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’s 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, airline 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 Behavior
To find the solution, we must first identify the problem. In this case, the problem is changed customer behavior. 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 behavior.
In order to sustain business through the post Coronavirus airline recession, airlines will have to adapt to cater to the changed buyer behaviors. A successful recovery will depend on airlines identifying the changed customer behavior 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 behavior 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 on coming post Coronavirus airline recession.
In an attempt to re-motivate and attract customers during and after 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 behavior 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.
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.
Personalized recommendations is the strategy and programmed process of automatically suggesting products/service that best compliment buyers at an individual level on airline e-commerce.
Personalized recommendations is great tool used to increase sales, up-sell and cross-sell services on airline e-commerce- most importantly for the post Coronavirus airline recession period; to secure more sales and increased revenue via airline e-commerce sales channel.
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.
Its a simple concept, we are more inclined and motivated to buy when we see an offer or product/service that appeal 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 takes out the assumptions and guess work in marketing and selling. It takes away the complicated decision on which flight offers and ancillary items to recommend.
Personalized recommendations are made based on each individual’s on site customer behavior. Big Data powered e-Commerce personalized recommendations systems identifies the customer’s needs and displays recommendations based on those specific needs.
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 behavior 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 outbreaks 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 behaviors.
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 behavior, demography variables and market demand factors.
Currently, most airlines operate on a 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. Its widely used in e-commerce by giants like Amazon, Expedia, Adidas and many third-party platforms selling air tickets and travel accommodation.
Big Data Analytics powered personalized dynamic pricing 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 everyday 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 to help on 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 their 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
Through out 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 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 insight on their customers; who they are, what they are looking for and how much they are willing to pay.
Utilizing data of customer behavior is done by tracking customers interactions with the 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 chose is powered by Big Data Analytics.
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 increase sales and and prevents revenue leak by offering the right discount to the right customer on airline e-commerce.
- Personalized recommendations increases 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.
What are the 3 best strategic e-commerce tools that will help airlines recover from the recession?
1. Personalized Discounting
2. Personalized Recommendations
3. Personalized Dynamic Pricing
How will Personalized Discounting help airlines increase sales and revenue?
With Personalized Discounting airlines can avoid the common pitfalls of revenue leak and unconvinced buyers caused by market-wide generic discounting and promotion.
Personalized Discounting leverages Big Data Analytics to offer the right discount to the right customer based on their buyer behavior.
How will Personalized Recommendations help airlines increase sales and revenue?
Bombarding customers with irrelevant up-selling and cross-selling offers will get you no where.
Personalized recommendations powered by Big Data Analytics is automated to target the right customer with the the right ancillary products and services. When customers are shown the right products/services, they are more likely to purchase.
How will Personalized Dynamic Pricing help airlines increase sales and revenue?
The COVID – 19 recession will impact different customer segments at different levels from a financial standpoint.
Intelligent pricing by catering to different customer price elasticity will help re-motivate buyers and increase revenue per sale.
Dynamic Pricing powered by Big Data Analytics enables airlines to automatically price position to match individual customer price elasticity based on customers’ buyer behavior and demography.
What is the role of Big Data Analytics in these systems?
Big Data Analytics and Data Science are the foundation and lifeblood of the above listed strategy tools.
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 necessary for the tools to operate effectively.
Should airlines incorporate all 3 tools at once?
This is not necessary. Airline can adapt and push out each tool to a degree and speed that best fits their goals. Each system works independently of each other and contributes in specific ways to help airline recovery.