How do you experiment with new airline marketing techniques?

2 Choose your experiment type and method

Depending on your goals and metrics, you can choose different types of marketing experiments to test your hypotheses and assumptions. For example, you can use A/B testing, multivariate testing, or factorial design to compare different versions of your website, landing page, email, or ad. You can also use surveys, interviews, focus groups, or observation to gather feedback and insights from your customers or prospects. You can also use online tools, platforms, or services to conduct and manage your experiments, such as Google Optimize, Optimizely, SurveyMonkey, or Qualtrics.

3 Segment and sample your audience

Another important step in designing your marketing experiments is to segment and sample your audience. You need to identify and select the groups of customers or prospects that you want to target with your experiments, based on criteria such as demographics, behavior, preferences, or needs. You also need to determine the size and method of your sample, depending on your budget, time frame, and statistical significance. You can use random sampling, stratified sampling, or cluster sampling to ensure that your sample is representative and unbiased.

4 Run and monitor your experiments

Once you have defined your goals, metrics, experiment type, method, audience, and sample, you are ready to run and monitor your experiments. You need to follow the best practices and ethical guidelines for conducting marketing experiments, such as ensuring informed consent, privacy, transparency, and validity. You also need to monitor your experiments regularly and collect data and feedback from your participants. You need to check for any errors, anomalies, or issues that might affect your results or conclusions.

5 Analyze and report your results

The final step in experimenting with new airline marketing techniques is to analyze and report your results. You need to use appropriate statistical methods and tools to process and interpret your data and feedback. You need to compare your results with your goals and metrics, and identify any significant differences or trends. You need to draw conclusions and recommendations based on your findings, and communicate them clearly and convincingly to your stakeholders. You need to highlight the strengths, weaknesses, opportunities, and challenges of your experiments, and suggest ways to improve or scale them.