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CASE STUDY
Top 3 US Airline
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The
Challenge
The airline had insufficient insights into their customer base.
While they had many disparate customer, flight, etc., datasets, they struggled to organize data and analytics for marketing and customer service activities in a centralized manner.
The prior approach was limited by rules-based targeting and an inability to learn and adapt with unconnected technologies, analytics approaches and reporting systems.
The
Solution
ElectrifAi deployed and scaled an Ai-driven solution to 90M+ customers within 6 months. We created a 360° demographic and behavioral customer view with algorithms to maximize accuracy, fill gaps, uncover hidden information, and enhance understanding of trip attributes. With advanced predictive and prescriptive analytics, we transformed campaign performance and customer service.
Our ML has enabled a suite of insights into customer needs, predicted actions and the campaign pipeline:
- Segmentations for the whole customer base
- Targeting of SME products
- Targeting of credit card types
- Customer Revenue
- Customer Experience and Disservice Score
- Propensity to churn
- Propensities to purchase miles, upgrade, opt for partner offers, add ancillary services
The
Value
Lift per customer
$500
by proactively predicting & mitigating high value customers at-risk
Customer sentiment
+25%
through identification of dis-serviced customers
Partner transactions
+16%
from personalized campaigns targeted with ancillary-product propensities
Case handling time
-30%
with new Customer Care app built with integrated data
New SME Customers
100
in 6 months by targeting travelers based on flight and redemption habits
