Data monetization team scales location analytics delivery

Our client was a leading European telecommunications provider, operating one of the continent's largest mobile networks, and serving over 50 million customers across multiple markets. The client’s data monetization unit faced a critical gap when their former analytics partner became unavailable. The sudden shortage threatened their ability to deliver location intelligence and network usage insights to enterprise clients. We have deployed dedicated data science resources to their data commercialization unit, and have been continuously serving them for over three years.

140%

faster delivery time from client request to final report

92%

client retention rate across recurring and ad-hoc projects

35

clients served with location and network analytics

Challenge

The telecommunications provider, our primary client, has lost their data monetization team’s analytics partner, creating an urgent capability gap. This unit transforms raw telco data into commercializable analytics for external customers, sourced from anonymized location intelligence and network metadata, Aggregating and analyzing this information yields insights on population mobility, origin-destination flows, or internet traffic patterns. Technical complexity in this domain is substantial: understanding radio signal propagation for accurate positioning, filtering indoor versus outdoor movements, identifying transportation patterns from co-moving devices, and differentiating social media platforms through protocol analysis. With 10+ major annual clients expecting sophisticated, production-ready analytics while maintaining strict anonymization standards, our client’s team needed data scientists combining telecommunications domain expertise with advanced spatial analysis capabilities.

Solution

Our data science team delivered custom analytics as client needs emerged. Origin-destination analysis formed our core offering: mapping traffic flows with demographic segmentation for use cases ranging from retail site selection to planning large-scale events. Indoor traffic analysis required filtering algorithms distinguishing genuine visitors from passersby, leveraging cellular network specifications. We tracked public transport ridership by identifying co-moving devices, monitored protected area traffic, and on a particularly interesting occasion, successfully traced wildlife disease origin to national park visitors. Our telecommunications protocol expertise enabled social media platform differentiation from traffic metadata, The high number of available cells belonging to our client even enabled us to access location data with higher than average accuracy, allowing for device location triangulation. Our tech stack was always selected case by case, tailored to end user needs. We served 35 clients over three years with both recurring annual and ad-hoc project needs.