Case Study: FLO expands EV charging coverage with dataplor POI data

How FLO® Utilizes dataplor’s POI Data to Enrich its EV Charging Coverage

FLO, a leading electric vehicle charging network in North America, faced a challenge with outdated and inaccurate points of interest (POI) data from its previous provider. This unreliable data, which was only updated annually and caused issues in bilingual regions, hindered their efforts to build predictive models for optimizing EV charger placement. To address this, FLO turned to the global location intelligence data from vendor dataplor.

dataplor provided a solution with a POI dataset that offered 65% more records, superior accuracy, and regular updates. This enabled FLO to significantly improve its machine learning models for predicting charger utilization and better target potential hosts for new installations. The results included increased prediction accuracy, more efficient network expansion, and a streamlined process for deploying new chargers.

FLO

Julien Lebrun

Network Planning Lead