification time by approximately 30%, freeing analyst capacity from record-by-record manual review
- Achieved 80% accuracy in duplicate identification through AI-assisted smart matching, reducing the risk of missed or incorrect merges
- Improved CRM reliability by establishing a cleaner and more consistent contact database across the firm
- Enabled more accurate reporting and faster data-driven decision-making for sales and marketing teams
- Delivered a scalable solution capable of supporting large datasets without disrupting existing processes
Tools & Technologies
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