5 ways predictive analytics can help airlines analyze, anticipate, and adapt

By Hélène Dubos | Technology

Jul 16
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How can the industry recover in a new normal that practically discourages flying? Let’s see how technology—more specifically, predictive analytics—can help airlines take to the skies again.

Recent years have seen more and more passengers being flown across the globe by the airline industry. In fact, this number reached 4.54 billion in 2019, according to Statista. Then of course, the COVID-19 pandemic happened.

Nations instituted lockdowns and cancelled visas to reduce the transmission of the virus. The airline industry was naturally one of the worst-hit—flights were cancelled, fleets were grounded, and operations had to be halted or scaled back.

A seemingly increasing trend turned to a sudden decline. Post-pandemic, Statista predicts the number of passengers to take flight in 2020 is only 2.2 billion. In 2021, the forecast is 3.4 billion, a slight uptick but still low compared to previous years.

The industry has a lot of catching up to do, but where do you start? There is no complete or correct answer, but one thing’s for sure: as we enter a new normal, airlines everywhere need as much information and insights as they can get on how to recover, realign, and move forward.

Where Predictive Analytics comes in

Even before COVID-19, advanced analytics has always played a significant role in transforming airline operations and improving the passenger experience.

The industry faces unexpected events everyday—from aircraft delays to seasonal fluctuations. Predictive analytics can provide the foresight needed to help you proactively make optimal decisions and stay on top of potential issues.

Below are 5 areas where predictive analytics can make an impact, post-pandemic.

1. Efficient resource allocation

With stocks plummeting and cash reserves dwindling, airlines need to make the most out of resources and infrastructure available when operations continue. One way to go about this is by reducing inefficiencies.

For example, by looking at historical data (e.g. number of flights, taxi times, airport capacity, and operational behavior), you can leverage forecasting algorithms to predict flight demand and passenger flow in order to implement effective capacity planning.

Anticipate passenger traffic in airports to decide whether a skeletal workforce is sufficient, plus address potential bottlenecks to minimize long queues. Reduce taxi time and fuel waste by getting foresight into possible weather and congestion issues.

With insight into demand, the aviation industry can effectively allocate resources and cut costs.

2. Improved passenger satisfaction

The pandemic brought a lot of unprecedented change, and that might have caused a lot of frustration for both the industry and the passengers. Part of airlines’ recovery plan should include measures on how to win customers and improve satisfaction.

Use predictive analytics for more aggressive passenger engagement. Conduct a text clustering analysis on passenger reviews, social media updates, and other communication touchpoints to identify patterns in customer feedback. Use the insight gained to address unresolved needs and meet expectations.

Another way to engage and retain passengers is to predict churn. Determine factors that significantly affect abandonment risk through machine learning. These insights can help you identify which passengers are likely to leave the website or cancel their booking, and you can target them with compelling offers and messages to get them back on board.

3. Optimal service offerings

To improve passenger engagement even further, consider injecting personalization into the mix. After all, 91% of consumers prefer brands who recognize, remember, and provide relevant offers and recommendations. Personalization can go a long way, especially with shopping habits changing during and after the pandemic.

Using clustering models, create customer segments to capture interest and provide a targeted passenger experience. This way, you can design experiences and offer products and services based on the segments’ predicted customer lifetime value, likelihood of engagement, or even propensity to purchase.

For example, customers who booked a holiday in March last year can be sent personalized deals on relevant vacation sports and tours. Or if customers are likely to purchase more luggage, you can send them personalized messages promoting the add-on.

In short, predictive insights will enable you to provide the right products, services, and price at the right time.

4. Effective call center management

The pandemic saw flights cancelled and rebooked left and right, and this has put the industry’s customer service representatives on the frontlines. Teams are getting bombarded with requests and questions. To illustrate: there was an uptick in flight-related Google queries (how to rebook ticket, cancel fight) during March 8—14 this year.

Start by making sure that there are enough representatives to handle queries at a given time. Predict demand for customer service and use the insights to manage start times, end times, and break times. To take this a step further, ensure that the right agents are available.

For example, if a surge of refund, cancellation, and booking modifications are expected at a certain time, you can make sure that skilled agents are there to provide the required resolution.

By streamlining operations in the call center, you can provide a smoother customer experience plus boost employee satisfaction.

5. Foresight into potential roadblocks

While no one could have prepared for the impact the pandemic had on the airline industry, strategic planning can help curb losses and manage uncertainty. And in an industry like aviation where the unexpected is expected, foresight can help organizations act more efficiently and effectively.

Leverage machine learning and predictive simulation to analyze unstructured and structured data—industry news, regulatory trends, domain knowledge—to forecast outcomes and potential failure events. While this doesn’t mean you can predict another pandemic per se, you’ll have enough foresight into potential time-based events. This way, you can manage risks, remain competitive, and engage in strategic decision making.

Ready to fly?

These are just some of the ways predictive analytics can help the aviation industry plot a steady course to recovery. By transforming operations, retaining and delighting customers, and staying on top of potential issues, airlines can slowly move forward and win back business. It’s worth noting though that achieving the full potential of advanced analytics requires a tight integration of systems. Talk to Conztanz today to learn more about data integration and reducing data silos.