International Marketing Company – Geolocation Research Initiative
Drawing insights from geolocation data to optimize targeted ad campaigns.
Service: Data Science
Industry: Technology/Software/SaaS
Tech Stack: Apache Hive, Apache Spark, AWS Lambda, AWS S3, Jupyter, Pyspark
Profile & Challenge
Our client - a major marketing company - desired to create new location and behavior-based attributes for target consumers that could be leveraged in model and audience creation. The attributes would be derived from data related to driving patterns and locations provided to the client by a major vehicle manufacturer. This data set contained vast amounts of information but lacked the necessary context relating one action to another, making the data hard to parse and interpret for our client’s purposes.
SOLUTION & OUTCOME
By optimizing existing approaches to extract better results, GAP developed a new proprietary methodology for the creation of these attributes. Algorithms were created to identify drivers’ home and work location and “stopped by” locations - places a consumer is likely to visit before or after work. Using these data points, GAP created audience profiles for frequent and recent visitors to these businesses. By identifying places and patterns of consumer visits, this unique model allowed our client to create and place better-targeted ads based on a consumer’s rider journey.
ADDITIONAL PROJECTS
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