Methodology - dynamic_neighborhoods - Latest

Dynamic Neighborhoods US Product Guide

Product type
Data
Portfolio
Enrich
Product family
Enrich Demographics > Segmentations and Geodemographics
Product
Dynamic Neighborhoods
Version
Latest
ft:locale
en-US
Product name
Dynamic Neighborhoods US
ft:title
Dynamic Neighborhoods US Product Guide
Copyright
2025
First publish date
2025
ft:lastEdition
2026-04-22
ft:lastPublication
2026-04-22T18:20:11.455000
L1_Product_Gateway
Enrich
L2_Product_Segment
Data
L3_Product_Brand
Precisely Demographics
L4_Investment_Segment
Precisely Demographics
L5_Product_Group
Segmentations & Geodemographics
L6_Product_Name
Segmentations

Dynamic Neighborhoods US combines data from Precisely's GroundView: Complete dataset with Precisely PlaceIQ's mobility data. A complete methodology statement for GroundView: Complete is found in the GroundView: Complete US Demographic Estimates and Projections Data Suite Product Guide, available from Precisely's product management team or from help.precisely.com.

Mobility data from Precisely PlaceIQ is a highly complex dataset. Data from this dataset undergoes a series of processes to ensure than the resulting product reflects mobility patterns that are observed on the ground and that privacy is protected prior to being included in Dynamic Neighborhoods US. Processing steps include, but are not limited to:

  • Filtering data on a rolling 3-month window using dates included in the mobility timestamp (OBS_START_DATE and OBS_END_DATE)
  • Filtering data on location accuracy
  • Filtering data on US basemap boundaries
  • Removing records where location data is overly generalized (such as where GPS-based location is not available)
  • Filtering out permanently stationary devices
  • Removing records with unrealistic travel time between two points

After processing, mobility data is combined with demographic data, and is clustered based on dwell time using the following methodology:

  • Anonymized devices are located and aggregated, then an algorithm determines home and work dwells for all devices. These dwells are updated frequently to account for changes during the time period.
  • Block groups with fewer than 20 addresses are excluded. This process is utilized for privacy reasons, to ensure than the home dwell location is large enough in scale to not allow for any potential ability to identify an individual or individual household.
  • Using the home dwell location, aggregated device data is enriched with demographic information for the associated location
  • Flows for devices for each location at a given day part and week part are calculated. Dwell time is used to exclude devices that are only passing through a location.
  • All profiles are aggregated at the destination area to produce a new time-specific demographic profile
  • Metrics are created (refer to the Metrics definitions section of this product guide for additional information)