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• Post :- 28th Feb 2025

Optimize testing design leads to better business outcomes
Estimate P&L Impact of proposed Loyalty Program features
ROI maximization and risk mitigation
Improved decision making via higher confidence in testing outcomes balanced rigor vs testing speed and size

IIdentify measurable KPI Metrics
Identify hypothesis and number of testing/control groups
Identify KPIs where client can measure true lift in the shortest amount of time (e.g., increased onboard spend, 60-day rebooking rate)
Identify key population segments and determine whether they can feasibly support an A/B/n test

Identify Test and Control Groups
Determine sample sizes and test duration using Power Analysis to ensure feasibility
Select testing/control sailings to maximize similarity between testing groups using clustering and optimization techniques
Optimize guest population to measure KPIs against using a matched-pairing design (not random) and indexing

Evaluate Test's Business Benefit
Quantify difference in guest behavior through statistical tests to determine the signal from the noise
Evaluate immediate business impacts of the pilot by monitoring short-term KPIs
Monitor long-term guest behavior with more robust KPIs to augment findings