A tablet with a pen above featuring the Cintric websiteCintric


Product Design, Information Architecture, Creative Direction, Motion Design, User Interface Design, Illustration, Back-End Developement


Data Analysis, Artificial Intelligence, Machine Learning


Figma, Adobe Illustrator, Adobe After Effects, Lottie, Python, HTML 5, CSS3, React Native

The Brief

Cintric developed a lightweight, mobile software development kit (SDK) that accurately measures the location signals of millions of users, providing powerful user behavioral pattern and location intelligence. With massive quantities of data streaming in, they needed a big data analytics solution to provide value to their customers.

The Challenge

Part of the challenge was creating the most battery-efficient SDK on the market. In the early days of mobile location tracking, GPS would quickly deplete any smartphone’s battery, leading to app uninstalls. This required innovative background tracking using a combination of wifi, bluetooth, inertial heading, GPS, and cell tower data to minimize the use of battery-intensive sensors. We had to come up with innovative processing approaches to minimize AWS costs and build machine-learning algorithms to convert raw location data into insights.

Three mobile phones featuring the cintric website pages

Our Approach

We determined user activity based on accelerometer activity to accurately associate them with individual visits to locations and time spent per location. This led us to create a solution for iOS and android which used less than 1% of the battery per day. Once the tracking SDK was deployed in enterprise apps, the volume of incoming data required scaling to many machines and a distributed database to handle it in real-time. We used innovative processing approaches to minimize AWS costs, including moving some processing to client-side code and clever data schemas in an elasticsearch database for queries.

Data was ingested via an AWS Firehose stream and processed from S3 in chunks and aggregated into an elasticsearch database. By using a custom, open street maps geocoding implementation, geo-clustering, and machine learning, data was able to generate consumer profiles and be accurately mapped to real-world locations. We built a custom analytics dashboard powered by this data in elasticsearch that allowed real-time aggregations, filtering, and data exploration.

Upon deployment, we were able to deliver a data-processing and machine-learning engine for Cintric. It was designed to process trillions of data points in real-time, in order to deliver consumer insights for retail brands. Users gained access to a powerful dashboard that can measure real-world impact of marketing campaigns, prevent store cannibalization, compare performance to competitors, and discover optimal locations to open and close.

100+ Trillion

Location data processed

300+ Trillion

Consumer profiles generated

75% Reduction

In AWS costs
Location data processed
Consumer profiles generated
In AWS costs

The Metrics

About the Company

Cintric was a venture-backed startup founded in 2014. They were a location intelligence and analytics company for mobile app publishers. The SDK they developed was the most battery-efficient on the market. Cintric was acquired by Ubermedia for their location analytics technology which Outliant developed. The acquisition was aimed to better serve marketers, advertisers, and media planners in the retail, auto, travel, and QSR sectors.