We understand the issue of positioning charging stations

In Europe, the market share of electric cars is growing rapidly. More and more drivers are investing in these cars and the battle for electric charge points is fierce.

Car manufacturers, energy suppliers, petrol stations, car dealers, large companies and retailers are all installing charging stations at a high speed. Moreover, governments are endeavouring to match local supply to demand.

But what are the best locations for these charging stations, taking into account expected demand, available supply and environmental characteristics?

There is an abundance of data available to help answer this. But where do you start? Thanks to its extensive data expertise and the power of predictive models, RetailSonar knows where.


Find the most promising locations for your charge points

  • Investigate the potential of new locations by mapping the demand and supply sides.
  • Demand side: To what extent do urbanisation, prosperity, tourism and employment opportunities determine the potential?
  • Supply side: Which locations already exist? And which locations will have charge points soon?
  • Use mobile data to measure the success of existing locations and apply the lessons learned to create your optimal location strategy.
  • What are customers’ expectations? What is the impact of good neighbours such as supermarkets, leisure facilities or employers?
  • Determine the impact of visibility. To what extent does the success of a location depend on passing traffic?
  • What is the impact of accessibility and sufficient parking?
  • Identify hotspots: places where the demand for charge points is great but the supply is still limited. These have the greatest potential.
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“Through a data-driven testing framework, we wanted to find out what the optimal locations were for our network of fast chargers.”

Maximise the use of your charge points

  • Clearly map the consumption per charge point, based on mobile data.
  • Ensure optimal use of all charge points and adjust customer behaviour if necessary.
  • Optimise the ROI of your marketing campaigns by targeting your audience.
  • Experiment with new marketing channels in a structured way.

Smart & data-driven determination of the optimal network

  • Map the locations and spread of all existing charge points.
  • In the current network, where does supply lag behind demand (residential or non-residential areas)?
  • Calculate the optimal coverage ratio for a location, region, province or country. How do you ensure that each resident has a charging point X minutes’ drive away?
  • Also analyse the use of existing charge points: which charge points are used to the maximum extent? This provides an additional picture of the demand.
  • And which charge points are not used very much? Can you increase the use of these with targeted marketing?
  • Work towards a future-proof charge point network, delivering maximum returns using a (semi) greenfield analysis.
  • Keep a close eye on changes in customer behaviour and respond intelligently to future location decisions.
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