In 2021, the global aviation analytics market was valued at USD 2.5 billion and is expected to grow at a compound annual growth rate (CAGR) of USD 12.3 billion over the next 5 years. The increasing demand for analytical solutions to modernise aircraft fleets and operational processes to ensure flight safety is driving the growth of the aviation analytics market.
In today’s digital and competitive environment, every airline is looking for ways to maximize its assets and offer the best service to its customers. The airline industry is turning to data analytics to improve operations, enhance customer experience and ensure safety. This is causing a lot of interest among airline industry professionals who want to understand how airlines are utilizing data analytics to achieve success.
Since the airline industry collects and analyzes huge amounts of data from a variety of sources and activities, such as reservations and departure systems, as well as revenue handling and flight management, CRM, website, etc., it is essential to collect and analyse all this data efficiently in order to enable airlines to move from operating to business excellence. In this post, we will be looking at how data analytics in aviation industry is being used.
How Do Airlines Use Data Analytics in Their Marketing?
Data analytics is changing the airline industry. Marketing is no different. Data analytics provides an integrated and holistic view of the target customer’s needs by concentrating on what’s best for them. It provides actionable campaign suggestions based on customer groupings and segmentations. Airlines are using data analytics to better understand their customers, customize their products and services, and ultimately increase sales.
How Airlines Use Data Analytics? – Data Analytics in Aviation Industry
The global aviation market for Big Data Analytics is expected to reach USD 7178 million till 2023, with a compound annual growth rate (CAGR) of 17.5%. Many airlines have successfully implemented Big Data Analytics to increase their market share and reduce costs. The aviation industry leverages technological innovations to reduce operating costs while enhancing the customer experience. These are the ways data analytics in aviation industry is being used in efficient way for various reasons.
Revenue Management
Airlines rely on business analytics to gain insight into traveler demand and to optimize pricing for optimal profitability. Thanks to the power of data science, airlines are now able to leverage advanced methods to conduct demand analysis. For instance, airlines rely on behavioral data from travelers to determine leisure demand, while information from professional networking sites, recruitment and procurement activities, can indicate new business travel destinations. With competitive flight pricing data, revenue teams can adjust fares at the optimal rate based on demand and competition to generate more bookings.
Nearly 24% of airline expenditure is related to fuel, and airlines worry about the impact of fuel prices on their profits each year. With the increasing throughput of the Satcom systems and 5G mobile communications, airlines are able to control their fuel expenses. Flight search APIs have become an essential tool for airlines to monitor flight prices across various booking applications, websites and OTAs.
Predictive Maintenance
Data analytics enables aviation industries to save costs and generate revenue streams by leveraging Big Data, IoT and predictive analytics. For example, airlines analyze data to predict aircraft part refurbishment needs or repair needs prior to breakdowns, thus reducing unplanned maintenance expenses and delays. Aviation industries can reduce expenses while generating new revenue streams. Some aircraft manufacturers use the data to carry out predictive maintenance or repair before the aircraft breaks down. Approximately 10% of airline operating costs go to maintenance, resulting in a lot of delays. The manufacturer and the carrier would benefit financially if they knew when a part needs refurbishing.
Predictive data analytics in aviation industry tracks engine temperature and fuel consumption, as well as flight patterns, to identify trends and gain insight into maintenance needs. This allows aviation companies to streamline maintenance schedules and increase aircraft uptime, resulting in improved safety, efficiency and profitability, higher customer satisfaction scores, and more revenue streams.
Data Analytics Boost Trip Revenue
Nearly 24% of all airline costs are fuel costs, and airlines are concerned about the impact of fuel prices on their profits each year. With the increasing throughput of Satcom systems and the advancement of 5G cellular communications, airlines can better manage their fuel expenses. The aircraft sends all data to the ground-based flight operations. An analytics engine uses its algorithms to process the data and send back a recalculated optimum route to the aircraft. By utilizing data analytics in the airline business, airlines can plan their flight routes more effectively. This helps ensure timely arrival of passengers and reduces fuel consumption, as well as overall costs. In order to do this, airlines must have access to accurate and up-to-date flight data as well as route information. By using a dependable Flight Tracking API, airlines can make better decisions when planning their airline route.
Using AR for Indoor Airport Navigation
Navigating an airport’s labyrinthine layout can be one of the worst experiences for travelers. Because GPS is so inaccurate for indoor navigation, airports are turning to other technologies, such as Bluetooth-enabled data beacons scattered throughout the facility or AR (augmented reality).
Reduces Risk Management
The need for flight data analytics is growing rapidly in the aviation industry as industry professionals recognize the value of risk management and accident prevention. In aircraft maintenance and crew management programs, airlines use data analytics to anticipate and manage pilot fatigue. This helps to reduce risks and ensure safe operations. By examining factors such as pilot schedule and flight time, airlines can detect potential risks and take action to prevent accidents, enhance safety, and save money.
Conclusion
The global aviation industry is no stranger to innovation, constantly evolving to meet the demands of a dynamic and competitive market. In recent years, a powerful driver of this change has been data analytics. By harnessing the vast amounts of data generated by every aspect of operations, airlines are taking flight towards new heights of efficiency, profitability, and customer satisfaction.
From personalized marketing campaigns that resonate with individual travelers to predictive maintenance that prevents costly breakdowns and delays, data analytics is transforming the way airlines do business. Route optimization algorithms minimize fuel consumption and ensure on-time arrivals, while risk management models based on crew fatigue analysis enhance safety and reduce accidents.
As data science in aviation continues to evolve, we can expect even more groundbreaking applications. Imagine intelligent cockpits that anticipate and react to weather disruptions, or onboard AI assistants that personalize your travel experience based on your preferences. The possibilities are endless, and the sky is no longer the limit for this data-driven revolution.
So, the next time you board a plane, remember the invisible but powerful forces of data analytics working behind the scenes, ensuring a smooth and enjoyable journey. The future of aviation is fueled by data, and the destination is clear: a smarter, safer, and more customer-centric industry that takes flight on the wings of innovation.
