Episode Details

In the fourth and final episode of the How Airlines Become Data Driven series, we move from analysing relationships to one of the most difficult questions in airline marketing: does marketing actually generate additional demand and bookings?

Traditional attribution can show which marketing channel received credit for a conversion. But it cannot necessarily tell us whether that booking happened because of the campaign or whether the customer would have booked anyway.

In this episode, I share a practical six-step framework for moving beyond attribution and correlation towards measuring the incremental impact of airline marketing.

In this episode, we talk about:

• Why airline digital teams rarely reach the incrementality stage

• The difference between attribution, correlation and causation

• How to define the business outcome or key metric you want to influence

• Why airline teams need trusted, connected data before attempting advanced measurement

• How external factors such as capacity, pricing, seasonality and competitor activity can influence results

• Why clear hypotheses are the starting point for meaningful analysis

• How existing or deliberately created variability makes marketing impact measurable

• How correlation, regression analysis and experimentation can help teams test their assumptions

• How market matching, causal-impact analysis and GeoLift tests can estimate incremental lift

• Where Marketing Mix Modeling fits into the measurement toolkit

• Why collaboration between airline marketing teams and data scientists is critical

• Why marketing leaders must be willing to challenge previous decisions, learn and adjust future investments

The episode is accompanied by a companion article featuring a visual six-step framework and five practical examples from airline consulting projects. These examples illustrate how airline teams can explore relationships between advertising and bookings, develop hypotheses, create test periods, compare treatment and control markets, and estimate incremental impact using different data science methods.

Explaining all the technical details behind these methods is beyond the scope of one podcast. Instead, the episode focuses on the practical questions airline marketing and analytics teams need to ask, the conditions required for meaningful measurement, and the importance of building a bridge between business experts and data scientists.

Whether you are evaluating an individual campaign, questioning the value of paid brand search, measuring the impact of brand advertising, or deciding how to allocate your marketing budget, the central question is the same: did your marketing create additional demand and bookings, or would they have happened anyway?

RESOURCES:

Read the companion article with the six-step framework, practical airline marketing analytics examples, charts, experiments and key takeaways from this episode:

https://diggintravel.com/does-airline-marketing-drive-more-bookings/