Analyzing the potential for expanding (public) charging infrastructure

Challenge: Attractiveness and acceptance of electric vehicles crucially depends on a public, accessible and exhaustive charging infrastructure.
However, the implementation and maintenance of such infrastructure is characterized by high cost and low efficiency. With an average utilization
rate of only around 4%, the performance depends on finding the optimal location. A lack of previous experience often complicates the identification
of these ideal locations.

Solution: The Geo Prediction Engine of Geospin reliably predicts the expected utilizations of charging stations – across all of Germany.
Choosing the optimal location is thus straight-forward, for instance by maximizing the utilization rates of your charging infrastructure.
The model was trained on several hundred-thousands of charging processes across 6.000 charging points, exploiting over 800 additional
geo-data sources.

Download our free product sheet here!

The basis for our analysis is a geographic area of interest. You do not need to provide any data.


Our Geo Prediction Engine calculates the expected utilization rate of charging infrastructure using 800 features reflecting the spatial environment.


Our software identifies the optimal locations for a demand-driven charging infrastructure.

What customers say:

„Currently, charging infrastructure is barely utilized, so every additional percentage point of usage is crucial!“

Sergej Stimeier, Referent Unternehmensstrategie, ESWE Versorgungs AG


Philipp Behrends
0761 59514 615
Geospin GmbH

Freiburg office (company seat):
Kartäuserstraße 39a
D – 79102 Freiburg i. Br.

Phone: +49 (0) 40 3092 2303