Methodology - Main

Dynamic Demographics Product Guide

Product type
Product family
Enrich Demographics > Segmentations and Geodemographics
Dynamic Demographics
Product name
Dynamic Demographics
Dynamic Demographics Product Guide
First publish date

Australia Dynamic Demographics combines data from Precisely's Estimates and Projections datasets with mobility data. A detailed methodology statement for Estimates and Projections is found in the Estimates and Projections Data Suite (Australia) Product Guide, available from Precisely's product management team.

Germany Dynamic Demographics and United Kingdom Dynamic Demographics combine GfK's demographic products with mobility data.

Mobility data is a highly complex dataset and prior to inclusion in Dynamic Demographics, it undergoes a set of processes that ensure the resulting product is a reflection of mobility patterns that are observed on the ground. Processing steps include, but are not limited to:

  • Filtering data on a rolling 12-month window using dates included in the mobility timestamp (OBS_START_DATE and OBS_END_DATE)
  • Filtering data on location accuracy
  • Filtering data on country boundary limits (i.e., geofencing at a national scale)
  • Removing records where location data is overly generalized (such as when accurate 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 or travel events using the following methodology:

Anonymized devices are located and aggregated at a Common Evening Location (SA1 or Uber HEX for Australia Dynamic Demographics; European Reference Grid – ERG – or HEX for Germany Dynamic Demographics; Output Area – OA – or Uber HEX for United Kingdom Dynamic Demographics). Note: This is based on dwell time and performed on a rolling 8-week window in order to allow for changes in a device's Common Evening Location during the time period.

Zones with an underlying address count of less than 20 are excluded across all countries. This process is utilized for privacy reasons, to ensure the CEL (Common Evening Location) is large enough in scale to not allow for any potential ability to identify an individual or individual household.

Using the Common Evening Location, aggregated device data is enriched with demographic information for the associated location

Flows for devices for each location at a given day part or week part are calculated. Note: Dwell time is used to exclude devices that are only passing through a location.

All profiles are aggregated to produce a new time-specific demographic profile

Metrics are created (refer to the Metrics definitions section of this product guide for additional information)