Airline Cargo

Boosting air freight revenues and value through personalization

Boosting air freight revenues and value through personalization

While online retailers are digital transformation trailblazers, industries like cargo have been slow adopters. Yet, no matter how far ahead or behind the digital journey, the pandemic demonstrated how important modern technology is for integrated cargo management system and resilience. And this has been a catalyst for technological evolution in air freight.

Platform booking solutions have been one of the greatest benefactors of air freight's digital evolution. While steps have been made to modernize air freight commerce and bookings, personalization is going to be the big step change in this space.

Why are personalized B2B offers so important?

Personalization is about delivering enhanced customer experiences that balance revenues with value and relevance. It also builds deeper relationships by showing your customers that you understand and value their needs and preferences. In a digital landscape with so much information and choice, personalization helps overcome "paralysis by analysis", accelerate decision-making, and boost conversion by influencing and guiding customers towards a desired outcome.

Advances in data analytics and artificial intelligence already help identify and relate patterns in human behavior to different stimuli. And these are getting better by the day. Even in its current state, field science helps tailor solutions that make customer experiences more relevant and personalized. For air freight, much room remains to improve modern data-driven sales and recommendation engines will be key.

How do recommendation engines work? 

In today's digital landscape, we are all subject to recommendation engines. Whether searching for a flight, picking a movie on Netflix, or shopping on Amazon, recommendation engines are always behind the scenes and how they decide to propose one offer over another can broadly be classified in two practices:

1. "Content based filtering" categorizes products and services according to specific features and attributes, aiming to make a link with the user's past behavior. For example, after watching a movie on Netflix, you might be recommended a different movie with the same star or genre. Recommendations are driven by the categories and subcategories that a user interacts with.

2. "Collaborative filtering" is a broader behavioral recommendation approach that looks at a user's previous history and interactions, matching them with that of similar users. The focus is behavioral rather than based on a product or service's specific features and attributes. Here, Netflix might recommend an Al Pacino movie after watching a Robert De Niro flic based on user behavioral patterns even if the stars and genres are different.

How do personalized recommendations and offers play into air freight? 

Although starting from a weak base, data quality in air freight is improving and is destined to continue doing so given increasing security and regulatory compliance. In parallel, almost 80% of cross-border eCommerce shipments move as air freight. With customer and market dynamics moving unwaveringly towards online shopping, increased digitalization comes with the need to differentiate offers to stand out from the crowd. So how do we achieve this and accelerate customer conversion?

The answer is… You guessed it – personalization! Some of the big steps the air freight industry needs to undertake to enhance digital customer interactions include:

  1. Categorizing customers
  2. Presenting them with simple and relevant offers based on business history
  3. Channeling relevant upsell options, and
  4. Proposing beneficial cross-sell options.
So in air cargo, once we have categorized our customers and proposed a basic offer that fits their purchasing history, we could present an expedited shipping upsell option and a cross-sell option for documentation processing or door pickup. Pitching these in the relevant flow to the appropriate customers is key to increasing look-to-book ratios, while dynamic pricing ensures optimized yields.

Which recommendation model suits air freight best?

Content filtering is unable to address all aspects of shipment sales and related services. Likewise, the industry´s current state of data quality and reliability isn´t conducive to collaborative filtering. So a hybrid recommendation engine model emerges. While the industry´s data situation improves and adoption of modern retailing techniques accelerates, manual intervention will be critical to proposing relevant air freight recommendations. Product categorization and user behavior patterns are key to stitching a tailored customer offer and personalizing digital interactions. Fully automated recommendations will take off once the air freight industry´s data quality and reliability improve. Modern revenue management solutions that integrate valuable insights from the vast amounts of data operational systems and processes produce will be game changers for personalized air freight offers and determine who sets the tempo.

Author Info 

Anish has over 15 years of experience designing solutions that power success for IBS Software's air cargo customers. Having worked on numerous customer engagements around the world, Anish has developed a rich and deep understanding of the air freight industry. This helps him provide valuable insights and practical solutions to customers that have a real impact on their business and maximize new growth opportunities


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