Demographic Data Scraping Services

Client Background: A mid-market specialty retail brand headquartered in Chicago with 180 stores across 22 U.S. states, planning a 40-store expansion over 24 months across the Southwest and Southeast regions.

Challenge: The client’s real estate team relied on a third-party demographic database that was updated annually and lacked the ZIP-code precision required for site selection in rapidly growing suburban markets. Inaccurate household income and population density data had already contributed to two underperforming store openings in the previous fiscal year.

Solution: Hir Infotech deployed an AI-powered demographic data scraping pipeline targeting U.S. Census Bureau ACS 5-Year Estimates, HUD location affordability data, and county-level economic development portals. The pipeline was configured to extract household income by ZIP, age distribution, daytime vs. residential population density, vehicle ownership rates, and retail spending index scores — refreshed monthly across 2,400 target ZIP codes. Data was delivered as a structured feed integrated directly into the client’s Power BI environment.

Results: Within 90 days, the client’s real estate analytics team identified 14 high-confidence expansion sites scoring in the top decile for all demographic criteria — compared to 3 sites identified using legacy data tools in the prior 6-month cycle. First-year revenue performance of the new sites opened using Hir Infotech’s demographic intelligence exceeded projections by 23%.

Client Testimonial: “The quality and freshness of the demographic data Hir Infotech delivered was unlike anything we’d seen from traditional data vendors. We now make real estate decisions with confidence rather than guesswork.” — VP of Real Estate Strategy, U.S. Retail Brand

Client Background: A Munich-based B2B SaaS company offering HR technology solutions, preparing to expand from DACH markets into France, the Netherlands, Sweden, and Denmark.

Challenge: The company’s product and go-to-market teams lacked current, country-specific workforce demographic data — including age distribution of active workforce populations, digital skills penetration, remote work adoption rates, and enterprise buyer concentrations by sector — that would be essential for product localization and sales territory planning.

Solution: Hir Infotech built a multi-source demographic data scraping architecture extracting from Eurostat, INSEE (France), CBS (Netherlands), SCB (Sweden), and Danmarks Statistik (Denmark). Custom extractors pulled workforce age pyramids, employment-by-industry breakdowns, enterprise density by NUTS-2 region, and technology adoption surveys from public government and EU commission sources. All data was delivered weekly in a structured JSON/CSV format with full GDPR compliance documentation.

Results: The client’s GTM team reduced market entry preparation time from 16 weeks to 6 weeks per country. Localized sales territories built on Hir Infotech’s demographic maps produced a 31% higher qualified pipeline in the first two quarters post-launch compared to territories built using generic market intelligence.

Client Testimonial: “Hir Infotech gave us a level of pan-European demographic detail that simply wasn’t available anywhere else at this quality, compliance standard, and speed. It materially accelerated our European expansion.” — CDO, Munich-Based HR Tech SaaS Company

Client Background: A Sydney-based non-bank lender offering personal and SME loan products across Australia’s eastern seaboard, operating in a competitive market dominated by the Big Four banks.

Challenge: The firm’s marketing team had limited visibility into the demographic composition of high-potential postcodes — specifically household income tiers, age demographics of homeowners vs. renters, and small business density — making it difficult to optimize direct mail, digital ad targeting, and broker partnership prioritization.

Solution: Hir Infotech deployed ABS Census scraping pipelines covering all 2,600+ Australian postcodes, extracting income quintile distributions, dwelling type (owned/rented/mortgaged), household size, age-of-head-of-household bands, and SME density from business register public data. Data was enriched with regional economic indicators from state government portals and delivered as a geocoded dataset integrated into the client’s Salesforce CRM via API.

Results: The client achieved a 41% improvement in direct mail response rates in the first campaign cycle using Hir Infotech’s demographic targeting data. Broker partnership investment was reallocated to high-density SME postcodes identified through the data, driving a 28% increase in SME loan originations in two quarters.

Client Testimonial: “We’d been flying blind on postcode demographics for years. Hir Infotech’s data transformed how we identify and prioritize markets — it paid back in the first campaign.” — Head of Marketing Analytics, Australian Non-Bank Lender

Client Background: A London-based pharmaceutical company preparing to launch a new treatment for a chronic metabolic condition in the UK and Ireland, requiring precise patient population mapping to prioritize HCP (healthcare professional) outreach and patient support programs.

Challenge: Available NHS Digital data was aggregated at CCG level and insufficiently granular for borough-level or GP-catchment targeting. The client needed current demographic profiles of at-risk age/BMI populations intersected with deprivation indices and healthcare access scores.

Solution: Hir Infotech developed a custom NHS Digital, Public Health England, and GOV.UK data scraping pipeline delivering postcode-level prevalence estimates, deprivation scoring (IMD), and age-stratified population counts for target demographic cohorts. Extraction was designed to operate within NHS Digital’s open data publication policies, with all personally identifiable patient data explicitly excluded from scope under GDPR compliance protocols.

Results: The medical affairs team identified 24 priority GP cluster zones representing 67% of the estimated target patient population — enabling a 40% reduction in HCP outreach budget while increasing program reach. The launch was recognized internally as one of the company’s fastest-ever market penetration achievements.

Client Testimonial: “The precision of the demographic mapping Hir Infotech provided changed our launch strategy entirely. The compliance rigor gave our legal team complete confidence.” — Director of Medical Affairs, UK Pharma Company

Client Background: A San Francisco-based online education platform serving 800,000+ adult learners, planning to expand its professional development curriculum into underserved mid-size U.S. cities.

Challenge: The product strategy team needed city-level and neighborhood-level data on adult education attainment rates, workforce sector composition, median age of workforce, and income-by-education-level distributions to identify where unmet professional upskilling demand was highest.

Solution: Hir Infotech’s AI scraping team built extractors targeting the U.S. Census Bureau’s Educational Attainment tables, Bureau of Labor Statistics Occupational Employment Statistics, and local workforce development board publications across 120 target cities. Data was normalized, geocoded, and delivered as a ranked opportunity index with composite demographic scores for each city and ZIP cluster.

Results: The client identified 18 high-priority metros with demographic profiles showing high workforce concentration in sectors targeted by the platform’s new curriculum — combined with below-average existing credential attainment — enabling a precise, data-backed product launch sequence. Beta enrollment conversion rates in the top-10 ranked markets exceeded projections by 36%.

Client Testimonial: “Hir Infotech’s demographic intelligence gave us the market clarity we’d been trying to build internally for two years, delivered in six weeks. It directly shaped our product roadmap.” — Chief Product Officer, U.S. EdTech Platform

Client Background: An Amsterdam-based fashion retailer with 95 stores across the Netherlands, Belgium, and Germany, seeking to build a granular consumer demographic model to power omnichannel personalization and local marketing programs.

Challenge: The company’s CRM held transaction data but lacked enriched demographic context — neighborhood-level age, household income, family composition, and cultural background indicators — that would allow meaningful micro-segmentation beyond purchase recency and frequency.

Solution: Hir Infotech deployed CBS (Netherlands), Statbel (Belgium), and Destatis (Germany) demographic data scraping pipelines, extracting postcode-level demographic profiles across all catchment areas surrounding each store. Data included age band distributions, household income quartiles, household composition (single/family/multi-generational), and population density — all delivered GDPR-compliant with no PII included, enriched into the client’s existing Salesforce Marketing Cloud environment.

Results: Micro-segmented local marketing campaigns built on Hir Infotech’s demographic layer achieved 27% higher email open rates and 19% higher in-store conversion rates compared to generic national campaigns. The client extended the demographic data subscription to cover five additional European markets within six months.

Client Testimonial: “The demographic enrichment Hir Infotech delivered transformed our segmentation from blunt to surgical. Our store teams now market like they truly know their local customer.” — CMO, Netherlands Fashion Retailer

Client Background: A Louisville, Kentucky-based regional health insurance carrier offering Medicare Advantage plans, competing for enrollment during the annual open enrollment period across six states.

Challenge: The carrier’s outreach team was over-investing in broad-market media placements with low conversion efficiency. They needed county-level and ZIP-level data on the 65+ population concentration, income eligibility bands, and chronic condition prevalence demographics to precision-target outreach and broker placement investments.

Solution: Hir Infotech extracted Medicare enrollment data, CMS plan comparison population statistics, CDC chronic disease demographic tables, and U.S. Census 65+ population data across all target counties and ZIPs. AI classification models were applied to weight and rank territories by composite demographic enrollment opportunity score, refreshed monthly during the 90-day enrollment window.

Results: The carrier reallocated 35% of outreach spend from low-density to high-density 65+ demographic markets. Enrollment growth in the current period exceeded prior year by 44% while total outreach cost per enrolled member fell by 22%.

Client Testimonial: “The demographic precision Hir Infotech delivered was a game-changer for our enrollment strategy. We stopped spending broadly and started winning specifically.” — VP of Sales & Distribution, U.S. Health Insurance Carrier