3 Key Ways Airline E-commerce can Fight the Airline Recession

Written by Natasha

The most important focus point for airlines during the post Coronavirus airline recession period is to re-motivate customers to fly with them. But some strategies used could lead to more harm than good. Here are the latest on the best Big Data Analytics ways to upgrade your airline e-commerce to reap the maximum benefits during and after the airline recession.

The COVID-19 Coronavirus pandemic continues to wreak havoc through the world. It has caused a devastating loss to human life and crumbled economies. We just might be on the worst economic trajectory in history.

As we’ve discussed previously and as many others have, the airline industry continues to be one of the industries most severely impacted by this outbreak. It is clear that an airline recession is now the reality. All airlines will suffer tremendously, and some may even be forced to cease operations.

This is not the first nor the last pandemic the world will face. Other pandemics or epidemics occurring in the future are natural and inevitable. In retrospect, airlines not only need to look into recovery options but also how they can better prepare themselves in the face of another global pandemic or epidemic.

What can airlines do to effectively combat an airline recession? What technologies and strategies will prove useful in the battle against the post-COVID-19 airline recession period and even beyond?

The Challenge – Changed Customer Behaviour

To find the solution, we must first identify the problem. In this case, the problem is changed customer behaviour. We’ve discussed in detail how the global economic recession will affect global air-ticket sales in a post Coronavirus world. The driving factor behind falling and low air-ticket sales during the post Coronavirus airline recession will be changed customer behaviour.

In order to sustain business through the post Coronavirus airline recession, airlines will have to adapt to cater to the changed buyer behaviours. A successful recovery will depend on airlines identifying the changed customer behaviour and adopting proper marketing strategies to better exploit the new market scenarios.

However, the challenge faced by airlines will be to accurately identify this new change in customer behaviour and reacting fast enough with suitable actions to re-capture and re-motivate customers.

How do you get customers’ attention? Appeal to their wants, needs and lifestyle. A customer-centric e-commerce strategy can help achieve this. Let’s see how a Big Data Analytics driven personalized approach supports this strategy.

How to Fight the Airline Recession with Airline E-commerce

E-commerce is one of the best tools available for airlines to fight the recession. There are a number of ways airlines can optimize their e-commerce platforms for optimum performance. However, we discuss the best available strategy tools airlines should pay attention to during the oncoming post Coronavirus airline recession.

Personalized Discounting

In an attempt to re-motivate and attract customers during and after the recession, airlines look into market-wide discounting and promotions via airline e-commerce. However, you want to avoid market-wide discounting.

Market-wide discounting are generic offerings in which all customers who search for flights at the same time are offered the same discount. This will only cause more harm than good by leading to dilution and revenue leaks.

Customers who were already going to purchase will still make use of the discount and the other customers airlines may have been targeting may not engage if the promotion or level of discount was not compelling enough for them to act. This results in revenue loss from customers who were going to purchase regardless and missed sales from potential customers that were the target group. Both being very bad news for airline recovery.

This is where airlines can use personalized discounting on airline e-commerce. Personalized discounting is about leveraging individual price elasticity and customer behaviour to offer some reduced fares or special promotions to the correct target customers without making the discount promotion available to all.

Through Big Data Analytics, airline e-commerce can identify hesitant buyers and roll out the appropriate personalized promotion or discount based on their buyer behavior and price elasticity to draw them in to purchasing.

Through Big Data powered personalized discounting, airline e-commerce can leverage their customer data to develop feed into a machine learning-based promotion system that will match the right promotion with the right customer.

This way, airlines can make promotional campaigns more effective to secure and increase sales while avoiding the pitfalls of campaign failing and revenue leaking.  

Personalized Recommendations

In the race to raise revenue back up during the airline recession, effective up-selling and cross-selling through airline e-commerce will play an important role in securing more sales and increased revenue.

The personalized recommendations engine is the strategy and programmed process of automatically suggesting products/service that best compliment buyers at an individual level on airline e-commerce.

When it comes to airfare and ancillary sales, bombarding customers with all or irrelevant recommendations isn’t effective and is rather overwhelming for the customer.

It’s a simple concept, we are more inclined and motivated to buy when we see an offer or product/service that appeals to us than when we are shown items irrelevant to us.

You sell more by targeting the right customers at the right time with the right offers.

Big data-powered personalized recommendations take out the assumptions and guesswork in marketing and selling. They take away the complicated decision on which flight offers and ancillary items to recommend.

Big Data powered e-Commerce personalized recommendations systems identifies the customer’s specific needs based on each individual’s on-site customer behaviour and displays relevant recommendations.

Personalized product recommendation engines use Big Data Analytics and Data Science methods to learn who customers are and what customers want through the use of implicit input methods. Implicit input methods include tracking every customers’ on-site behaviour and past interactions on airline e-commerce.

These data points are then fed through heavy machine learning to profile a customer and produce the best possible recommendations to match each individual customer.

Big Data Analytics powered personalized recommendations operate on a multi-dimensional foundation. Which means it does not track or recommend based on one factor, rather it takes into consideration multiple factors to better understand the customer when recommending.

The incorporation of personalized multi-dimensional e-Commerce analysis and recommendation systems enables an effective high functioning selling system to drive higher cross-selling sales, up-selling revenue and customer satisfaction. It is designed to make selling easier for airlines and buying easier for customers.

Personalized Dynamic Pricing

The COVID-19 outbreak’s impact has not been equal across the world in every country or for every customer segment.

Although there will be a post-Coronavirus wide-spread global recession, customer segments will be affected differently from a financial standpoint. Depending on a varying number of factors, customers will be spread out on a spectrum ranging from some customer segments being heavily impacted and others not as much.

And one thing will be clear, this renders airline’s current pricing and pricing strategy completely futile. Airlines will need to develop new pricing by re-learning their customers’ new price elasticity and buying behaviours.

Big Data Analytics powered Personalized Dynamic Pricing is one tool that can enhance airline’s efforts to price intelligently at digital speed. Developing and making pricing offers by catering to individual customer price elasticity could be the antidote to re-motivate buyers and increase revenue per sale.

At its core, Big Data Analytics powered Personalized Dynamic Pricing, also known as intelligent pricing, is the practice of changing pricing based on a varying number of variables. It is a pricing strategy in which businesses set flexible prices for products or services based on customer behaviour, demography variables and market demand factors.

Currently, most airlines operate on a generic Dynamic Pricing model. When high demand coincides with short supply, then airlines charge more for the product. This model is rigid and soon becoming outdated and inefficient especially for the time period during airline recession recovery.

Airlines can optimize total revenue by taking this a step further. Pricing needs to look at more than just the traditional factors.

Big Data Analytics powered Personalized Dynamic Pricing is not a new concept, especially in e-commerce. There are a number of businesses that utilize Personalized Dynamic Pricing and most certainly you would have come across it even if you were unaware that dynamic pricing was at play. It’s widely used in e-commerce by giants like Amazon, Expedia, Adidas and many third-party platforms selling air tickets and travel accommodation.

Using Big Data Analytics powered Personalized Dynamic Pricing, airline e-commerce can have access to many more important customer variables for constructing the perfect pricing. It uses real-time market data to determine and make the best-suited pricing suggestions that maximize revenue and sales.

Big Data Analytics will capture the billions of pieces of transactional data every hour of every day on your airline e-commerce platform. Analytical algorithms will then process the data and turn it into pricing decisions based around the objectives set by airlines – eg: revenue maximization.

The system then offers different prices to customers depending on what it knows about each passenger’s demography, preference and price elasticity.

An airline can use what it knows about customers to promote either a higher-priced or lower-priced package. If it is determined that a customer is likely to have a higher price elasticity, the airline can promote a higher-priced fare and hide its cheaper fares or position them at the bottom of a list and vice versa.

This would work for increasing sales by introducing a new customer or hesitant buyer with an especially affordable ticket or increase revenue by offering a higher ticket price to someone who is likely to be undeterred by an up-charge.

This doesn’t have to be extreme; airlines can still retain control over the pricing. Airlines can set a price floor and a segment price range that reflects the brand value and allows them the flexibility to stay profitable. All new pricing recommendations determined by the system for each customer segment is also subjected to pre-approval before being incorporated into the pricing cycle.

The Role of Big Data Analytics in customer-centric e-commerce strategy

Throughout this article, you may have noticed the words Big Data Analytics being repeated. That is because Big Data Analytics and Data Science are the foundation and lifeblood of the above-listed strategy tools. The system is what powers Personalized Discounting, Personalized Recommendations and Personalized Dynamic Pricing.

Monitoring hundreds of thousands of interactions on airline e-commerce and keeping an eye on real-time supply and demand trends is a highly complex and challenging task, beyond the scope of most companies. This is where Big Data Analytic solutions step in. Only a Big Data Analytics system is built with the processing power to handle such a large proportion of data processing and scale horizontally for growth.

Big Data Analytics is used by many e-commerce giants like Amazon, Best buy and travel websites to gather insights on their customers; who they are, what they are looking for and how much they are willing to pay.

Today, there are plenty of open source Big Data tools tools such as special databases which can be utilized to investigate customer behaviour.

Utilizing data of customer behaviour is done by tracking customers interactions with e-commerce platforms such as the mobile App and Web platform. The Big Data system system gathers and processes millions of data of every second of customer interaction and examines data sets in order to draw conclusions about the information they contain and produce optimal and realistic decision based on the data.

Hence, it is important that the personalized recommendation system, personalized discounting system and dynamic pricing system you choose are powered by Big Data Analytics.

Concluding Notes

We’ve discussed in detail the best strategic e-commerce tools available for airlines in terms of helping further their goal of bouncing back from the airline recession. With this, airlines and relevant personnel can now focus on exploring the incorporation of these strategic tools to help recovery.

The above mentioned 3 tools all help airlines achieve one common goal; increase revenue and profit.

• Personalized discounting increases sales and prevents revenue leak by offering the right discount to the right customer on airline e-commerce.

• Personalized recommendations increase revenue and sales on up-selling/cross-selling by introducing the right offers to the right customer on airline e-commerce.

• Dynamic pricing allows airlines to re-motivate customers and secure more sales with better price positioning to match individual customer price elasticity on airline e-commerce.

Airlines do not need to incorporate and roll out all three strategy tools at one go. Airlines can start off slow by incorporating one and gradually adding the others or even choosing to stick to one tool.

With competition rising and demand falling, optimizing airline e-commerce with the necessary tools can make the difference that is needed.

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