29-January-2026
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Turn Dirty Data Into Your Biggest Competitive Advantage
Data Cleansing
In today’s AI-driven business landscape, the quality of your data determines the quality of every decision you make. Hir Infotech delivers enterprise-grade, AI-powered data cleansing services trusted by 2,745+ businesses across the USA, Europe, and Australia. With 13+ years of hands-on data intelligence expertise, we identify, correct, standardize, and enrich your datasets — eliminating duplicates, filling gaps, and ensuring full compliance with GDPR, CCPA, and regional data regulations. Whether you manage a CRM with 10,000 records or a data warehouse with 50 million entries, our intelligent data cleansing solutions give your teams the accurate, actionable data they need to grow with confidence.
22.5%
Data Decay Rate
$12.9M
Annual Cost of Bad Data
70%
CRM Accuracy Crisis
17.3%
CAGR
30%
B2B contact records
Why Data Cleansing Is No Longer Optional for Enterprise Growth
In an era where AI models, CRM platforms, and marketing automation tools are only as intelligent as the data they consume, maintaining clean, complete, and current datasets has become a strategic business imperative. For mid-market and enterprise B2B organizations across the USA, UK, Germany, France, the Netherlands, Sweden, Australia, and beyond, poor data quality silently erodes revenue pipelines, distorts analytics, inflates operational costs, and creates serious compliance exposure. Hir Infotech's AI-driven data cleansing services solve these problems at scale — combining intelligent automation, machine learning validation, and human expert review to deliver datasets you can trust. Our global delivery team has supported 2,745+ clients across industries including financial services, healthcare, e-commerce, SaaS, logistics, real estate, and manufacturing. Whether your challenge is deduplicating a Salesforce CRM, standardizing addresses across European markets, validating contact records for outbound campaigns, or preparing raw data for BI tools and AI pipelines, Hir Infotech delivers accuracy-first results at enterprise speed.
- AI-Powered Deduplication & Record Merging: Our proprietary algorithms detect and merge duplicate records across CRM systems, marketing databases, and ERP platforms — preserving master records while eliminating costly redundancies that inflate costs and distort reporting.
- Data Standardization & Normalization: We apply consistent formatting rules to names, addresses, phone numbers, company identifiers, and job titles across every record — ensuring uniformity across Salesforce, HubSpot, Microsoft Dynamics, and custom data environments.
- Missing Data Detection & Intelligent Enrichment: Using AI-assisted gap analysis, we identify incomplete fields and enrich records with verified, up-to-date information from authoritative sources — restoring value to degraded datasets and improving campaign reach.
- GDPR, CCPA & Regional Compliance Cleansing: We audit and remediate datasets to align with GDPR (EU), CCPA (USA), LGPD (Brazil), and regional data protection regulations — removing non-consented or non-compliant records and supporting your legal and privacy obligations.
What We Clean, Fix & Deliver
Hir Infotech’s data cleansing capabilities span structured and unstructured data, covering B2B contact records, transactional data, product catalogs, and CRM exports — delivered clean, validated, and integration-ready.
Intelligent Duplicate Detection
Using fuzzy matching, phonetic algorithms, and ML-based entity resolution, we identify and resolve duplicate records across multiple data sources — even when records differ slightly in name spelling, format, or field structure.
Automated Standardization Engine
Our standardization pipeline normalizes inconsistent data formats: date fields, country codes, currency values, address structures (including USPS, Royal Mail, and EU postal formats), and industry classification codes — making datasets plug-and-play for analytics and AI tools.
Real-Time Data Validation
Every record passes through multi-layer validation checks — syntax, format, constraint, and consistency rules — ensuring email addresses are deliverable, phone numbers are formatted correctly, and postal codes match geographic regions across the USA, UK, EU, and Australia.
Compliance-Aware Data Remediation
We perform structured compliance audits against GDPR (Europe), CCPA (California), PDPA (Australia), and other regional privacy regulations — flagging, suppressing, or removing non-compliant records to protect your organization from regulatory risk.
Trusted by leading brands
Use Cases and Website
The Hidden Cost of Dirty Data on Your Revenue Pipeline
How AI-Driven Data Cleansing Is Transforming B2B Operations in 2026
Most B2B organizations are unknowingly operating on data that is eroding their revenue potential. Gartner research confirms that poor data quality costs organizations an average of $12.9 million per year — a figure that compounds silently through missed sales opportunities, failed marketing campaigns, duplicated vendor payments, and compromised analytics outputs. The problem is systemic: B2B contact data decays at 22.5% annually, meaning nearly a quarter of your CRM becomes outdated within 12 months without active cleansing. Sales teams waste hundreds of hours chasing disconnected numbers and undeliverable emails. Marketing teams invest budget in campaigns that never reach their intended audience. Data science teams build AI models on corrupted inputs and wonder why predictions fall flat. Hir Infotech’s AI-powered data cleansing services interrupt this cycle at the root. By combining machine learning anomaly detection, automated validation pipelines, and expert human review, we restore your data to a state of accuracy, completeness, and compliance — delivering measurable improvements in CRM performance, marketing ROI, and operational efficiency. Our clients across the USA, UK, France, Germany, Spain, Sweden, Denmark, Italy, Iceland, the Netherlands, Austria, Switzerland, and Australia consistently report reduced bounce rates, faster sales cycles, and more reliable reporting after a single data cleansing engagement.cleanlist+1
Enterprise-Grade Data Cleansing Built for Scale, Speed, and Compliance
Not all data cleansing services are created equal. Generic freelance platforms and one-size-fits-all tools cannot replicate the combination of domain expertise, AI-powered tooling, and compliance awareness that Hir Infotech brings to every engagement. With 13+ years of data intelligence experience and 2,745+ satisfied clients globally, we have developed purpose-built data cleansing workflows for industries as diverse as financial services, healthcare, e-commerce, logistics, real estate, and enterprise SaaS. Our process begins with a thorough data profiling audit — identifying the exact nature, volume, and severity of quality issues within your dataset — before a single record is touched. From there, our AI cleansing engine applies rule-based validation, fuzzy matching, entity resolution, and enrichment layers in parallel, dramatically reducing processing time compared to manual approaches. For businesses in regulated markets — including financial institutions in Switzerland and Austria, healthcare organizations in the USA and Australia, and e-commerce operators subject to GDPR across the EU — we apply jurisdiction-specific compliance layers to ensure every cleansed dataset meets legal requirements. We deliver outputs in your preferred format (CSV, JSON, SQL, API feed) directly into your existing stack — whether that is Salesforce, HubSpot, SAP, Oracle, Snowflake, or a custom data warehouse — ensuring zero disruption to your workflows and immediate usability of cleansed data.
Industry We Serve
Case Studies
Client Background
A mid-market B2B SaaS company headquartered in Austin, Texas, providing project management software to enterprise clients across North America. The company operated a Salesforce CRM containing approximately 180,000 contact and account records built over eight years of growth through organic sales, marketing campaigns, and two acquisitions.
Challenge
Following the acquisitions, the CRM contained overlapping records from three separate legacy systems. The sales team reported widespread frustration with duplicate leads, incorrect account hierarchies, outdated contact details, and missing firmographic data. Email bounce rates had climbed to 18%, and sales reps estimated they were losing 6–8 hours per week dealing with bad data. Leadership flagged the data problem as a material risk to their Q3 pipeline targets.
Solution
Hir Infotech conducted a full data profiling audit, identifying 31,000+ duplicate records, 22,000 invalid email addresses, and 40,000+ records with missing critical fields (industry, company size, decision-maker title). We deployed our AI deduplication engine with fuzzy matching to resolve duplicates, validated all email and phone records against real-time verification APIs, standardized job titles and industry codes, and enriched missing firmographic fields. The full cleansing process was completed within 14 business days with zero Salesforce downtime.
Results
- Duplicate records reduced by 94% (31,000+ resolved)
- Email bounce rate dropped from 18% to under 2.1%
- Sales team productivity improved — reps recovered an estimated 6 hours per week per person
- CRM record completeness rose from 61% to 97%
- Pipeline visibility improved, contributing to a 28% increase in qualified opportunities in the following quarter
Client Testimonial
“Hir Infotech didn’t just clean our data — they gave us back our confidence in Salesforce. Our reps are working smarter, our campaigns are finally hitting the right people, and our reporting is actually reliable. The ROI was evident within 30 days.”
— VP of Revenue Operations, B2B SaaS, Austin, Texas
Client Background
A London-headquartered wealth management firm serving high-net-worth clients across the UK, Germany, and Switzerland, managing over €4 billion in assets. The firm operated a legacy client database of 95,000 records across multiple systems that had never undergone formal data governance.
Challenge
With GDPR enforcement intensifying and an upcoming FCA audit, the compliance team identified critical risks in their client data infrastructure. Records contained inconsistent formatting, missing consent flags, duplicate client profiles across business lines, and expired contact information. The firm faced potential regulatory penalties and reputational risk if the audit revealed non-compliant data handling practices.
Solution
Hir Infotech engaged the client’s compliance, IT, and data teams to map data flows and define cleansing rules aligned with GDPR Article 5 accuracy requirements and FCA data governance guidelines. We cleansed 95,000 client records — standardizing names, addresses, and ID formats across UK, German, and Swiss postal conventions; flagging and suppressing 7,200 records lacking valid consent documentation; deduplicating cross-business profiles; and delivering a clean, audit-ready dataset with full change documentation.
Results
- 7,200 non-compliant records identified and suppressed prior to audit
- Duplicate client profiles reduced by 89%
- Successful FCA audit with no data governance findings
- Client communication accuracy improved — returned mail rate dropped from 11% to under 1.5%
- Compliance team reported 40% reduction in manual data remediation hours monthly
Client Testimonial
“Facing a regulatory audit with data in that state was a serious concern. Hir Infotech’s team was methodical, thorough, and clearly understood the compliance requirements. We passed our audit with zero data issues — that outcome alone was worth every penny of the engagement.”
— Chief Compliance Officer, Wealth Management Firm, London, UK
Client Background
A mid-sized Australian multi-category e-commerce retailer operating across their own Shopify store and third-party marketplaces including Amazon AU and eBay Australia, with a product catalog of 85,000+ SKUs across electronics, home goods, and fashion.
Challenge
The retailer’s product catalog had been imported from four separate supplier feeds using inconsistent naming conventions, attribute structures, and category hierarchies. Over 30% of listings contained duplicate SKUs, incorrect attributes (wrong dimensions, mismatched colours), truncated descriptions, and non-compliant category mappings. The result was poor search visibility, elevated return rates (customers receiving the wrong product), and marketplace suppression notices from Amazon AU.
Solution
Hir Infotech conducted a full catalog audit and applied our product data cleansing pipeline: deduplicating SKUs, standardizing product titles against marketplace style guides, normalizing attribute fields (size, colour, material, weight, dimensions), enriching missing product descriptions using structured templates, and reclassifying products to correct category hierarchies for Amazon AU and eBay Australia taxonomy.
Results
- 26,000+ duplicate and erroneous SKUs resolved
- Product listing suppression issues cleared on Amazon AU within 30 days
- Organic search impressions on Amazon increased by 41% in 60 days post-cleansing
- Product return rate dropped from 9.2% to 3.8%
- Average order value improved by 12% attributed to improved product discovery and accurate descriptions
Client Testimonial
“We had no idea how much damage dirty product data was doing to our marketplace rankings and return rate. Hir Infotech fixed years of catalog chaos in weeks. The improvement in our Amazon AU search visibility was almost immediate.”
— Head of Digital Commerce, Multi-Category Retailer, Sydney, Australia
Client Background
A multi-state US healthcare provider network operating across 14 facilities in Texas, Florida, and Ohio, managing a centralized patient database of 1.2 million records accumulated across 12 years of operations and three system migrations.
Challenge
Multiple EHR system migrations had left the patient database riddled with duplicates, inconsistent demographic records, invalid insurance IDs, and missing critical clinical data fields. The network faced HIPAA compliance risk, insurance claim rejections due to patient record mismatches, and patient safety concerns from care teams working with fragmented records.
Solution
Hir Infotech deployed a HIPAA-compliant data cleansing workflow, including encrypted data transfer protocols and signed BAA agreements. Our team performed probabilistic matching to identify duplicate patient records (same patient, different ID formats), standardized demographic fields (DOB formats, address structures, name formatting), validated insurance IDs against payer standards, and enriched records with corrected ZIP+4 postal codes for billing accuracy.
Results
- 148,000 duplicate patient records identified and consolidated
- Insurance claim rejection rate due to data errors reduced by 67%
- Record completeness improved from 72% to 96%
- Clinical care teams reported significantly improved confidence in patient histories
- Zero HIPAA compliance findings in subsequent CMS audit
Client Testimonial
“Patient safety depends on accurate records. Hir Infotech handled our most sensitive data with absolute professionalism and delivered a cleansing outcome that directly improved clinical operations and our compliance posture. We consider them an indispensable long-term partner.”
— Chief Data Officer, Healthcare Provider Network, Dallas, Texas
Client Background
A large German manufacturing conglomerate with operations across Germany, Austria, and the Netherlands, running a centralized SAP S/4HANA ERP instance managing 45,000+ supplier records accumulated over 18 years.
Challenge
Decades of manual data entry, decentralized procurement processes, and three ERP migrations had created a supplier master dataset filled with duplicates, inconsistent VAT and IBAN formats across German, Austrian, and Dutch standards, missing contact details, and outdated supplier classifications. Procurement efficiency was suffering, and the finance team was processing duplicate vendor payments totaling an estimated €2.1 million annually.
Solution
Hir Infotech worked alongside the client’s SAP team to extract, profile, and cleanse the supplier master data. We applied European VAT number validation (Germany, Austria, Netherlands), standardized IBAN and BIC formats, resolved 8,400+ duplicate vendor records using entity resolution algorithms, reclassified suppliers against UNSPSC category codes, and validated contact details. Cleansed data was loaded back into SAP S/4HANA via validated data migration scripts.
Results
- 8,400+ duplicate supplier records resolved
- Duplicate payment risk eliminated — finance team recovered identification of €2.1M in duplicate payment exposure
- Supplier data completeness improved from 58% to 94%
- Procurement cycle time reduced by an estimated 22%
- SAP reporting accuracy improved significantly across accounts payable and spend analytics
Client Testimonial
“The scale of our supplier data problem was something we had been avoiding for years. Hir Infotech made it manageable, methodical, and fast. The financial impact was immediate and measurable. Their understanding of SAP data structures and EU compliance standards was impressive.”
— Head of Procurement Systems, Manufacturing Group, Munich, Germany
Client Background
A UK-based online real estate platform aggregating property listings and agent profiles from over 8,000 independent estate agencies across England, Scotland, and Wales, with a database of 3.2 million property listings and 120,000 agent profiles.
Challenge
The platform’s aggregation model pulled data from hundreds of feeds with inconsistent formats, duplicate listings from the same property listed by multiple agents, incorrect postcodes, missing EPC ratings (required by UK regulations), and outdated agent contact information. Duplicate listings frustrated users and damaged search experience quality, while non-compliant listings exposed the platform to Trading Standards risk.
Solution
Hir Infotech applied a multi-stage property data cleansing process: deduplicating listings using address matching and Royal Mail PAF validation, standardizing property attributes (bedroom count, property type, tenure), flagging and removing listings with non-compliant or missing EPC data, and cleansing agent profiles to verify emails, phone numbers, and agency registration details.
Results
- 420,000+ duplicate property listings identified and resolved
- Royal Mail PAF address validation applied to 100% of listings
- Regulatory compliance rate for EPC inclusion improved from 71% to 99.3%
- User session duration on property search increased by 18% post-cleansing
- Agent contact email deliverability improved from 78% to 97.4%
Client Testimonial
“The quality of listings on our platform directly drives user trust and SEO performance. Hir Infotech’s team understood both the technical and regulatory complexity of UK property data. The improvement in data quality was transformational for our product team.”
— CTO, Real Estate Aggregation Platform, London, UK
Client Background
A mid-market logistics and distribution company based in Rotterdam, the Netherlands, operating last-mile delivery services across the Netherlands, Belgium, and Germany, with a customer database of 280,000 B2B and B2C consignee records and a route optimization system dependent on accurate address data.
Challenge
Address data quality issues were causing delivery failures at a rate of 4.8% — well above industry benchmarks. Incorrect postal codes, missing apartment/floor details, formatting inconsistencies across Dutch, Belgian, and German address conventions, and duplicate consignee records were costing the business an estimated €380,000 annually in failed delivery attempts and rerouting costs.
Solution
Hir Infotech applied address cleansing and validation protocols aligned with Dutch PostNL, Belgian bpost, and German Deutsche Post address standards. We standardized address formats across all three markets, validated against official national address registries, identified and merged 18,000+ duplicate consignee records, and enriched records with geo-coordinates for improved route optimization compatibility.
Results
- Delivery failure rate reduced from 4.8% to under 0.9%
- 18,000+ duplicate consignee records resolved
- Address validation coverage reached 99.1% across NL/BE/DE
- Annual failed delivery cost savings estimated at €340,000+
- Route optimization model accuracy improved by 31%
Client Testimonial
“In logistics, address accuracy is everything. Hir Infotech understood the complexity of operating across three different national address systems and delivered a solution that immediately improved our delivery performance. The cost savings were significant and rapid.”
— Operations Director, Logistics & Distribution, Rotterdam, Netherlands
Case Studies
Client Background
A mid-market B2B SaaS company headquartered in Austin, Texas, providing project management software to enterprise clients across North America. The company operated a Salesforce CRM containing approximately 180,000 contact and account records built over eight years of growth through organic sales, marketing campaigns, and two acquisitions.
Challenge
Following the acquisitions, the CRM contained overlapping records from three separate legacy systems. The sales team reported widespread frustration with duplicate leads, incorrect account hierarchies, outdated contact details, and missing firmographic data. Email bounce rates had climbed to 18%, and sales reps estimated they were losing 6–8 hours per week dealing with bad data. Leadership flagged the data problem as a material risk to their Q3 pipeline targets.
Solution
Hir Infotech conducted a full data profiling audit, identifying 31,000+ duplicate records, 22,000 invalid email addresses, and 40,000+ records with missing critical fields (industry, company size, decision-maker title). We deployed our AI deduplication engine with fuzzy matching to resolve duplicates, validated all email and phone records against real-time verification APIs, standardized job titles and industry codes, and enriched missing firmographic fields. The full cleansing process was completed within 14 business days with zero Salesforce downtime.
Results
- Duplicate records reduced by 94% (31,000+ resolved)
- Email bounce rate dropped from 18% to under 2.1%
- Sales team productivity improved — reps recovered an estimated 6 hours per week per person
- CRM record completeness rose from 61% to 97%
- Pipeline visibility improved, contributing to a 28% increase in qualified opportunities in the following quarter
Client Testimonial
“Hir Infotech didn’t just clean our data — they gave us back our confidence in Salesforce. Our reps are working smarter, our campaigns are finally hitting the right people, and our reporting is actually reliable. The ROI was evident within 30 days.”
— VP of Revenue Operations, B2B SaaS, Austin, Texas
Client Background
A London-headquartered wealth management firm serving high-net-worth clients across the UK, Germany, and Switzerland, managing over €4 billion in assets. The firm operated a legacy client database of 95,000 records across multiple systems that had never undergone formal data governance.
Challenge
With GDPR enforcement intensifying and an upcoming FCA audit, the compliance team identified critical risks in their client data infrastructure. Records contained inconsistent formatting, missing consent flags, duplicate client profiles across business lines, and expired contact information. The firm faced potential regulatory penalties and reputational risk if the audit revealed non-compliant data handling practices.
Solution
Hir Infotech engaged the client’s compliance, IT, and data teams to map data flows and define cleansing rules aligned with GDPR Article 5 accuracy requirements and FCA data governance guidelines. We cleansed 95,000 client records — standardizing names, addresses, and ID formats across UK, German, and Swiss postal conventions; flagging and suppressing 7,200 records lacking valid consent documentation; deduplicating cross-business profiles; and delivering a clean, audit-ready dataset with full change documentation.
Results
- 7,200 non-compliant records identified and suppressed prior to audit
- Duplicate client profiles reduced by 89%
- Successful FCA audit with no data governance findings
- Client communication accuracy improved — returned mail rate dropped from 11% to under 1.5%
- Compliance team reported 40% reduction in manual data remediation hours monthly
Client Testimonial
“Facing a regulatory audit with data in that state was a serious concern. Hir Infotech’s team was methodical, thorough, and clearly understood the compliance requirements. We passed our audit with zero data issues — that outcome alone was worth every penny of the engagement.”
— Chief Compliance Officer, Wealth Management Firm, London, UK
Client Background
A mid-sized Australian multi-category e-commerce retailer operating across their own Shopify store and third-party marketplaces including Amazon AU and eBay Australia, with a product catalog of 85,000+ SKUs across electronics, home goods, and fashion.
Challenge
The retailer’s product catalog had been imported from four separate supplier feeds using inconsistent naming conventions, attribute structures, and category hierarchies. Over 30% of listings contained duplicate SKUs, incorrect attributes (wrong dimensions, mismatched colours), truncated descriptions, and non-compliant category mappings. The result was poor search visibility, elevated return rates (customers receiving the wrong product), and marketplace suppression notices from Amazon AU.
Solution
Hir Infotech conducted a full catalog audit and applied our product data cleansing pipeline: deduplicating SKUs, standardizing product titles against marketplace style guides, normalizing attribute fields (size, colour, material, weight, dimensions), enriching missing product descriptions using structured templates, and reclassifying products to correct category hierarchies for Amazon AU and eBay Australia taxonomy.
Results
- 26,000+ duplicate and erroneous SKUs resolved
- Product listing suppression issues cleared on Amazon AU within 30 days
- Organic search impressions on Amazon increased by 41% in 60 days post-cleansing
- Product return rate dropped from 9.2% to 3.8%
- Average order value improved by 12% attributed to improved product discovery and accurate descriptions
Client Testimonial
“We had no idea how much damage dirty product data was doing to our marketplace rankings and return rate. Hir Infotech fixed years of catalog chaos in weeks. The improvement in our Amazon AU search visibility was almost immediate.”
— Head of Digital Commerce, Multi-Category Retailer, Sydney, Australia
Client Background
A multi-state US healthcare provider network operating across 14 facilities in Texas, Florida, and Ohio, managing a centralized patient database of 1.2 million records accumulated across 12 years of operations and three system migrations.
Challenge
Multiple EHR system migrations had left the patient database riddled with duplicates, inconsistent demographic records, invalid insurance IDs, and missing critical clinical data fields. The network faced HIPAA compliance risk, insurance claim rejections due to patient record mismatches, and patient safety concerns from care teams working with fragmented records.
Solution
Hir Infotech deployed a HIPAA-compliant data cleansing workflow, including encrypted data transfer protocols and signed BAA agreements. Our team performed probabilistic matching to identify duplicate patient records (same patient, different ID formats), standardized demographic fields (DOB formats, address structures, name formatting), validated insurance IDs against payer standards, and enriched records with corrected ZIP+4 postal codes for billing accuracy.
Results
- 148,000 duplicate patient records identified and consolidated
- Insurance claim rejection rate due to data errors reduced by 67%
- Record completeness improved from 72% to 96%
- Clinical care teams reported significantly improved confidence in patient histories
- Zero HIPAA compliance findings in subsequent CMS audit
Client Testimonial
“Patient safety depends on accurate records. Hir Infotech handled our most sensitive data with absolute professionalism and delivered a cleansing outcome that directly improved clinical operations and our compliance posture. We consider them an indispensable long-term partner.”
— Chief Data Officer, Healthcare Provider Network, Dallas, Texas
Client Background
A large German manufacturing conglomerate with operations across Germany, Austria, and the Netherlands, running a centralized SAP S/4HANA ERP instance managing 45,000+ supplier records accumulated over 18 years.
Challenge
Decades of manual data entry, decentralized procurement processes, and three ERP migrations had created a supplier master dataset filled with duplicates, inconsistent VAT and IBAN formats across German, Austrian, and Dutch standards, missing contact details, and outdated supplier classifications. Procurement efficiency was suffering, and the finance team was processing duplicate vendor payments totaling an estimated €2.1 million annually.
Solution
Hir Infotech worked alongside the client’s SAP team to extract, profile, and cleanse the supplier master data. We applied European VAT number validation (Germany, Austria, Netherlands), standardized IBAN and BIC formats, resolved 8,400+ duplicate vendor records using entity resolution algorithms, reclassified suppliers against UNSPSC category codes, and validated contact details. Cleansed data was loaded back into SAP S/4HANA via validated data migration scripts.
Results
- 8,400+ duplicate supplier records resolved
- Duplicate payment risk eliminated — finance team recovered identification of €2.1M in duplicate payment exposure
- Supplier data completeness improved from 58% to 94%
- Procurement cycle time reduced by an estimated 22%
- SAP reporting accuracy improved significantly across accounts payable and spend analytics
Client Testimonial
“The scale of our supplier data problem was something we had been avoiding for years. Hir Infotech made it manageable, methodical, and fast. The financial impact was immediate and measurable. Their understanding of SAP data structures and EU compliance standards was impressive.”
— Head of Procurement Systems, Manufacturing Group, Munich, Germany
Client Background
A UK-based online real estate platform aggregating property listings and agent profiles from over 8,000 independent estate agencies across England, Scotland, and Wales, with a database of 3.2 million property listings and 120,000 agent profiles.
Challenge
The platform’s aggregation model pulled data from hundreds of feeds with inconsistent formats, duplicate listings from the same property listed by multiple agents, incorrect postcodes, missing EPC ratings (required by UK regulations), and outdated agent contact information. Duplicate listings frustrated users and damaged search experience quality, while non-compliant listings exposed the platform to Trading Standards risk.
Solution
Hir Infotech applied a multi-stage property data cleansing process: deduplicating listings using address matching and Royal Mail PAF validation, standardizing property attributes (bedroom count, property type, tenure), flagging and removing listings with non-compliant or missing EPC data, and cleansing agent profiles to verify emails, phone numbers, and agency registration details.
Results
- 420,000+ duplicate property listings identified and resolved
- Royal Mail PAF address validation applied to 100% of listings
- Regulatory compliance rate for EPC inclusion improved from 71% to 99.3%
- User session duration on property search increased by 18% post-cleansing
- Agent contact email deliverability improved from 78% to 97.4%
Client Testimonial
“The quality of listings on our platform directly drives user trust and SEO performance. Hir Infotech’s team understood both the technical and regulatory complexity of UK property data. The improvement in data quality was transformational for our product team.”
— CTO, Real Estate Aggregation Platform, London, UK
Client Background
A mid-market logistics and distribution company based in Rotterdam, the Netherlands, operating last-mile delivery services across the Netherlands, Belgium, and Germany, with a customer database of 280,000 B2B and B2C consignee records and a route optimization system dependent on accurate address data.
Challenge
Address data quality issues were causing delivery failures at a rate of 4.8% — well above industry benchmarks. Incorrect postal codes, missing apartment/floor details, formatting inconsistencies across Dutch, Belgian, and German address conventions, and duplicate consignee records were costing the business an estimated €380,000 annually in failed delivery attempts and rerouting costs.
Solution
Hir Infotech applied address cleansing and validation protocols aligned with Dutch PostNL, Belgian bpost, and German Deutsche Post address standards. We standardized address formats across all three markets, validated against official national address registries, identified and merged 18,000+ duplicate consignee records, and enriched records with geo-coordinates for improved route optimization compatibility.
Results
- Delivery failure rate reduced from 4.8% to under 0.9%
- 18,000+ duplicate consignee records resolved
- Address validation coverage reached 99.1% across NL/BE/DE
- Annual failed delivery cost savings estimated at €340,000+
- Route optimization model accuracy improved by 31%
Client Testimonial
“In logistics, address accuracy is everything. Hir Infotech understood the complexity of operating across three different national address systems and delivered a solution that immediately improved our delivery performance. The cost savings were significant and rapid.”
— Operations Director, Logistics & Distribution, Rotterdam, Netherlands
Working with Hir Infotech
Data you can trust
Rely on Hir Infotech for 95%+ accurate data, meticulously verified to fuel your B2B success. Our global scraping solutions deliver trusted insights for confident decision-making worldwide.
Decades of experience
With 12+ years of expertise, Hir Infotech has served 2745+ clients globally. Our proven scraping solutions drive B2B success across the USA, Europe, and Australia.
Legal peace of mind
Rely on Hir Infotech for 95%+ accurate data, meticulously verified to fuel your B2B success. Our global scraping solutions deliver trusted insights for confident decision-making worldwide.
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Ready to Transform Your Data Quality?
Your business runs on data — make sure that data is working for you, not against you. Hir Infotech has helped 2,745+ mid-market and enterprise clients across the USA, Europe, and Australia unlock the true value of their data through AI-powered, compliance-aware data cleansing services. With 13+ years of proven experience and a global delivery team ready to scale to your requirements, we’re the trusted partner your data strategy deserves.
No commitment required. See the Hir Infotech difference on your own data — request your complimentary sample cleanse today.
Unlock Business Growth with Expert Data Cleansing Solutions.
Benefits of Data Cleansing for Enterprise B2B Organizations
Flexible Pricing Models
Project-Based (Flat Fee) Pricing
A one-time fee is charged for a specific project, regardless of volume or duration, based on scope and complexity.
Hourly or Time-Based Pricing
Billed based on the time spent developing, running, or maintaining the scraper, often used for custom or consulting-heavy projects.
Pay-As-You-Go
Charged based on actual usage, such as per request, per GB of bandwidth, or per page scraped, with no fixed commitment.
Subscription-Based Pricing
pay a recurring fee (monthly or annually) for access to scraping services, often tiered based on usage limits like the number of requests, pages scraped, or data points extracted.
Hir Infotech’s Web Scraping Methodology
1
Understanding Your Goals
We begin by collaborating with you to define your data needs—be it for a one-time project, recurring insights, or custom solutions. Whether you opt for Pay-As-You-Go flexibility, a Project-Based Flat Fee, Hourly expertise, or a Subscription plan, we align our approach to your objectives.
2
Target Identification & Planning
Our team identifies the websites and data sources critical to your project. We analyze site structures, assess complexity (e.g., static vs. dynamic content), and plan the most efficient scraping strategy, ensuring compliance with public data access norms.
3
Advanced Data Extraction
Using cutting-edge tools and custom-built scrapers, we extract data at scale. We tackle challenges like JavaScript-rendered pages or anti-scraping measures with techniques such as:
- Rotating proxies to avoid blocks.
- Headless browsers (e.g., Selenium) for dynamic content.
- Optimized request pacing to mimic human behavior.
4
Data Processing & Quality Control
Raw data is parsed, cleaned, and structured into formats like CSV, JSON, or Excel. We remove duplicates, correct errors, and validate accuracy to ensure you receive reliable, ready-to-use datasets.
5
Delivery Tailored to You
Depending on your pricing model, we deliver results how and when you need them:
- Pay-As-You-Go: On-demand data for ad-hoc use.
- Project-Based: Complete datasets for one-off projects.
- Hourly: Iterative updates during custom development.
- Subscription: Regular, automated feeds for ongoing insights.
6
Ongoing Support & Optimization
We monitor site changes, adapt scrapers as needed, and provide support to keep your data flowing seamlessly. Subscription clients enjoy continuous updates, while Hourly clients benefit from hands-on refinements.
Let's build something great together.
Contact us for top-tier talent and exceptional results.
We’ve been working with Hir Infotech for our data scraping needs, and they have exceeded our expectations. The data they provide us is always accurate, timely and helps us make more informed decisions. The team at Hir Infotech is always responsive, and we appreciate their high level of expertise.
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Frequently Asked Questions
What exactly is data cleansing, and how is it different from data enrichment?
Data cleansing (also called data cleaning or data scrubbing) is the process of detecting and correcting inaccurate, incomplete, duplicate, or improperly formatted records within a dataset. It involves removing or fixing errors, standardizing field formats, resolving duplicates, and validating records against trusted reference sources. Data enrichment, by contrast, involves appending additional information to existing records — such as adding missing phone numbers, firmographic data, or technographic signals. Hir Infotech provides both services, and in most enterprise engagements, cleansing and enrichment are performed together to deliver maximum data quality improvement.
How does Hir Infotech ensure GDPR and CCPA compliance during data cleansing?
Compliance is embedded into every stage of our data cleansing workflow. For GDPR (EU), we apply Article 5 accuracy requirements and can identify records lacking valid consent documentation for suppression or deletion. For CCPA (California), we support consumer data rights workflows including right-to-deletion management. We operate under data processing agreements (DPAs), use encrypted data transfer protocols (SFTP/TLS), and maintain full audit trails of every change made during cleansing. Our team includes compliance-aware data specialists with direct experience in EU, UK, US, and Australian regulatory environments.
What volume of data can Hir Infotech process, and how fast?
Hir Infotech’s data cleansing infrastructure is built for enterprise scale. We regularly process datasets ranging from 10,000 records to 50+ million records. Processing timelines depend on dataset size, complexity, and the number of cleansing operations required — but typical enterprise CRM cleansing projects (100,000–500,000 records) are completed within 10–21 business days. For urgent requirements, we offer expedited processing. Large-scale catalog and transactional datasets are processed via our automated pipeline infrastructure with parallel processing capability.
Which CRM, ERP, and data platforms do you integrate with?
Hir Infotech delivers cleansed data in formats compatible with all major enterprise platforms, including Salesforce, HubSpot, Microsoft Dynamics 365, SAP S/4HANA, Oracle ERP Cloud, Zoho CRM, Marketo, Pardot, Snowflake, BigQuery, Databricks, and custom data warehouses. We deliver outputs as CSV, JSON, XML, SQL scripts, or via direct API integration. For enterprise clients, we can configure automated, recurring cleansing workflows that deliver clean data on a scheduled cadence directly into your system of record.
How do you handle sensitive data such as healthcare, financial, or HR records?
For sensitive data categories, Hir Infotech applies enhanced security protocols as standard. Healthcare data (HIPAA-regulated, USA; covered entities and business associates) is processed under signed BAA agreements with encrypted-at-rest and in-transit data handling. Financial and client data subject to FCA, MiFID II, or Swiss FINMA requirements is handled with jurisdiction-appropriate safeguards. All personnel accessing sensitive datasets operate under NDAs and role-based access controls. We are happy to provide our full data security framework documentation as part of vendor due diligence.
Can you perform ongoing/recurring data cleansing, or is it a one-time service?
Both models are available. Many clients begin with a one-time deep cleanse to establish a clean baseline, followed by a scheduled recurring cleansing programme (monthly, quarterly, or semi-annual) to address ongoing data decay. Given that B2B contact data decays at approximately 22.5% per year, ongoing cleansing is strongly recommended to maintain data quality over time. Hir Infotech offers managed data quality programmes that include automated monitoring, anomaly alerting, and scheduled cleansing cycles — ensuring your datasets remain accurate, complete, and compliant on a continuous basis.
What industries does Hir Infotech serve with data cleansing?
Hir Infotech serves B2B organizations across a broad range of industries, including financial services and banking, healthcare and life sciences, e-commerce and retail, SaaS and technology, manufacturing and supply chain, real estate and property, logistics and distribution, professional services, education, and media and publishing. We have active clients across the USA, UK, Germany, France, Netherlands, Sweden, Denmark, Italy, Spain, Austria, Switzerland, Iceland, and Australia — with deep familiarity with the data standards, regulatory requirements, and industry-specific data structures relevant to each market.
How do you measure and report on data quality improvements?
Every engagement begins with a baseline data quality audit that scores your dataset across six dimensions: completeness, accuracy, consistency, validity, uniqueness, and timeliness. Post-cleansing, we deliver a comprehensive quality improvement report comparing before and after metrics across each dimension, detailing the exact number of records corrected, deduplicated, enriched, or removed. This documentation supports ROI reporting, compliance auditing, and internal data governance reviews. For recurring programmes, we provide monthly or quarterly dashboards tracking ongoing data quality metrics.
How is Hir Infotech different from using an off-the-shelf data cleansing tool?
Off-the-shelf tools are effective for simple, rule-based cleansing tasks on structured data. However, they struggle with complex deduplication across merged systems, industry-specific data standards, compliance-aware remediation, and multilingual or multi-regional data formats. Hir Infotech combines AI-powered automation with expert human review — particularly for edge cases, ambiguous records, and compliance-sensitive decisions that automated tools routinely mishandle. With 13+ years of experience across 2,745+ client engagements, we bring institutional knowledge that no SaaS tool can replicate. We also provide full audit documentation, SLA guarantees, and dedicated account management — services that generic tools do not offer.
What does the data cleansing process look like from start to finish?
Our process follows five structured phases: 1) Discovery & Scoping — we review your dataset, understand your systems, use cases, and compliance requirements, and agree on cleansing rules and deliverable formats. 2) Data Profiling & Audit — we run a full quality assessment to identify and quantify all issues. 3) Cleansing Execution — our AI pipeline processes the dataset, applying deduplication, standardization, validation, enrichment, and compliance remediation. 4) Quality Assurance — a human expert review layer checks edge cases, ambiguous records, and compliance flags. 5) Delivery & Reporting — we deliver the cleansed dataset in your preferred format along with a detailed quality improvement report and change log. Throughout the engagement, a dedicated project manager maintains regular communication with your team.