Local Business Data Sources by Country (US/UK/SG/IN)
most small businesses outsource market research to gut feel and a Reddit thread. that works for a while. it stops working when you need to defend a pricing decision, justify a market expansion, or convince a co-founder that the next geography is worth the effort. the gap is rarely intelligence, the data is usually free and waiting on a government portal nobody bothered to find. the gap is knowing which portal to open in which country for which question.
this guide is for solopreneurs, microbusinesses, and small SMEs operating in or expanding into the US, UK, Singapore, or India. by the end you will have a country-by-country reference of the most useful free and paid data sources, what each one is good for, what the data quality is actually like, and the typical workflow for pulling research without wasting half a day. nothing exotic, just the sources operators in each country actually rely on.
why country-specific data sources matter
global tools like Statista, IBISWorld, and Euromonitor are excellent. they are also expensive and they aggregate. when you need the actual demographic count of a postal code, the actual number of registered F&B businesses in your suburb, or the actual import-export tonnage on your product category, you need primary national sources, not a global aggregator’s summary.
Local business data sources by country in 2026 vary widely in quality and access. The US has the deepest open ecosystem (Census, BLS, BEA, IRS, FRED), the UK has high-quality government open data (ONS, Companies House, gov.uk data portal), Singapore offers excellent SME-targeted data (data.gov.sg, IMDA, Statistics Singapore, Enterprise Singapore), and India has rapidly improving open data (data.gov.in, MoSPI, MCA21) plus the strongest payments and financial data via UPI and RBI. Most operators only need 5-10 sources per country; the rest is noise.
context matters. the same question (how many bakeries are there in my catchment) has different answers depending on whether you ask a US zip code, a UK postcode, a Singapore subzone, or an Indian PIN code, and the data sources that answer it differ.
United States: the open data heartland
the US runs the deepest open data ecosystem of the four countries. it is also the most fragmented.
the foundational sources
US Census Bureau. demographics, economic census, county business patterns. the County Business Patterns dataset is the closest you get to free industry-level firm counts at the zip-code level.
Bureau of Labor Statistics (BLS). employment, wages, occupational projections. excellent for staffing market analysis and hourly pay benchmarks.
Bureau of Economic Analysis (BEA). GDP by region and industry, personal income, trade. for state-level macro context this is the best free source.
Federal Reserve Economic Data (FRED). 800,000+ time series for economic data, interest rates, prices. the working economist’s quick lookup tool.
IRS Statistics of Income. small business income data by state and industry. less granular than Census but useful for tax-context benchmarks.
the local-level sources
state and city open data portals. NYC Open Data, LA Geohub, Chicago Data Portal, Austin Open Data are the most extensive. quality varies wildly by state. for the Singapore government data sources parallel comparison, the Singapore open ecosystem is more centralized than the US patchwork.
Yelp, Google Maps, OpenStreetMap. for businesses-by-category data at neighborhood level, these scrape better than any government source. follow each platform’s terms of service.
the paid sources worth their cost
Reference USA, ZoomInfo, D&B Hoovers. for B2B contact and firmographic data at scale. typically $5,000-25,000/year. realistic for shops with five-figure deal sizes.
Mintel, IBISWorld, Statista Pro. industry reports and consumer demographics. typically $1,000-5,000 for an industry report, $300-2,000/mo for a subscription.
United Kingdom: structured and accessible
the UK runs a tighter, more centralized open data system than the US. less data total, but easier to navigate.
the foundational sources
Office for National Statistics (ONS). UK census, business demography, regional economic indicators. the IDBR (Inter-Departmental Business Register) is excellent for industry firm counts at local authority level.
Companies House. every UK company filing, free, with API access. for B2B research this is the single best free source in the UK.
gov.uk data portal. centralized index of UK government open data. quality varies but the index makes finding sources quick.
HMRC. tax statistics, including VAT-registered businesses by region and industry. less granular than ONS but useful for tax-context benchmarks.
UK Trade Info. import-export data by HS code. for product-led businesses sourcing or selling internationally, indispensable.
the local-level sources
local authority open data portals. London Datastore, Greater Manchester open data, Bristol open data. patchier than the US city portals.
Nomis. ONS-hosted labour market and population statistics interface. easier to query than the raw ONS site.
Land Registry price-paid data. property transactions by postcode. for retail and hospitality location analysis, the gold standard.
the paid sources worth their cost
YouGov, Mintel UK, Kantar. for consumer research and brand tracking. typically £2,000-10,000 for a study, £500-2,500/mo for a subscription.
Experian Mosaic, CACI Acorn. household-level demographic and lifestyle segmentation. typically £5,000-25,000/year. realistic for direct mail and location-decision use cases.
Singapore: SME-friendly and centralized
Singapore runs the most SME-targeted open data ecosystem of the four countries. less raw data total than the US or UK, but more relevant per capita for small business operators. the Singapore government data sources complete guide for researchers covers this in depth.
the foundational sources
Department of Statistics Singapore (DOS). SingStat tables, economic survey of services and manufacturing, household expenditure survey. the SingStat Table Builder is the practical entry point.
data.gov.sg. centralized open data portal. cleaner than the US or UK equivalents. quality varies but the navigation is excellent.
Enterprise Singapore. SME profile statistics, industry transformation maps, market reports for export markets. specifically aimed at SMEs.
ACRA Bizfile. every Singapore-registered business, fileable via API. less detailed than Companies House but functional.
Monetary Authority of Singapore (MAS). financial sector statistics, exchange rates, monetary indicators.
the local-level sources
URA Master Plan and SLA data. retail and commercial unit data by subzone. critical for F&B and retail location decisions.
LTA Datamall. transport data, including bus and MRT ridership at station level. useful for footfall context.
HDB sales transactions. resale price data by block and town. for retail catchment analysis.
the paid sources worth their cost
Nielsen Singapore, Kantar Singapore. consumer panel and brand tracking. typically S$5,000-30,000 for a study.
Euromonitor Singapore reports. industry overviews from a global perspective. typically S$1,500-5,000 per report.
India: rapidly improving open data plus payments depth
India has improved dramatically in open data over the last five years. data.gov.in, MoSPI, and the MCA21 portal are now competitive with most OECD equivalents. payments data via UPI is genuinely world-leading.
the foundational sources
Ministry of Statistics and Programme Implementation (MoSPI). National Sample Survey, Periodic Labour Force Survey, Consumer Pyramids household survey. the working source for India macro and household-level analysis.
data.gov.in. centralized open data portal. quality and coverage are catching up to OECD peers. the navigation is improving.
MCA21 portal. every India-registered company filing, free. the equivalent of the UK Companies House. searchable but the UI is aged.
Reserve Bank of India (RBI). financial sector statistics, monetary indicators, banking sector aggregates, UPI transaction volumes. UPI is the world’s largest real-time payment system, the data is extraordinarily detailed.
GSTN. GST returns aggregate data by state and HSN code. for product-led businesses tracking sector activity.
the local-level sources
state open data portals. Telangana, Karnataka, Andhra Pradesh, Maharashtra, and Tamil Nadu run the strongest state open data sites. Delhi and Mumbai are catching up.
DGCI&S. import-export data by HS code. for product-led businesses sourcing or selling internationally.
NPCI UPI dashboard. real-time UPI transaction volumes. the world’s most detailed retail payments dataset by ecosystem.
PRS Legislative Research and IndiaStat. excellent third-party aggregators of government data, often easier to navigate than the original sources.
the paid sources worth their cost
Centre for Monitoring Indian Economy (CMIE). Prowess, Economic Outlook, Consumer Pyramids. typically INR 50,000-500,000/year. the dominant private aggregator of India macro and firm data.
Nielsen India, Kantar India. consumer panel and retail measurement. typically INR 5-30 lakh for a study.
YouGov India, Ipsos India. attitudinal and brand surveys. typically INR 3-10 lakh per study.
the comparison table: country by country, source by question
| question | US | UK | Singapore | India |
|---|---|---|---|---|
| firm count by industry and region | County Business Patterns | ONS IDBR | SingStat / Enterprise SG | MoSPI / data.gov.in |
| company filings | state SOS | Companies House | ACRA Bizfile | MCA21 |
| household income | Census ACS | ONS | DOS Household Expenditure Survey | NSS / PLFS |
| demographics | Census Bureau | ONS Census | DOS | MoSPI / Census 2011 (2021 pending) |
| trade data | USITC DataWeb | UK Trade Info | TradeStat (Enterprise SG) | DGCI&S |
| consumer panel (paid) | Mintel, IBISWorld | Kantar, Mintel UK | Nielsen, Kantar SG | Nielsen India, CMIE Consumer Pyramids |
| company-level firmographics (paid) | ZoomInfo, Reference USA | Dun and Bradstreet UK | Statista SG | Tracxn, CMIE Prowess |
| real-time payments | not available | not available | not centrally available | NPCI UPI dashboard |
note the variance. the US wins on raw breadth. the UK wins on company filing depth. Singapore wins on SME targeting and centralization. India wins on payments and increasingly on macro depth.
the typical research workflow by country
once you know the sources, the workflow is similar across all four countries.
step 1: scope the question precisely
what specifically do you need to know, and what decision will the answer drive. “what is the addressable market” is too vague. “how many F&B outlets exist within 1km of three candidate locations in my city” is precise. precise scoping cuts research time by 80%.
step 2: identify the right primary source
use the table above. start with the free government source. fall back to paid only when the free one cannot answer.
step 3: pull the data and clean it
most government data downloads in CSV or Excel. some need a quick clean pass. the excel index match tutorial better than VLOOKUP covers the patterns that come up most.
step 4: triangulate with a second source
never trust a single source for a decision. always check a second source, ideally from a different category (paid vs free, government vs industry). the ASEAN market research data sources 2026 approach to triangulation generalises well.
step 5: ask the obvious AI question
upload the cleaned data to ChatGPT or Claude. ask it the obvious questions you would ask a junior analyst. fact-check anything that surprises you. the ChatGPT Code Interpreter tutorial 2026 covers the technique.
sources to skip in each country
every country has popular sources that under-deliver. avoid these unless you have a specific reason.
US
free LinkedIn data scrapers. against terms of service and the data quality is poor.
old Census tables before 2020. demographics shift fast, post-COVID data is materially different from pre.
UK
postcode-only datasets without context. UK postcodes can cover wildly different demographics. always pair postcode data with income or social grade.
Singapore
national-level retail data without subzone breakdown. Singapore retail varies massively by subzone, national averages mislead.
India
old NSS rounds before 2017. India’s economy has restructured significantly since GST, post-2017 data is more reliable.
conclusion: the right source beats the expensive one
the local data is almost always available for free, you just need to know which portal to open. the trap most operators fall into is paying $2,000 for a Statista report when the underlying data is on a government portal in the same country. learn the country-specific sources once, and you save thousands per year on research that you can run yourself.
actionable next step: this week, bookmark the foundational sources for your primary country (the four to five entries listed above per country). pick one specific question your business needs answered, and try to answer it using only the free sources. measure how long it takes you. if it works, you have a process. if it does not, that is when you graduate to a paid source.
if you want the country-deep companion guides, see the best US small business data tools 2026, UK SME analytics tools 2026, best data analysis tools for Singapore SMEs 2026, and India SaaS analytics stack 2026 pieces. for the wider regional view see the ASEAN market research data sources 2026 reference. need help finding the right source for a specific question? drop us a line via the contact form.