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Growth Through Customer Retention
Objective
Develop a predictive model that will enable the airline to grow their customer base by:
- Reducing revenue leakage resulting from customer attrition
- Illustrating how attrition varies by customer category (new vs. returning vs. win-backs)
- Proactively communicating with customers at-risk of attrition
Industry: Destination Airline Travel
Services: Technology Innovation
Technology: Predictive Attrition Model
Use the outcome for hedging on fuel and other capacity planning efforts
Established
$70.5M
in incremental revenue retention opportunity
Identified leading indicators of customer attrition – inclusive of actionable business rules logic that could be leveraged ahead of full model operationalization
Our Client
Our client is a mid-tier destination airline seeks to drive active customer base growth by improving customer attrition.
Challenge
The airline recognizes this as a critical lever for their growth, given that current attrition rates are almost 60%. Overcoming this challenge is paramount for the airline achieving its strategic business objectives, considering that customers can only book travel directly with the airline.
Approach
Build a Predictive Analytics Attrition Model that:
- Identifies customer characteristics that explain attrition likelihood
- Scores customers’ likelihood to attrite within the subsequent year
Outcomes
- Advised complementing the predictive model with predictive retention and conditional spend
- Suggested overlaying demographic data to provide visibility to customer personas and design personalized offers / targeted communications to at-risk customers
- Advocated data management initiatives to permit employing other internal assets to enhance the model’s predictive power
Impact
- Identified leading indicators of customer attrition – inclusive of actionable business rules logic that could be leveraged ahead of full model operationalization
- Established ~$70.5M in incremental revenue retention opportunity (over the business as usual/random model)
- Corroborated the predictive value of the airline’s internal and external data sources to refine the roadmap and next steps
- Use the outcome for hedging on fuel and other capacity planning efforts
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