Sky is the limit for Big Data Analytics in the Aviation Industry
By implementing Big Data Analytics EasyJet saw an increase in profits per seat by almost 20%
While enjoying Sunday with your family, your mobile beeps with a notification. The notification shows ”Book your flight tickets for just Rs 1200/-“. Here comes another notification “Flat 50% discount on the flight ticket. Hurry up….!!! (offer valid till 31st March)”.
Do these kinds of offers and discounts fascinate you so much? How these airlines target you with such amazing offers.
Today’s Aviation Industry is highly competitive, airlines generate billions of dollars every year but their profit margin is less than 1%.
With most of the airlines in the world operating on wafer-thin profit margins, they need to cut costs. Let’s explore the power of Big Data Analytics that has completely transformed your air travel experience.
Big Data in Aviation Industry
Right from targeting you with these interesting offers to your in-flight experience, Big Data Analytics has transformed the aviation industry to a great extent.
The market size of Big Data Analytics in the global aviation industry was valued at $2,52 million in 2016. By 2023, it is expected to reach $7178 million with a CAGR of 17.5%.
Many airlines have performed very well in terms of market share and cost reduction by implementing Big Data Analytics. Technological Advancements are reducing the operational cost of the Aviation Industry moreover helping them enhance the customer experience.
Customer Segmentation and Differential Pricing Strategy can be easily achieved through Big Data Analytics. These concepts help airlines with customized targeting and also generate maximum revenue from the available capacity.
Information is the oil of the 21st century, and analytics is the combustion engine. – By Peter Sondergaard
Role of Big Data Analytics in Aviation Industry
1. Centralized view of the customer
The aviation industry generates a huge amount of data daily but most of the data is not in an organized manner. A major challenge faced by various airlines is the integration of the customer information lying in silos. For example, airlines can capture the data from:
- Online Transactions while booking tickets
- Search Data from Websites and Apps
- Data from customer service
- Response to Offers/Discounts
- Past Travel History
Combining all these data points can help create a centralized view of every customer. Big Data Analytics can generate useful insights from this data, which are mentioned below in the article.
2. Real-time Analytics to Optimize Flight Route
With each unsold seat of the aircraft, there is a loss of revenue. Route analysis is done to determine aircraft occupancy and route profitability. By analyzing customers’ travel behavior, airlines can optimize flight routes to provide services to maximum customers.
Increasing the customer base is most important for maximizing capacity utilization. Through big data analytics, we can do route optimization very easily. We can increase the number of aircraft on the most profitable routes.
3. Demand Forecasting and Fleet Optimization
By analyzing the past travel history of the customers, airlines can predict future demand. Predictive analytics plays a great role in forecasting future demand. Airlines can increase/decrease the number of aircraft if they know the upcoming demand.
This, in turn, increases fleet optimization and enhances capacity utilization. The crew can be allocated accordingly for effectively managing the customers. This will enhance time punctuality in flight operations and increase customer satisfaction.
Consumer data will be the biggest differentiator in the next two to three years. Whoever unlocks the reams of data and uses it strategically will win. – By Angela Ahrendts
4. Customer Segmentation and Differential Pricing Strategy
It is important to know each customer has his/her own needs. Some customers can be time-sensitive and some can be price-sensitive. Some customers give more importance to amenities and luxury, and for some, it does not matter.
Therefore airlines can generate various offers to cater to different segments. Depending on the offer airlines can price their tickets. This differential pricing strategy helps generate maximum revenue from each customer.
5. Fuel Efficiency
According to the General Electric Report, a 1% reduction in jet fuel can save up to $30 billion in the aviation industry.
Only 2% of operational expenses are recognized as profit by most of the airlines. According to Statista, in 2019 airlines’ average fuel expenditure was 23.07% of their operational costs.
Therefore it is extremely critical for the air carriers to cut fuel costs. Various external factors like wind speed, humidity, temperature, aircraft weight, altitude, air density determine the fuel efficiency of a particular flight.
All these data are collected on a real-time basis from the sensors. Data Analytics can analyze all these factors to determine the most cost-effective route for the aircraft.
6. Giving out personalized offers
Client received bookings of more than $1 million per week with the help of personalized marketing.
Big Data Analytics helps in understanding the customer’s travel behavior, willingness to pay, etc. Analyzing the customer’s preferred location, search history, etc. we can target them with customized offers.
Customized offers always attract customers, and helps in improving customer satisfaction and loyalty.
Let’s understand with an example, how personalized offers/communication impacts sales.
Boxever is a customer intelligence and personalized marketing platform in the travel industry. This company serves various clients, helping them chalk out personalized offers for their customers.
Boxever’s client made a marketing plan around abandoned carts and sent personalized emails to its customers. As a result, they received bookings of more than $1 million per week with the help of these email communications.
7. Smart Maintenance
Big Data Analytics helps Boeing save $300,00 annually in terms of service delay and repair costs.
Many times we see delays and cancellations of flights. The major reason behind this is unplanned aircraft maintenance due to technical glitches. This results in customer dissatisfaction and also the loss of revenue due to downtime of the aircraft.
Surprisingly, 30% of the delay is due to unplanned maintenance.
Big Data Analytics can come to the rescue to tackle this situation effectively. Critical sensors can be attached to monitor the aircraft’s health. Predictive analytics can help identify the part which will require immediate maintenance and when to replace it.
Big Data Analytics can help in asset utilization and thereby improve the airline’s profitability.
Example:
Boeing has an Airplane Health Management System through which it analyzes around 2 million conditions daily across 4000 aircraft.
With the help of Big Data Analytics, Airplane Health Management System:
- Perform mechanical analysis, in-flight metrics and shop findings
- Effectively plan maintenance and distribution
- Predict unplanned failures and the required action to be taken
- Helps Boeing save $300,00 annually in terms of service delay and repair costs.
8. Performance Measurement
With the help of Big Data Analytics, airlines can effectively analyze various performance parameters like:
- Profit per passenger
- Average Revenue per Flight
- Number of passengers flown per flight/sector
- Average Flight Occupancy
- Overbooking
- Operating cost per Flight
Case Studies
1. United Airline Case: Enhancing customer satisfaction and loyalty
Using Big Data Analytics, United Airlines has increased 15 % year-on-year revenue
With each booking, the customer generates lots of data. Even a single booking can provide lots of information about the customers. Each customer profile consists of more than 100 variables related to past travel details, search history, response to discounts/offers, etc.
United Airlines analyzes these variables in just a few seconds and comes up with lots of fascinating offers.
Customer profiling helps in developing tailor-made offers according to the customer’s needs. This helped United Airlines increase the year on year revenue by 15%.
2. British Airways: Understanding the customer more precisely
With the help of the smart “Know me” feature, BA provides personalized search results to its customers. Big Data Analytics helped British Airways identify the characteristics of its customer base. What they find is that its customer base mainly consists of time-pressed and busy-professionals who require immediate service.
This insight again helped in offering customized services and thereby enhancing customer satisfaction. Due to this, BA received positive feedback from the customers for understanding them.
3. EasyJet
By implementing Big Data Analytics EasyJet saw an increase in profits per seat by almost 20%
EasyJet is the British Low-cost carrier that has implemented Data Analytics to improve its decision making. The Airline implemented a differential pricing strategy to generate maximum revenue from the available capacity.
Big Data analytics helped in customer segmentation which opened the path for differential pricing. As a result, between 2010-2014, the company overserved the increase in profit per seat by almost 20%.
Conclusion
Many companies have saved themselves from bankruptcy by implementing Big Data Analytics. Big Data Analytics will completely overhaul the travel experience in the upcoming years.
Big Data Analytics is effectively using concepts like Demand Forecasting, Differential Pricing Strategy to generate the maximum revenue. There will be a huge demand for analytics professionals in the upcoming years to cater to the needs of this industry.
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