Customer Value Scoring Model for Airline Revenue and Frequency
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Solution Overview
Problem
The airline industry lacks effective customer value models that consider both net revenue and flying frequency, making it difficult to accurately evaluate customer contributions and identify valuable customers.
Innovation Solution
A computer-implemented method and apparatus that evaluates customer records by assigning scores based on net revenue and number of flights, sorting records accordingly, and assigning an evaluation score to each customer, ensuring that records with different attribute values are ranked differently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If customer value is measured solely by net revenue contribution, then revenue measurement is simple and direct, but frequent fliers who contribute less immediate revenue are undervalued and may be lost
Solution Approach 1:
The patent transforms the single parameter of net revenue into multiple parameters including net revenue contribution, number of flights, and miles flown. It applies scoring functions to convert these parameters into normalized scores that can be combined, thereby changing the measurement parameters to achieve more accurate customer valuation without excessive complexity
Solution Approach 2:
The patent segments the customer evaluation into distinct components: net revenue scoring, flight frequency scoring, and mileage scoring. Each component is evaluated separately through its own scoring function, then combined to produce an overall customer value score, making the complex evaluation process more manageable and interpretable
2Measurement precision
If multiple customer attributes are considered in evaluation, then customer value assessment becomes more accurate, but the evaluation process becomes more complex
Solution Approach 1:
The patent converts multiple customer attributes (net revenue, number of flights, miles flown) into standardized score parameters through scoring functions. This transformation allows different types of data to be compared and combined on a common scale, improving evaluation accuracy while managing complexity through normalization
Solution Approach 2:
The patent adds a new dimension to customer evaluation by introducing scoring as an intermediate layer between raw attributes and final evaluation. This creates a two-dimensional evaluation space (attributes × scores) that facilitates more accurate multi-criteria assessment while maintaining systematic complexity
Data Source
AI summary
A computer implemented method of evaluating customers in the airline industry in a given period is disclosed. Records of each customer' contribution factors, which include net revenue and number of flights, are first obtained. A score is then assigned for each of the attribute values. The records are consecutively sorted by the assigned scores, first for the net revenue, then for the number of flights. The records are further sorted by the raw values of the net revenue and number of flights, preferably until, records having different net revenue and/or number of flights have been sorted to different ranks. Finally, an evaluation score is assigned to each record which has been sorted.