The European EV market is booming. Last year almost 2 million new electric cars were registered [European Environment Agency] and with more affordable EVs on the horizon it is expected that the market will continue to grow. For a long time the fuel retail industry has played a chicken and egg game with car manufacturers, trying to strike the perfect balance between serving the emerging electric vehicle market and offering services that remain profitable. Now, with an increase in demand for EV charging, it is not just traditional fuel retailers entering the charging game, but new competitors from outside the mobility industry.
The EV charging market still has room for growth, but with increased competition and a number of other factors that effect the price of charging we are starting to see a market primed for predictive pricing. So what effects EV pricing?
Unsurprisingly, the cost of electricity is a key determinant of charging cost however the type of charging station, location, network memberships, time-based vs energy-based charging, fluctuations in demand, season, time of day, additional onsite services and government incentives can all impact pricing.
Whilst some of these factors differ from those that impact traditional fuels, the principle is still the same. By considering all available data, artificial intelligence is able to price proactively. In fact, one key advantage to pricing electricity over traditional fuels is the availability of data. At any given site you can see not only the cost of electricity but the availability of chargers through a number of readily available apps.
Those accustomed to charging, whether at home or on the road, will know that dynamic pricing is already in place for the majority of charging providers. As the price of electricity fluctuates throughout the day, the prices adjust accordingly. This is why many people will choose to charge their car overnight when electricity is cheaper. Whilst dynamic pricing has obvious benefits for the retailer, it does not consider all the factors that can influence pricing. Predictive pricing using artificial intelligence takes pricing to the next level. By focusing on customer behaviours as well as the factors outlined above, artificial intelligence can spot trends and adjust the prices accordingly. For 16 years A2i has been pricing traditional fuels in this way, helping retailers to achieve their goals in volatile markets.
Convenience trumps price
One key difference between pricing electric charging and traditional fuels is the time it takes to recharge. If a fuel station is full the queues are likely to move quickly, however this isn’t the case with EV and customers will often settle for paying more if the charging experience is more timely and convenient. If, for example, you operate a site that is currently empty and your competitor across the street is 95% full, reducing your price may not be the right thing to do. This example perfectly illustrates the potential margin EV operators can gain by having the right price for their EV charging at the right time.
The additional wait time can also influence where and when customers choose to charge. A strong convenience offering where a customer can pick up groceries for dinner or a cafe with good coffee and reliable wi-fi where they can work can also factor into the decision making process. Customers may also choose to build their charging time around other tasks such as food shopping, or during their working hours. Only with customer-centric pricing can retailers spot behavioural trends and use this to inform their pricing strategy.
Charging doesn’t need to be complicated
One key advantage to owning an electric vehicle is the ability to charge at home. However this isn’t always an option and, particularly for longer trips, the fast charging network is essential. Some homes are unable to install chargers due to the location or because of increased pressure on the electricity grid. Even if a customer is charging at home, this electricity will still be provided by someone and they too could benefit from predictive pricing. We are seeing more and more energy providers entering the charging arena providing both at home charging and access to certain networks on the go often through subscription type models.
Subscription models have been a popular method of packaging charging services, however critics have stated that often these methods lack transparency and customers are not always aware of the true cost of charging their vehicle. Complex pricing structures, hidden fees, inconsistent pricing and limited access to real time pricing information all hinder the experience of customers. By harnessing the power of artificial intelligence, retailers can better understand their customer needs and provide them with transparent pricing information wherever they choose to charge their vehicle.
Charging plus…
As electric vehicles continue to take off and the market becomes more competitive, we recognise not only the importance of predictive pricing for EV chargers but how PriceCast technology could also be used for convenience and additional services. Our roadmap is focused on providing artificial intelligent technology to support retailer’s goals whichever direction the industry might take.
