EV Intelligence for charging operators

EV Intelligence for
Charge Point Operators

Optimize site location to drive ROI and maximize EV Charging Station performance

EV mobility is going through a crucial adoption process. Station deployment requires massive resources and finding the right location for EV charging stations that will maximize ROI and democratize service accessibility is a substantial hurdle. Guesswork-driven site selection translates into low performing stations that do not yield the desired returns. 

The Otonomo EV Intelligence solution enables EV charging providers, OEMs and cities going through the process of EV adoption to optimally deploy stations and sites to maximize ROI and service accessibility. Charge point operators gain access to accurate measurements of EV charging demand and precise mapping of low-battery zones across primary EV corridors.

Interested in finding out more about how EV intelligence can reshape your operations ?

  • Site Location Optimization

    Gain visibility into key corridor locations by distance

  • EV Drivers Insights

    Reduce battery anxiety levels by understanding area demographics and exploring customer personas.

  • EVCS (EV Charging Station) ROI Maximizer

    Determine station type for maximum revenue with point of charging insights.


Optimize EV Charging Station placement using

  • Visibility into site location demand

    Pinpoint ideal locations to optimize EV charging stations ROI with trip distance, duration, origin and destination. Identify station/location trade-area and population density. Detect demand for slow, fast and ultrafast chargers.

  • Area Demographics and Customer Personas

    Gain unprecedented visibility into visitation patterns for prospective station locations, including duration of stay in an area, recommended charger type, daily visits, POIs and  socio demographic characteristics. 

  • Point of charge insights

    Gain insight into demand map, EV station demand ranking, clusters demand ranking and EV Charging saturation, leverage a machine learning model which ranks each cluster to predict power consumption demand.

Explore EV intelligence and use cases for your organization

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