Neighborhood Patterns
Overview
Advan Research’s Neighborhood Patterns dataset contains footfall data aggregated by census block
group (CBG) in the U.S. Learn which day of the week a CBG is busiest, what time of the day a CBG is busiest, where devices that stop during breakfast, lunch, and dinner travel from, and how weekday and weekend demographics compare. This data is ideal for site-selection use cases and other use cases where you need to understand how busy an area is, when it is busy and the demographics of the visitors.
| Data Information | Value |
|---|---|
| Refresh Cadence | Monthly |
| Historical Coverage | 2019-Present |
| Geographic Coverage | United States,Canada |
Schema
| Name | Description |
|---|---|
| AREA | The designation of the area being described. Canadian DAshave a "CA:" prefix to differentiate from US CBGs. |
| AREA_TYPE | The type of area specified in thearea column. Canadian DAs willhave 'Census Block Group' here. |
| ORIGIN_AREA_TYPE | The type of area used in the device_home_areas and device_daytime_areas columns. Canadian DAs have 'Census Block Group' here but both CBGs and DAs will appear in these columns. |
| DATE_RANGE_START | Start time for measurement period in ISO 8601 format of YYYY-MM-DDTHH:mm:SS±hh:mm (local time with offset from GMT). |
| DATE_RANGE_END | End time for measurement period in ISO 8601 format of YYYY-MM-DDTHH:mm:SS±hh:mm (local time with offset from GMT). The end time will be the last day of the month at 12 a.m. local time |
| DAY_COUNTS | The frequency of each day of the week that occurred in the date range in local time. |
| RAW_STOP_COUNTS | Number of stops by devices in our panel to this area during the date range. A stop must have a minimum duration of 1 minute to be included. The count includes stops by devices whose home area is the same as this area. |
| RAW_DEVICE_COUNTS | Number of unique devices in our panel that stopped in this area during the date range. This includes devices whose home area is the same as this area. |
| STOPS_BY_DAY | The number of stops in this area each day (local time) over the covered time period. |
| STOPS_BY_EACH_HOUR | The number of stops in this area that began each hour (local time) over the covered time period. |
| DEVICE_HOME_AREAS | The number of devices that stopped in this area by home origin area. The area itself is included as a potential key. |
| WEEKDAY_DEVICE_HOME_AREAS | This column is the same as device_home_areas except it only includes those devices that stopped in the area Monday through Friday local time. |
| WEEKEND_DEVICE_HOME_AREAS | This column is the same as device_home_areas except it only includes those visitors that visited on Saturday or Sunday local time. |
| BREAKFAST_DEVICE_HOME_AREAS | This column is the same as the device_home_areas except it only includes those devices that stopped in the area between 6 am and 10:59 am local time. |
| LUNCH_DEVICE_HOME_AREAS | This column is the same as device_home_areas except it only includes those devices that stopped in the area between 11 am and 2:59 pm local time. |
| DINNER_DEVICE_HOME_AREAS | This column is the same as device_home_areas except it only includes those devices that stopped in the area between 5 pm and 8:59 pm local time. |
| NIGHTLIFE_DEVICE_HOME_AREAS | This column is the same as device_home_areas except it only includes those devices that stopped in the area between 9 pm and midnight local time. |
| WORK_HOURS_DEVICE_HOME_AREAS | This column is the same as device_home_areas except it only includes those devices that stopped in the area between 7:30 am and 5:30 pm Monday through Friday local time. |
| WORK_BEHAVIOR_DEVICE_HOME_AREAS | This column is the same as work_hours_device_home_are as but only includes devices that dwelled for at least 6 hours and excludes devices whose visit is in the same gh7 as their home location. |
| DEVICE_DAYTIME_AREAS | This column is the same as work_hours_device_home_areas but only includes devices that dwelled for at least 6 hours and excludes devices whose visit is in the same gh7 as their home location. |
| DISTANCE_FROM_HOME | Median distance from home travelled by devices (of devices whose home we have identified) in meters. |
| DISTANCE_FROM_PRIMARY_DAYTIME_LOCATION | Median distance, in meters, traveled to the stopping point(s) within the area by devices from their device_daytime_area (of devices whose device_daytime_area we have identified). We determine device_daytime_area within 100 meters and find the median distance per device (if more than one stop in the area for a device) to calculate the median for all devices. |
| MEDIAN_DWELL | Median dwell time in minutes. Note that we are only including stops that have a dwell of at least 1 minute. |
| TOP_SAME_DAY_BRAND | Brands that the devices that stopped in this area visited in the same day as the stop in this area. Limited to top 20. The value shown for each brand is a percentage representing: devices going to both the brand and the area / total devices stopping in the area. |
| TOP_SAME_MONTH_BRAND | Brands that the devices that stopped in this area visited in the same month as the stop in this area. Limited to top 20. The value shown for each brand is a percentage representing: devices going to both the brand and the area / total devices stopping in the area. |
| POPULARITY_BY_EACH_HOUR | The number of stops in this area each hour (local time) over the covered time period, regardless of when the stop started. This is a complementary column to stops_by_each_hour. |
| POPULARITY_BY_HOUR_MONDAY | A 24-element array with one value for each hour of the day (hour 0 to hour 23) representing the number of stops that occurred for that hour on any Monday in the time range. |
| POPULARITY_BY_HOUR_TUESDAY | A 24-element array with one value for each hour of the day (hour 0 to hour 23) representing the number of stops that occurred for that hour on any Tuesday in the time range. |
| POPULARITY_BY_HOUR_WEDNESDAY | A 24-element array with one value for each hour of the day (hour 0 to hour 23) representing the number of stops that occurred for that hour on any Wednesday in the time range. |
| POPULARITY_BY_HOUR_THURSDAY | A 24-element array with one value for each hour of the day (hour 0 to hour 23) representing the number of stops that occurred for that hour on any Thursday in the time range. |
| POPULARITY_BY_HOUR_FRIDAY | A 24-element array with one value for each hour of the day (hour 0 to hour 23) representing the number of stops that occurred for that hour on any Friday in the time range. |
| POPULARITY_BY_HOUR_SATURDAY | A 24-element array with one value for each hour of the day (hour 0 to hour 23) representing the number of stops that occurred for that hour on any Saturday in the time range. |
| POPULARITY_BY_HOUR_SUNDAY | A 24-element array with one value for each hour of the day (hour 0 to hour 23) representing the number of stops that occurred for that hour on any Sunday in the time range. |
| DEVICE_TYPE | The number of devices that stopped in the area that are using Android vs. iOS. |
| ISO_COUNTRY_CODE | The 2 letter ISO 3166-1 alpha-2 country code of the area |
| REGION | When iso_country_code == US, then this is the USA state or territory. When iso_country_code == CA, then this is the Canadian Province or territory. |
| Y | The year of the measurement period (included for easier filtering) |
| M | The month of the measurement period (included for easier filtering) |
Key Concepts
Visit Attribution
Advan Research computes the visits/visitors and other metrics inside a POI using the POI’s geometry. They do not apply any dwell time or any concept of “stops”; they rely on the polygon for accuracy. We have tested our data on 1,500 publicly traded tickers versus (a) top line revenue as reported from the companies and (b) credit card transaction counts on physical locations, and we have determined consistently that in the vast majority of cases filtering for dwell time reduces the signal and makes the correlation/forecasting worse.
Differential privacy is applied to visit fields. A random number between 0 and 5 in the US is added or subtracted to the number of stops and census block group visitors. In addition, if there is only one device in the home and daytime areas it is not reported at all; if there are between 2 and 4 devices, they are reported as 4; and, starting January 2023 in the US, only the 65th percentile of areas are included.
Determining Home Location
Advan Research computes a device’s home/work (night/day) location by looking at the previous calendar month and computing the time a device spent in each building in the country; then taking the most frequented building. They define daytime (work location) as 8am-6pm M-F. We define nighttime (home location) as 6pm-8am.
Panel
Along with the the Neighborhood Patterns, Advan Research also provides a Panel Overview Data to help you better understand the context of the data appearing in Neighborhood Patterns.
Home Location Distributions by State/Census Block Group ↗️
US and Canada POI
On Dewey, US and Canada are separated into distinct datasets. Depending on the geographic region of interest, select the corresponding dataset.
Updated about 1 month ago