Harnessing AI and GenAI to Transform Mobility, Fuel and Convenience Retail

Our Perspective

The fuel retail industry, traditionally centered on hydrocarbon-based products, is rapidly evolving into a dynamic and innovative sector, diversifying into energy/ fuel options like gas (CNG/RNG), EV charging, hydrogen fuel, and mobility services. This expansion necessitates integrating new services through mobile apps for seamless fuel payments, personalized loyalty rewards, and targeted promotions based on customer purchase history. Historically, the oil and gas retail sector has been low on the customer-centric dimension, caring less about cross-selling opportunities and primarily concentrating on fuel sales. However, with the advent of AI, the industry is poised for significant growth and innovation.

As the industry evolves, many fuel retailers still rely on basic loyalty programs and broad segmentation without the data infrastructure needed for true personalization. Without robust artificial intelligence (AI) and data systems, tracking cross-channel behavior and maximizing cross-selling opportunities remains challenging. Fuel retailers must adopt AI-driven strategies for a unified customer view across fuel and convenience services, boosting revenue and targeting. According to Skyquest, the AI market in the fuel industry, valued at $2.32 billion in 2022, is projected to grow to $5.32 billion by 2031, at a CAGR of 8.76%. 

AI and generative AI (GenAI) are core platform technologies that enable personalized and seamless customer engagement and make every interaction intelligent. These technologies are instrumental in overcoming several challenges that exist in the journey of customer-centric transformation:

1. Integration of New Energy Fuels: Fuel retailers face logistical and technical challenges as they add new energy options like EV charging, biofuels, and hydrogen fuels. These new services must blend well with traditional fuel options for a smooth customer experience.

2. Data Silos: Many retailers struggle with fragmented applications and siloed data systems, hindering a unified view of customers across services. For example, disconnected loyalty and marketing systems can result in missed opportunities for personalized promotions. Marketing campaigns without personalization have low uptake and can adversely affect brand perception and long-term loyalty. 

3. Legacy Systems: Retailers often use outdated point-of-sale and transaction systems that lack integration with mobile payments, loyalty, modern checkout options, and real-time inventory updates, making omnichannel commerce challenging.

4. Regulatory and Infrastructure Barriers: Offering new energy services like bio/renewable fuels (CBG, RNG), hydrogen, and EV charging requires adhering to stringent regulations and potentially redesigning physical infrastructure, which adds complexity to integration.

Optimizing Customer Lifecycle Management with AI

Fuel retailers face increasing pressure to build long-term customer relationships as the industry diversifies beyond traditional fuel services to become mobility and convenience providers. By leveraging AI for customer lifecycle management (CLM), retailers can better understand customer needs, tailor interactions, and drive loyalty.

• Personalized Customer Journeys and Retention: AI maps customer journeys by analyzing purchase history, preferences, and behavior, creating targeted offers that encourage repeat visits. For instance, AI can identify a customer who regularly buys coffee during fuel stops and offer a discounted breakfast combo. AI-driven predictive analytics also identify churn risks, allowing retailers to proactively offer fuel/ charging discounts, loyalty rewards, or personalized incentives to retain high-value customers.
• Optimizing Engagement Across Channels: Integrating AI into CLM allows fuel retailers and mobility providers to deliver consistent customer experiences across physical and digital touchpoints. This might include using mobile apps for personalized promotions, in-store digital displays for targeted ads, and real-time SMS offers based on location. 
• Driving Profitability Through Customer Insights: AI-driven CLM can increase customer lifetime value (CLV) and basket size by recommending relevant add-ons at fuel stops, turning single transactions into higher-value purchases.

AI and GenAI in Fuel Retail, Mobility and Convenience: Driving Personalization and Automation

AI transforms customer engagement in fuel retail, mobility, and convenience services by delivering hyper-personalized experiences and streamlining operations. By integrating AI and GenAI, fuel retailers, mobility, and convenience providers can create innovative customer engagement strategies, reducing manual effort while delivering highly relevant, data-driven experiences.

• Traditional AI for Customer Engagement: AI-powered micro-segmentation enables retailers to move beyond broad customer groups, allowing for precise targeting based on purchase behavior. Additionally, next-best-action recommendations analyze real-time data to suggest tailored promotions — such as offering a discounted breakfast combo to a customer who regularly buys coffee during fuel stops.
• GenAI for Communication and Automation: GenAI enhances customer interactions by creating personalized emails, SMS promotions, and digital ads at scale. It also improves customer service automation, handling loyalty point inquiries, click-and-collect status updates, and order tracking. Retailers can even use GenAI to summarize customer reviews and automate responses to common inquiries.

Businesses Need a Holistic Data Transformation

Organizations need to be aware of and prepared for a holistic approach to building data and AI platforms that unify information from disparate systems, making it accessible for advanced analytics and AI-driven insights. These insights support precision targeting, customer service, planning, and forecasting. A 360-degree customer view, combining historical transactions with real-time data, drives hyper-personalization and improved customer convenience. To achieve this, businesses should focus on:

• Unified Data Platforms: Businesses must develop data platforms that combine master and transactional data to achieve a unified customer view for analysis and insights. To complement this, AI-driven systems are required to process this data and uncover actionable insights, allowing retailers to create more targeted engagement strategies. 
• Personalized Customer Experiences: Leveraging customer data like purchase history, preferences, and location allows retailers to create tailored interactions that improve loyalty and satisfaction. Focusing on these details can drive higher non-fuel revenue, site profitability, and footfalls. 
• Business Value-Driven Solutions: Retailers should prioritize solutions that deliver measurable business outcomes. By optimizing key performance indicators (KPIs) such as customer lifetime value (CLV), non-fuel revenue mix, average basket size, and visit frequency, businesses can refine their strategies based on customer segmentation and behavior. 

Wipro’s Proven Success in Driving Retail Transformation

Fuel retailers face various challenges, including modernizing operations and improving customer experiences. The following Wipro case studies provide strategic insights into effectively addressing these issues, helping businesses adapt and thrive in a changing market landscape.

1. Digital Strategy and Architecture Development for a Major Oil and Gas Player

A significant oil and gas player sought to modernize its retail business by integrating unified digital platforms to expand market channels and enhance customer loyalty. Wipro developed a customer engagement and marketing strategy that resulted in over 100,000 new loyalty sign-ups in six months. The initiative also increased basket size, improved RFM scores, and boosted revenue and customer retention.

2. Retail Business Transformation for a Major US Oil and Gas Player

A leading US oil and gas retailer sought to elevate customer experience by offering pay-at-pump functionality while integrating loyalty offers. To address this, Wipro extended the retailer’s mobile app by incorporating pay-at-pump capabilities and re-architecting it to integrate loyalty with payment solutions seamlessly—the redesigned app, built using UX principles, enhanced customer engagement and experience. As a result, the mobile app achieved 5.4 million installs and contributed to $0.5 billion in total sales in 2023.

3. Transformation of Retail Fuel Pricing for a European Oil and Gas Player

A European oil and gas player needed to standardize pricing across all fuel grades, EV charging at its retail outlets and charging stations while introducing dynamic pricing capabilities. Wipro developed a cloud-native pricing system to modernize existing applications and extend them with real-time, industry-aligned dynamic pricing features. The new system is being rolled out globally in phases and is expected to directly improve margins and revenue by enabling more agile and responsive pricing strategies.

Businesses must deliver more tailored, convenient, and seamless experiences to meet evolving customer expectations. A comprehensive approach to data integration ensures that retailers adopt the right technologies and derive real value from them. Fuel retailers, mobility providers, and convenience providers can maintain a competitive edge in an increasingly competitive market by optimizing customer lifecycle management through AI. 

About the Authors

Manu Sharma
Consulting Partner, Energy Consulting

With more than 25 years of experience, Manu consults with clients on the energy transition, new product introduction, and customer-centric transformation initiatives. His special interests are energy transition pathways, sustainable fuels, industry diversification, and the development of AI-centric technology platforms to enable the energy transition.

Sudhansu Sekhar Choudhury
Senior Partner, Energy Consulting

Sudhansu is a senior consulting partner in the energy domain with more than 24 years of experience in core energy industry and IT domain consulting. He drives solutions and services for global energy clients and focuses on building capability at scale, orchestrating new age solutions, developing thought leadership, and driving customer-centric transformation across hydrocarbon product supply chain, customer and mobility, and new energy. He has helped energy enterprises advance new business capabilities and deliver business solutions and transformation initiatives within their downstream and new energy businesses.

Michael Yaacoub
Principal Full Stack Software Engineer, Energy Consulting

Michael is a Principal Full Stack Software Engineer and Solutions Architect with over 21 years of experience in cloud computing, AI/ML, full-stack development, enterprise architecture, and DevOps. He has led cross-functional teams and driven digital transformation initiatives across various industries. Michael holds a Master’s degree in Computer Science and multiple certifications in cloud computing, software development, and project management.