Aviation

Flight Ancillary Recommendations

Data-driven system that personalizes travel add-on recommendations based on customer profile, route details, and previous purchasing behavior.

This template can be edited in GoRules BRMS

Solution

This intelligent recommendation engine helps airlines boost ancillary revenue by delivering personalized product suggestions that match each traveler's specific journey context. The system analyzes multiple factors including loyalty tier status, flight duration, travel purpose, and destination type to recommend the most relevant add-ons like lounge access, priority boarding, or extra baggage.

For business travelers, it prioritizes productivity-enhancing services such as WiFi and fast-track security, especially for frequent flyers on medium to long routes. Leisure travelers receive suggestions focused on comfort and experience enhancement, while family groups see recommendations for practical needs like family seating and entertainment packages. The system also examines previous purchase history to avoid redundant recommendations, ensuring travelers only see relevant new offerings they haven't already bought.

How it works

The recommendation engine follows a structured evaluation process:

  1. Flight Classification: Categorizes flights as short, medium, or long based on duration in minutes.
  2. Customer Analysis: Evaluates loyalty status and examines previous purchase patterns to identify premium customers and product preferences.
  3. Base Recommendations: Generates initial suggestions by matching travel purpose (business, leisure, family) with flight duration and customer attributes.
  4. Contextual Enhancement: Adds specialized recommendations based on route characteristics (international, beach destinations) and airport facilities.
  5. Priority Assignment: Ranks all recommendations by relevance score to highlight the most valuable suggestions first.
  6. Recommendation Consolidation: Merges all suggestions into a unified, prioritized list for presentation to the customer.

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