This is the fourth and final installment in my podcast series, How Airlines Become Data Driven, where I’ve gone back to Diggintravel’s hands-on roots and shared practical lessons from more than five years of working with airline ecommerce, digital marketing and analytics teams.
The series has followed a simple progression.
In the first episode, we looked at the habits, routines and ways of working that enable airline teams to become more data driven.
The second episode focused on building trust in digital data. Before analysing performance or optimising campaigns, we first need confidence that the numbers we’re using are reliable.
In the third episode, we connected the dots. We explored how to consolidate different data sources into one joined view and use a top-down approach to understand what is really driving airline performance.
This fourth and final episode takes us to the last and most advanced stage.
Once we trust our data and understand the relationships between our most important metrics, how do we determine whether marketing actually caused a change in customer behaviour? Did a campaign generate incremental flight searches and bookings, or would those customers have booked anyway?
In my experience, airline digital teams rarely reach this stage. In the episode, I explain why that is and explore the data, analytical methods, experimentation and organizational commitment required to move beyond conventional attribution and correlation.
But when airline teams do reach this stage, they can begin to answer the marketing questions that really matter. They can measure the incremental impact of their campaigns, understand which channels genuinely create additional demand, and make better decisions about where to invest their marketing budgets.
Listen to the fourth and final episode of the Diggintravel Podcast series, How Airlines Become Data Driven. In this episode, we explore how airline marketing teams can move beyond attribution and correlation to understand whether their marketing activities actually generate incremental demand, flight searches and bookings.
Or, read on for the key takeaways, a practical framework for measuring marketing impact, and real examples from airline consulting projects.
And don’t forget to subscribe to the Diggintravel Podcast in your preferred podcast app to stay on top of the latest airline UX, digital strategy, marketing, data science and AI trends!
Over the years, I’ve developed a practical framework for helping airline teams move beyond conventional attribution and start measuring the incremental impact of their marketing activities. The goal is to answer a deceptively simple question: did our marketing generate additional demand and bookings, or would they have happened anyway?
The framework consists of six steps:
Most importantly, airline marketing and digital leaders must be genuinely willing to test their assumptions and learn how much incremental value their campaigns, or other digital activities are actually creating. This is often harder than it sounds. We become attached to established routines, channels and ways of measuring success, while the results may challenge some of our previous decisions and investments. The key is a genuine willingness to learn, change and improve.
The infographic below summarises the six steps airline teams can follow to move from trusted, connected data to measuring the incremental impact of their marketing activities.
In the podcast, I discuss several methods airline teams can use to move from identifying relationships to estimating the incremental impact of marketing. These range from relatively simple trend, correlation and regression analysis to structured incrementality experiments, geo-lift testing, market matching, causal-impact analysis and Marketing Mix Modeling.
Explaining each of these methods in detail, especially the data science behind them, is beyond the scope of this podcast and article. In our airline consulting projects, we develop and apply these approaches together with data scientists, combining their statistical expertise with our understanding of airline marketing, ecommerce, customer behaviour and the wider business context. As I explain in the podcast, one of the most critical parts of this process is the moderation and orchestration between airline marketing teams and data scientists. Building that bridge ensures that the analysis starts with the right business questions, uses the right context and ultimately produces results that marketing teams can understand and act on.
The examples below illustrate some of the analyses and experiments we have used in practice. They are not intended as detailed technical explanations, but as examples of how airline teams can begin testing their assumptions and learning whether their marketing activities are actually creating incremental demand and bookings.
This article concludes the four-part How Airlines Become Data Driven series. Here is an overview of the complete series and the practical progression from building data-driven habits to measuring the incremental impact of airline marketing:
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