microtarget's data
200+ microterritorial indicators at 100m grid level across Spain. Built with proprietary data. Ready to integrate.
What microtarget data contains
Microterritorial indicators are socioeconomic, demographic and behavioural variables calculated at 100m-side grid level across all Spanish territory. Unlike census data — available by census section or municipality — these indicators have a granularity that allows street, block or building-level analysis.
microtarget offers over 200 of these indicators, grouped into 12 thematic categories, built with proprietary sources and estimation models developed in-house by unica360.
Indicators
1. Demographics
Resident population by age, gender and origin. Education level, households, people per household.
Source: Municipal register + proprietary models.
2. Income and spending
Average income per capita and per household. Estimated spending by category: food, leisure, clothing, transport, health.
3. Housing and property
Average surface area, age, number of floors, detached houses, garden, land use.
Source: Land Registry + models.
4. Retail supply
Density of retail, hospitality, transport, culture and health establishments. By type and category. Over 30 subcategories.
5. Urbanity and centrality
Population density index and degree of urbanity. Urban/peri-urban/rural distinction at grid level.
6. Green areas
Proximity to parks and green areas. Accessible surface area within a 5, 10 and 15-minute walking radius.
7. Foot traffic
Pedestrian presence model at street-segment level. Broken down by time slot (morning/afternoon/night) and day type (weekday/weekend/summer).
8. Vehicle traffic
Vehicle flow by time slot and day type. Weekday/weekend distinction.
9. Floating working population
Population presence for work purposes. Useful for retail, hospitality and service planning.
10. Tourism
Tourist presence model by area. Seasonality, origin and length of stay.
11. Neighbourhood typology
Microterritorial classification by combination of socioeconomic, commercial and urban planning characteristics.
12. Lifestyles
Attitudes, values, perceived quality of life. Variables derived from territorialised psychographic models.
The indicators are delivered in three formats depending on your use case:
API
real-time lookup by address or coordinate →
Dataset
Contact us to download our full dataset →
Aplicación online
visual lookup, no code required →
The base granularity is the 100m grid; aggregation by census section, postcode or municipality is also available.
Use cases of the geodata has applied examples for each category, sector by sector.
FAQ
What granularity does the data have?
The base is the 100m-side grid (1.4 million cells for Spain). For Spain there's also a postcode variant, useful for cross-referencing with business data that uses postcode as a reference. Other aggregations — municipality, census section — are available on request.
What sources do the indicators come from?
From official and open sources: INE (including the Household Budget Survey, the Living Conditions Survey and the Household Finance Survey), the Spanish Tax Agency, the Land Registry, Eurostat and MITMA mobility data, complemented with POIs from directories and online APIs. On top of these sources, unica360 applies its own machine learning, NLP and simulation models to produce indicators the raw data doesn't offer, such as income at 100m resolution or pedestrian flows by street segment.
In what formats are they delivered?
REST API (real-time lookup by address or coordinate), a downloadable dataset in CSV, GeoJSON or Parquet, and an online location intelligence app for visual, code-free lookup.
How often are they updated? Are there historical series?
Most datasets are updated once a year; the exact date depends on the availability of the official source data. Demographics includes variables with a historical perspective of up to 15 years, suitable for trend analysis; for other categories, the latest available version is delivered.
How do your foot traffic and vehicle traffic indices differ from other data sources?
We simulate mobility with activity-based, agent-based models that generate synthetic data. Compared to mobile telecom data, they offer far greater spatial precision, legal certainty in any country, lower cost, and the ability to simulate scenarios that don't exist yet.
What exactly does the disposable income indicator measure?
The average disposable income per taxpayer (after tax) in each cell. It only considers the population that files a tax return: in areas with many non-filers (minors, pensioners below the threshold), it may underrepresent the household's real spending capacity. For purchasing power analysis, it's best combined with other income and spending indicators in the dataset.
Is the data comparable across countries?
The methodology is the same, but the specific variables may differ by country, because official sources (statistics offices, land registries, tax data) don't record the same things in every market. For multi-country projects, ask for a variable-by-variable comparison of the markets you're interested in.
Can I integrate the indicators into my models without processing personal data?
Yes. They're grid-level aggregated data: they contain no individual or identifiable information, so they can be integrated into models, scoring and applications without incorporating any third-party personal data into the processing.
Need to see the data before deciding?
Access the API or request a dataset sample.