In today's world, vehicles are more than just a means of transportation—they're moving data sensors. Respecting the privacy of individuals, while retaining valuable informational content,
anonymized vehicle data has been the offspring of this data-capturing activity. This data fuels actionable insights and applications in various use cases including most notably Traffic Management, Transportation Analytics, Smart City operations and various industry-specific cases.
TOFAŞ is a prominent automotive company based in Turkey that produces passenger cars and light commercial vehicles including the FIAT brand locally. The company's commitment to innovation and quality has helped it maintain a strong presence in the automotive industry. In reflection of this spirit, TOFAS has also been carefully exploring the productization and commercialisation of anonymised vehicle data. As part of this activity, TOFAS has become a data supplier partner in the MOBITO Data Marketplace. Currently, they offer Anonymised Vehicle Probe data, Diagnostics Data and Vehicle Fueling Behaviour Data.
This case study explores how Vehicle Fueling Behaviour data obtained from connected vehicles, provide a comprehensive understanding for gas stations, of their customer's behaviour, preferences, and market trends.
The sample report shown below provides a comprehensive comparative analysis of vehicle fueling behaviour from vehicles data signals and their overlay with gas station information.
Whether you are a fuel station owner seeking to enhance customer experience, understanding customer preferences or trying to understand the fuel market to install new fuel stations or preparing a competitive analysis, this case study explains some of the specific applications and insights that this data lends itself to and how this can lead to invaluable commercial insights.
Firstly, this type data is representative of the market activity of the fuel market. This includes vehicle traffic at gas stations, information on vehicle fueling events, total litres of fuel consumed, fuel type distribution of vehicles, and the vehicle type distribution in the market. By analysing these trends organisations can gain a deeper understanding of the dynamics shaping the Fuel Market for multiple purposes:
Total Vehicle Traffic at Gas Stations:
Utilisation: Recognizing regions with higher volumes of vehicle traffic at gas stations can provide valuable insights for fuel providers to refine their expansion strategies. This data is crucial for assessing the accessibility and convenience for consumers, influencing their decisions on fueling locations based on the flow of traffic.
Supply Insights: When utilisation is combined with density of gas stations it can radically de-risk investment decisions by placing stations to cater to unfulfilled demand.
Total Filling Events and Total Litres of Fuel Consumed:
Consumer Behavior Analysis: By analysing patterns in filling events and total fuel consumption, fuel providers can gain insights into peak demand periods, helping optimise staffing and resource allocation.
Demand Forecasting: Understanding fluctuations in fuel consumption allows for better forecasting, enabling stakeholders to anticipate market trends, plan inventory levels, and adapt marketing strategies accordingly.
Fuel Type Distribution of Vehicles:
Environmental Impact: Knowledge of fuel type preferences informs policymakers and industry stakeholders about the environmental impact of vehicle fleets, facilitating initiatives to promote cleaner fuels and sustainable practices.
Market Adaptation: Fuel providers can adjust their offerings based on the prevalent fuel types, whether gasoline, diesel, or alternative fuels, to meet consumer demands and stay competitive in the market.
In essence, fueling behavior data from connected vehicles serves as a powerful tool for informed decision-making, enabling gas station operators and other organisations enhance operational efficiency, plan infrastructure development, and stay responsive to evolving market trends in the fuel industry.
Another prominent application of Vehicle Fueling Behavior data from connected vehicles lies in competitive analysis, as shown in the sample comparing a particular gas station to the broader Turkish fuel market. This involves region or province-wise comparisons of fuel station distribution, chronological ranking comparisons based on filling events, and assessing the comparative filling events of a fuel station over a specified time period in relation to the rest of the market.
Region/Province-wise Comparison on Fuel Station Distribution:
Market Presence: Analysing the geographical distribution of fuel stations based on the filling events from vehicles helps a gas station provider to understand its market penetration in different regions or provinces. This information is crucial for refining marketing strategies and identifying potential areas for expansion or optimization.
Competitive Positioning: Comparing the station distribution in different regions allows for a comprehensive evaluation of how a particular gas station provider stacks up against competitors in specific geographic areas, enabling targeted improvements where necessary. This knowledge is essential for refining business objectives, setting realistic targets, and developing strategies to gain a larger share of the market.
Efficiency Ranking of Fuel Stations based on Vehicle Fuel Filling Events:
Temporal Trends: Examining the ranking based on vehicle fuel filling events provides insights into the station's performance over time. It helps identify growth patterns, assess the impact of marketing initiatives, and pinpoint potential areas for improvement.
In essence, leveraging Vehicle Fueling Behavior data for competitive analysis empowers stakeholders to make informed decisions based on a nuanced understanding of their position in the market. It enables them to identify strengths, capitalize on opportunities, address weaknesses, and stay agile in a dynamic and competitive fuel market landscape.
In summary, this TOFAS case study details how information about how people fuel up their cars can be utilised towards operational and strategic gains. By analysing trends like where people fill up, what types of fuel they use, and when they do it, businesses and experts can make smart decisions. For gas station providers, it means they can improve how they serve customers and figure out where to open new stations. For organisations studying the fuel market, it helps them understand the current market status and plan for the future.
The case study further proves that accessing and analysing the right data is not just good for businesses; it also helps cities plan better and can inform important policy discussions like the environmental standing of the automotive/ transportation sector.
If you are interested in learning more on how you can utilise anonymised vehicle data in your own business don’t hesitate to Get in touch