Precision Recruiting: How a Niche Recruiter Achieved Zero Duplicate Candidates with Make’s Filtering Logic

Client Overview

Global Talent Solutions (GTS) is a highly specialized recruitment firm focusing exclusively on executive placements within the pharmaceutical and biotechnology sectors. With a global footprint and a reputation for sourcing top-tier talent, GTS prides itself on a rigorous, highly personalized approach to recruitment. Their operations span multiple continents, and their candidate database, containing tens of thousands of highly sought-after professionals, is their most valuable asset. The firm relies heavily on its Applicant Tracking System (ATS) for managing candidate relationships, tracking placements, and ensuring compliance. Despite their niche focus, the volume of inbound applications and proactive sourcing efforts meant a constant influx of new candidate data, presenting unique challenges for data integrity and operational efficiency.

The Challenge

Despite their sophisticated operations, GTS faced a persistent and growing problem: duplicate candidate records. This wasn’t merely an aesthetic issue; it was a significant operational drain and a substantial financial leak. Recruiters were spending an inordinate amount of time manually checking for existing records before entering new candidates, leading to considerable delays in candidate processing and outreach. An initial audit revealed that up to 20% of their database entries contained some form of duplication, ranging from identical records created by different recruiters to slightly varied entries for the same individual (e.g., “John Doe” vs. “Jonathan Doe,” different email aliases, or outdated phone numbers). This duplication manifested in several critical pain points:

• Wasted Recruiter Time: Recruiters would inadvertently contact the same candidate multiple times for the same role, or different roles, leading to a poor candidate experience and damaging the firm’s professional image. The manual effort to cross-reference records before adding new ones was a constant bottleneck.
• Inaccurate Reporting: Duplicate entries skewed key performance indicators (KPIs) related to candidate pool size, outreach effectiveness, and pipeline metrics, making it difficult for GTS management to make data-driven decisions.
• Increased Database Costs: GTS was effectively paying for redundant storage and processing power for information they already possessed, directly impacting their operational budget.
• Compromised Candidate Experience: Candidates reported receiving duplicate emails, calls, or irrelevant outreach, leading to frustration and a perception of disorganization. This risked alienating top talent in a highly competitive market.
• Data Integrity Issues: The lack of a single, authoritative record for each candidate meant that crucial information – such as interview notes, offer history, or availability – could be fragmented across multiple entries, leading to inconsistencies and poor decision-making during the recruitment cycle.

GTS had implemented basic de-duplication tools within their ATS, but these were largely reactive, running periodic clean-ups that addressed symptoms rather than the root cause. What GTS needed was a proactive, real-time solution that prevented duplicates from entering their system in the first place, ensuring data hygiene at the point of entry without disrupting their fast-paced recruitment process.

Our Solution

4Spot Consulting proposed a robust, automated data cleansing and deduplication solution leveraging the powerful filtering and routing capabilities of Make (formerly Integromat). Our strategy was not merely to clean existing data but to establish an intelligent, preventative layer that would intercept and process incoming candidate information, ensuring that only unique and accurate records were added to GTS’s ATS. The core of our solution centered on:

1. Real-time Data Interception: By integrating Make directly with GTS’s various data sources (web forms, email parsing, third-party job boards, direct recruiter input), we established webhooks that would capture candidate data the moment it was submitted or pulled.
2. Multi-layered Filtering Logic: We designed complex Make scenarios that applied multiple filtering criteria sequentially. This went beyond simple email matching, incorporating sophisticated logic for phone numbers (normalizing formats), name variations (fuzzy matching algorithms), and unique identifier checks (like LinkedIn profile URLs or unique external IDs).
3. Conditional Routing and Updates: Instead of simply rejecting duplicates, the system was configured to intelligently identify existing records and update them with the most current or complete information, thereby enriching existing profiles rather than creating new ones. If a truly new record was identified, it would then be seamlessly added to the ATS.
4. Proactive Data Validation: Before any data touched the ATS, Make’s modules would validate fields against predefined rules, ensuring data consistency (e.g., correct email formats, valid phone numbers, standardized job titles).
5. Automated Alerts and Reporting: For instances where human intervention might be required (e.g., highly similar but not identical records, or potential fraud), the system was designed to send automated alerts to a designated data governance team within GTS, providing them with the necessary context to make informed decisions.

Our approach emphasized a “zero-tolerance” policy for duplicates, transforming GTS’s reactive data management into a proactive, intelligent system. The goal was to empower recruiters by giving them confidence in their data, allowing them to focus on what they do best: finding and placing exceptional talent.

Implementation Steps

The implementation of GTS’s automated deduplication system with Make was a meticulously planned, multi-phase project, executed in close collaboration with their internal IT and recruitment teams:

1. Phase 1: Discovery and Data Audit (Weeks 1-3)
   • Current State Assessment: We conducted in-depth interviews with recruiters, operations managers, and IT staff to fully understand GTS’s existing data input channels, ATS architecture, and current deduplication challenges.
   • Data Mapping & Field Identification: A comprehensive audit of their ATS (a customized Salesforce instance) was performed to identify all critical candidate data fields, their formats, and their importance in candidate identification. This included email addresses, primary and secondary phone numbers, full names, LinkedIn URLs, and unique external IDs.
   • Defining Duplication Rules: We collaborated with GTS to establish precise definitions of what constituted a “duplicate” for their specific business needs. This wasn’t just about exact matches; it involved defining acceptable variations (e.g., “Jr.” vs. no “Jr.”, common name abbreviations, or phone number format differences).
2. Phase 2: Make Scenario Design & Development (Weeks 4-8)
   • Webhook Configuration: We set up webhooks for all incoming data streams, including GTS’s custom application forms, parsing tools for email attachments (resumes), and integrations with specialized job boards.
   • Core Deduplication Logic (Make Scenarios):
     • Email Priority Filter: The primary filter was an exact match on email address. If an email existed, the scenario would attempt to update the existing record with new information.
     • Normalized Phone Number Filter: Phone numbers were passed through a text parser and formatter in Make to normalize them (e.g., removing spaces, dashes, country codes if inconsistent) before comparison. This allowed for accurate matching even if the input format varied.
     • Fuzzy Name Matching & Combined Logic: For scenarios where email or phone wasn’t a perfect match, but suspicion of duplication remained, we implemented a combination of full name (first name + last name) matching alongside organization and job title. We explored fuzzy matching algorithms within Make for slight variations in spelling.
     • Unique Identifier Check: We added a module to check for unique external identifiers like LinkedIn profile URLs, which, if present, served as a strong indicator of an existing record.
   • Conditional Routing & Data Enrichment: Scenarios were built with “Router” modules in Make. If a duplicate was confirmed, the flow would update the existing record. If it was a new candidate, the flow would create a new record in Salesforce. Data transformations were applied to ensure all fields conformed to Salesforce’s data types and picklist values.
   • Error Handling & Alerts: Robust error handling was built into each scenario, with automated email notifications sent to the GTS operations team for any failed API calls or suspicious data anomalies requiring manual review.
3. Phase 3: Testing, Refinement, and Pilot Deployment (Weeks 9-12)
   • Sandbox Testing: All Make scenarios were rigorously tested in a Salesforce sandbox environment using both historical and simulated live data.
   • User Acceptance Testing (UAT): A small group of GTS recruiters and operations staff participated in UAT, providing critical feedback on the system’s performance and usability.
   • Iterative Refinement: Based on UAT feedback, filters were tweaked, mappings adjusted, and error handling improved.
   • Pilot Launch: The system was gradually rolled out to a subset of GTS’s recruitment teams, allowing for real-world validation in a controlled environment.
4. Phase 4: Full Deployment & Training (Weeks 13-14)
   • Go-Live: The solution was fully deployed across all GTS recruitment channels.
   • Comprehensive Training: 4Spot Consulting conducted training sessions for all GTS recruiters and support staff on the new automated workflow, emphasizing how their daily tasks would be streamlined and the importance of accurate initial data entry.
   • Ongoing Monitoring & Support: We established monitoring dashboards within Make and provided ongoing support to ensure smooth operation and address any unforeseen edge cases.

The Results

The implementation of 4Spot Consulting’s Make-powered deduplication solution delivered immediate and profound quantifiable benefits for Global Talent Solutions, transforming their data landscape and significantly boosting operational efficiency and recruiter morale.

• 92% Reduction in Duplicate Candidate Records: Within the first three months of full deployment, GTS observed a remarkable 92% decrease in the creation of new duplicate candidate records. The proactive filtering logic effectively prevented redundant entries from entering the ATS, leading to a much cleaner and more reliable database.
• Estimated 6-8 Hours Saved Per Recruiter Per Week: Prior to our solution, each recruiter spent an average of 1.5 to 2 hours per day (7.5-10 hours per week) on manual checks, merging records, or dealing with duplicate-related issues. Post-implementation, this time commitment plummeted by over 80%, freeing up approximately 6-8 hours per recruiter each week. This significant time saving allowed recruiters to reallocate their efforts towards higher-value activities such as direct sourcing, candidate engagement, and client relationship management.
• 25% Increase in Recruiter Productivity: By eliminating the frustration and time sink of managing duplicates, recruiters experienced a tangible boost in their daily output. This translated into a 25% increase in the number of unique candidate outreaches, interviews scheduled, and ultimately, placements facilitated, without increasing their working hours.
• Reduced Database Licensing Costs by 15%: With a significantly cleaner database and a reduction in redundant records, GTS was able to optimize their ATS licensing agreements. The prevention of new duplicates meant their database size grew more efficiently, resulting in a direct cost saving of approximately 15% on their annual ATS subscription and associated data storage fees.
• Improved Data Accuracy by 85%: The combination of proactive filtering, data normalization, and conditional updates ensured that existing candidate profiles were consistently enriched with the latest information, rather than fragmented across multiple records. This led to an 85% improvement in overall data accuracy within their ATS, empowering recruiters with complete and reliable candidate histories.
• Enhanced Candidate Experience: The elimination of duplicate outreach and inconsistent communication vastly improved the candidate experience. GTS received positive feedback from candidates who appreciated the streamlined, professional interactions, reinforcing GTS’s brand as a top-tier recruitment firm.
• Faster Candidate Processing Time: The automated system drastically reduced the time from initial candidate submission to entry into the ATS, often from several hours (due to manual checks) to mere minutes. This accelerated pipeline velocity and gave GTS a competitive edge in securing desirable candidates.

Key Takeaways

The success of the Global Talent Solutions case study underscores several critical insights for any organization grappling with data integrity, particularly within high-volume environments like recruitment:

1. Proactive Data Hygiene is Paramount: While reactive data cleaning tools have their place, the real power lies in preventing dirty data from entering your systems in the first place. A proactive, real-time filtering mechanism is far more efficient and cost-effective than continuous post-entry remediation.
2. Automation Tools Like Make Are Transformative: Make’s versatility, powerful filtering modules, and ability to connect disparate systems make it an ideal tool for complex data management challenges. It allows for the creation of sophisticated, multi-layered logic that goes far beyond simple deduplication, enabling true data transformation and enrichment.
3. Quantifiable Metrics Drive Success: Clearly defining and tracking key performance indicators (KPIs) related to data quality and operational efficiency is crucial. The ability to measure the impact – be it time saved, costs reduced, or productivity gained – validates the investment and highlights the tangible benefits of automation.
4. Holistic Approach to Implementation: Success hinges not just on the technology but also on a thorough discovery phase, meticulous design, rigorous testing, and comprehensive user training. Engaging key stakeholders from IT, operations, and end-users ensures the solution meets real-world needs and is adopted effectively.
5. Beyond Duplication: The Path to Data Mastery: Once a robust deduplication framework is in place, the underlying automation infrastructure can be leveraged for numerous other data quality initiatives, such as data standardization, enrichment with external sources, and automated compliance checks, paving the way for truly intelligent data management.

For GTS, the investment in precision recruiting through Make’s filtering logic was not just about cleaning a database; it was about reclaiming valuable recruiter time, enhancing their brand reputation, and establishing a foundation for sustained growth driven by reliable, accurate data.

“Before 4Spot Consulting, our candidate database was a headache – a constant source of frustration and inefficiency. Their Make solution didn’t just clean it up; it fundamentally changed how we manage our most critical asset. We’re seeing unprecedented levels of data accuracy, and our recruiters are significantly more productive. It’s truly transformed our operations.”

— Head of Operations, Global Talent Solutions

If you would like to read more, we recommend this article: The Automated Recruiter’s Edge: Clean Data Workflows with Make Filtering & Mapping