Lifesight Human Mobility & Footfall Data now available in CARTO

During the COVID-19 pandemic a key challenge has been sourcing data that is real-time enough to reflect the weekly and daily changes that affect consumer behavior. Human mobility data and footfall traffic in particular have undergone significant shifts as lockdown restrictions come and go in response to the surges of cases. This means that by the time that data has been sourced, evaluated, ETL’d, analyzed, and processed into insights, it is often no longer valuable or relevant to the business stakeholder looking to make a commercial decision.

For this reason having fast access to relevant, centralized, high quality, and near real-time location data, (including population, demographics, purchasing power, credit card transactions, points of interest, climate, road traffic, and much more) is crucial.

Today we are very pleased to announce our partnership with Lifesight, a leader in customer intelligence, & the inclusion of their mobility and people data in our Data Observatory.

Lifesight Mobility & People Data

Lifesight specializes in alternative consumer data collected from mobile audiences to provide intelligence covering consumer identity, behavior and interests. The company’s massive consumer datasets of over 2.3 billion profiles across the globe, in over 36 markets, and are designed to help users leverage alternative data for various use cases in industries such as CPG, retail, financial services and travel. Lifesight’s data arrives to complete the availability of human mobility data in CARTO’s Data Observatory especially in the APAC and ANZ territories.

Lifesight collects high quality persistent human mobility data from location aware mobile apps using an embedded SDK. Lifesight complies with global privacy regulations including CCPA and GDPR, and adheres to strict data collection (opt-in) and opt-out processes.

Foot Traffic Data

High quality persistent GPS-based mobile location data collected via SDK from mobile apps aggregated based on monthly averages segmented by day of week and part of day using the QuadGrid level 17 format, a standard grid system with cells sized approximately 300x300m.

• 59.4B Monthly Location Pings, 1.92B Daily Location Pings
• 90% Horizontal Accuracy
• 60 countries
• 2 years of past data available

This data product provides aggregated visitor data, also segmenting visitors by their home origin, place of work, and recently travelled countries.

Key variables (see all):

• Number of visitors
• Distance from home
• Visitors country of origin
• Visitors home origin
• Visitors place of work

People Data

This dataset complements the foot traffic data with visitor profiles ranging demographic attributes, technographics, brand affinity, locations and more. The data also comes aggregated in 300x300m grid cells based on monthly averages segmented by day of week and part of day.

• 910M Device Profiles
• 70% match rate
• 23 countries
• 2 years of past data available

Key variables (see all):

• Visitors other countries traveled
• Device characteristics
• Brand affinity
• Place category affinity
• Behavioral interests
• Ratio of visitors by age
• Ratio of visitors by gender
• Proportion residents
• Proportion workers
• Proportion others

If you are looking to understand more about how you might use Location Intelligence in your organization, you can explore our Customer Stories library here - or, you can speak to one of our spatial data experts to discuss potential use cases - simply contact us here.

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 960401.