The mobility retail market is in for a period of change and disruption as the world shifts away from traditional fuels. Oil demand growth shows signs of slowing and across multiple scenarios demand is expected to begin to decline by 2030.¹ This shift in fuel focus is presenting an opportunity for both established mobility retailers and market entrants to define new offerings using AI and advanced analytics (AA).

As electric vehicles (EVs) become more prominent, the customization of service stations may prove crucial to future success.² Intelligently harnessing AA or AI can help mobility retailers customize their value proposition for each station and unlock a wide variety of use cases that could help improve returns, achieve cost savings, and drive customer engagement.³ Some of these use cases include personalization in customer loyalty programs, fuel price optimization, labor activity improvements, station network optimization, and convenience retail optimization.⁴

This article dives into the latter two use cases—station network optimization and convenience retail optimization—exploring how mobility retailers can use AA and AI to tailor each service station to their customers’ preferences and seize opportunities in the changing landscape.