UTC_TIMESTAMP | HASHED_EMAIL | DEVICE_TYPE | VENUE_NAME | VENUE_TYPE | VENUE_SUBTYPE | VENUE_PLACE | PLACE | COUNTRY | STATE | CITY | POSTCODE | LAT | LONG |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
xxxxxxxxxxxxx | xxxxxxxxxx | xxx | xxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxxxx | xxxxxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxx | xxxxxxxxxxxxxxxxx | xxxxxxxxxxxxxxxxxx |
xxxxxxxxxxxxx | xxxxxxxxxx | xxx | xxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxxxx | xxxxxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxx | xxxxxxxxxxxxxxxxx | xxxxxxxxxxxxxxxxxx |
xxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxxxx | xxxxxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxx |
xxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxxxx | xxxxxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxx | xxxxxxxxxxx | xxxxxxxxxxxxxxxxxx |
xxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxxxxx | xxxxxxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxxx | xxxxxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxx | xxxxxxxxxxx | xxxxxxxxxxxxxxxxxx |
xxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxxx | xxxxxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxxx |
xxxxxxxxxxxxx | xxxxxxxxxx | xxx | xxxxxxxxxxxxxxxxxx | xxxxxxxx | xxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxxx | xxxxxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxx | xxxxxxxxxxxxxxxxxx | xxxxxxxxxxxxxxxxx |
xxxxxxxxxxxxx | xxxxxxxxxx | xxx | xxxxxxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxxxx | xxxxxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxx | xxxxxxxxxxxxxxxxx | xxxxxxxxxxxxxxxxxx |
xxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxxx | xxxxxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxx | xxxxxxxxxx | xxxxxxxxxx |
xxxxxxxxxxxxx | xxxxxxxxxx | xxxxxxx | xxxxxx | xxxxxxxx | xxxxxxxxxxx | xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx | xxxxxx | xxxxxxxxxxxxx | xxxxxxxx | xxxxxxxx | xxxxx | xxxxxxxxxxx | xxxxxxxxxxxx |
Attribute | Type | Example |
---|---|---|
UTC_TIMESTAMP | Integer | 1743477122063 |
HASHED_EMAIL | String | 28864ad2b68f2777394627feef5dce08d72ce39db064c9a8d338cdae2f4386e0 |
DEVICE_TYPE | String | iOS |
VENUE_NAME | String | O.N.S Clothing |
VENUE_TYPE | String | commercial |
VENUE_SUBTYPE | String | clothing |
VENUE_PLACE | String | {"placeId":"51d42b1b8cc77f52c0598bf47fcf595c4440f00103f90135fae0580200000092030e4f2e4e2e5320436c6f7468696e67","venueLocation":{"type":"Point","coordinates":[-73.9965544,40.7214908]},"venueName":"O.... |
PLACE | String | outside |
COUNTRY | String | United States |
STATE | String | New York |
CITY | String | New York |
POSTCODE | Integer | 10012 |
LAT | Float | 40.72163760172529 |
LONG | Float | -73.99649328166548 |
Description
Silencio’s Business-Type Segmented POI Dataset provides sector-specific footfall insights across industries such as fashion, hospitality, fitness, healthcare, and more. Built on 10M+ POI check-ins from an active base of 1M+ opted-in users, this dataset helps analysts and strategists understand consumer behavior and competitor performance in the physical world. Use this dataset to: • Benchmark footfall across different business categories • Conduct competitor analysis and market research • Identify trends in consumer engagement Strongest coverage: • Europe • Brazil • India • Nigeria • Philippines • Bangladesh • Pakistan • United States Delivered via CSV or S3. AI-powered segmentation is under development.
Country Coverage
(236 countries)Data Categories
- Point of Interest (POI) Data
- Visit Data
- Retail Data
- Retail Store Data
- Commercial Real Estate Data
Pricing
One-off purchase | $25K $22.5K |
Monthly License | $2.5K $2.25K |
Yearly License | $20K $18K |
Usage-based |
Not available |
Volumes
- Records
- 10M
- Attributes
- 14
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