Identity Resolution

Client Background:
A mid-market SaaS company headquartered in Austin, Texas, with a sales team of 120 reps and a database of over 800,000 CRM records across Salesforce. The company had been scaling rapidly through acquisitions and inbound marketing, resulting in a CRM environment severely degraded by duplicate records and inconsistent data entry standards.

Challenge:
The sales operations team estimated that nearly 35% of all CRM records were duplicates or near-duplicates — the same contacts appearing multiple times under different email addresses, name formats, or imported from different marketing campaigns. Lead routing was broken: high-value inbound leads were being assigned to the wrong reps or lost entirely. Attribution data was unreliable, and marketing was re-engaging existing customers as cold prospects, damaging brand reputation.

Solution:
Hir Infotech deployed its AI-driven identity resolution service against the full Salesforce database, applying probabilistic matching algorithms to surface and merge duplicate contact and lead records. We linked records based on a combination of email domains, phone number normalization, company name fuzzy matching, LinkedIn profile identifiers, and behavioral engagement data from HubSpot. A master identity graph was constructed for each unique buyer and account, and clean, enriched records were reloaded back into Salesforce with full audit documentation.

Results:

• 34% reduction in total CRM records through intelligent deduplication
  
  
• Lead routing accuracy improved from 61% to 94% within 60 days
  
  
• Marketing re-engagement false positive rate dropped by 78%
  
  
• Sales cycle shortened by an average of 8 days due to cleaner routing and enriched context
  
  

Client Testimonial:
“Hir Infotech cleaned up a data mess that had been costing us real revenue for years. The results were measurable within weeks — our sales team finally trusts the data they’re working with.”
— VP of Revenue Operations, SaaS Enterprise, Austin, TX

Client Background:
A UK-based B2B e-commerce platform serving wholesale buyers across manufacturing, retail, and distribution sectors. The company managed over 2 million buyer accounts across its platform, website, email system, and offline trade show data — all stored in disconnected systems.

Challenge:
The company’s marketing and account management teams were working from different versions of the same customer — one in the email platform, one in the website analytics tool, and one in the ERP system. Cross-sell and upsell campaigns were underperforming because no one had a complete view of any given buyer’s activity, preferences, or account size. GDPR compliance added additional complexity, requiring consent-verified data handling throughout.

Solution:
Hir Infotech constructed a real-time identity graph that unified buyer identities across the email system, web analytics, ERP, and trade event databases. Using TCF-consented data signals and GDPR-compliant processing agreements, we resolved over 2 million buyer records into approximately 1.4 million unique, enriched profiles. The identity graph was integrated directly into the client’s CDP and refreshed continuously via streaming data pipelines.

Results:

• 1.4 million clean, unified buyer profiles replacing 2 million fragmented records
  
  
• 31% increase in cross-sell campaign conversion rates
  
  
• Marketing team reduced audience build time from 3 days to under 2 hours
  
  
• Full GDPR audit trail maintained across all resolution decisions
  
  

Client Testimonial:
“We always knew our data was fragmented, but we didn’t realize how much revenue that was costing us until we saw what a clean identity graph could do. Hir Infotech delivered beyond expectations.”
— Chief Data Officer, B2B E-Commerce Platform, London, UK

Client Background:
A Berlin-based fintech providing B2B payment infrastructure and credit facilities to mid-market European SMEs. With transaction volumes exceeding €400M annually and operations across Germany, Austria, and the Netherlands, the company faced growing exposure to synthetic identity fraud and account takeover attacks.

Challenge:
Fraudulent actors were creating synthetic business identities — combining real and fabricated firmographic data — to access credit facilities. The company’s existing rule-based fraud detection system was catching only the most obvious cases, with sophisticated synthetic identities passing through undetected. The compliance team needed a more intelligent, data-driven identity verification layer that could operate within GDPR boundaries.

Solution:
Hir Infotech deployed an AI-powered identity resolution and verification layer integrated into the client’s onboarding workflow. Our system cross-referenced applicant identity signals — business registration numbers, director names, phone numbers, IP addresses, device fingerprints, and behavioral patterns — against multiple European commercial and public data sources. Machine learning models trained on fraud signal patterns flagged identity inconsistencies in real time, while GDPR-compliant processing ensured all data handling met EU regulatory requirements.

Results:

• 67% reduction in synthetic identity fraud cases within the first quarter
  
  
• Onboarding false positive rate (legitimate businesses flagged as fraud) reduced by 42%
  
  
• €2.3M in estimated fraud losses prevented in the first six months
  
  
• Full GDPR documentation and DPO sign-off on all data processing workflows
  
  

Client Testimonial:
“Identity fraud was an existential risk for our business. Hir Infotech gave us the intelligence layer we needed to protect our platform without slowing down legitimate customer onboarding.”
— Head of Risk & Compliance, Fintech Platform, Berlin, Germany

Client Background:
A large private healthcare network in Sydney, Australia, operating 14 hospitals and 60+ outpatient clinics across New South Wales and Victoria. The organization managed over 5 million patient records across legacy EHR systems, appointment platforms, and billing databases accumulated over 20+ years.

Challenge:
Duplicate patient records were creating serious clinical risks. The same patient appearing under different names, DOBs, or Medicare numbers across systems could receive duplicate prescriptions, miss critical allergy flags, or have incomplete medical history reviewed at point of care. The organization’s IT team estimated 8–12% of all records were duplicates or near-duplicates — a figure representing hundreds of thousands of patients.

Solution:
Hir Infotech applied a healthcare-specific identity resolution framework that combined deterministic matching on Medicare numbers and date of birth with probabilistic matching on name variants, address history, and contact details. The service was deployed with Australian Privacy Act compliance protocols and integrated with the network’s existing EHR platform. Approximately 480,000 duplicate records were identified, reviewed, and merged or flagged for clinical review in a staged rollout over 12 weeks.

Results:

• 480,000 duplicate patient records resolved across all 14 hospital systems
  
  
• Clinical risk flags improved by 23% through more complete patient histories
  
  
• Billing accuracy improved, reducing insurance claim rejections by 18%
  
  
• Australian Privacy Act compliance maintained throughout the full project lifecycle
  
  

Client Testimonial:
“Patient safety depends on clean data. Hir Infotech understood the stakes and delivered a solution that was both technically excellent and clinically sensitive. We’ve reduced risk significantly.”
— Chief Information Officer, Private Healthcare Network, Sydney, Australia

Client Background:
A Paris-based enterprise software vendor specializing in supply chain management solutions for mid-market manufacturers across France, Belgium, and Spain. The company’s ABM program was targeting 500 named accounts but struggling to identify the right decision-makers within those accounts due to fragmented contact data.

Challenge:
The marketing team had contact records across Marketo, LinkedIn Campaign Manager, and a third-party intent data provider — but the same individual frequently appeared in all three systems under different identifiers. Lead-to-account matching was inaccurate, resulting in content and ads being served to the wrong contacts or the same person being counted multiple times in attribution reports.

Solution:
Hir Infotech deployed an AI-driven identity resolution layer that unified contact identities across Marketo, the LinkedIn ad platform, and the intent data provider. Using domain-based company matching, email alias normalization, and LinkedIn profile identifier linking, we built a unified contact graph for all 500 target accounts — resolving 18,400 contact records into 11,200 unique, accurately matched buyer profiles.

Results:

• 18,400 contact records resolved into 11,200 clean, unique profiles
  
  
• ABM campaign reach improved by 29% through accurate audience targeting
  
  
• Attribution accuracy increased, enabling the team to identify 3 previously invisible pipeline influencers per account on average
  
  
• Marketing qualified account (MQA) conversion rate improved by 22%
  
  

Client Testimonial:
“Our ABM program was flying blind before Hir Infotech. Now we know exactly who we’re talking to, within every target account. The pipeline impact has been tangible and measurable.”
— Head of Demand Generation, Enterprise Software, Paris, France

Client Background:
An Amsterdam-based media and publishing group operating B2B subscription products serving marketing, finance, and legal professionals across the Netherlands, Belgium, Denmark, and Sweden. The group was pursuing data collaboration partnerships with advertising partners but lacked a compliant identity resolution layer for its clean room environment.

Challenge:
The media group needed to enable audience matching with advertising partners inside a clean room without exposing raw subscriber PII. Existing subscriber identity data was fragmented across publication-specific systems, CRM, and paywall platforms — meaning the identity layer feeding the clean room was incomplete and inconsistent, reducing match rates and limiting monetization.

Solution:
Hir Infotech built a unified subscriber identity graph integrating data from all four publication systems, CRM, paywall, and event registration databases. Using hashed email matching, probabilistic device signal linking, and GDPR-safe data processing, we produced a consolidated, privacy-safe identity layer with over 85% match coverage across the active subscriber base. This identity layer was integrated directly into the client’s clean room environment for privacy-preserving audience collaboration.

Results:

• 85%+ match rate achieved in clean room audience collaboration with advertising partners
  
  
• Subscriber identity graph unified across 4 previously siloed systems
  
  
• New advertising revenue partnerships activated within 90 days of deployment
  
  
• Full GDPR and TCF 2.2 compliance maintained throughout
  
  

Client Testimonial:
“Hir Infotech solved a problem we’d been stuck on for two years. Their team understood both the technical complexity and the European regulatory requirements — and delivered a solution that actually worked.”
— VP of Data Strategy, Media Group, Amsterdam, Netherlands