Airlines spend millions of dollars annually on advertising, showcasing their brands and fares across the spectrum of digital, radio and television. However, there is typically little science behind those marketing decisions, with no rigorous analysis to see how best to allocate ad dollars.
Some airlines determine the mix by simply allocating a certain percentage annually to each media vehicle, regardless of the intent or audience. For example the Marketing budget may be divvied up with Internet banner ads getting 20 percent, radio 40 percent, newspapers 30 percent, and TV 10 percent.
The lack of precise analysis behind this approach hasn’t stopped airlines from attempting to measure the effectiveness of those campaigns, asking questions such as “What’s the return on investment on those banner ads?”
What today’s airlines need is a better analysis – specifically, Marketing Mix Optimization – so that they can understand which media vehicles work best. By doing so, airlines can do more with the same amount of marketing dollars and the return on investment of the marketing vehicles will soar to new heights.
A Marketing Mix Optimization works by uncovering the incremental benefit of each campaign and aggregating that to the channel level. There are three critical aspects of Marketing Mix Optimization:
- Normalizing the data. Airlines should adjust their marketing data to control for the factors outside of the marketing campaign, including pricing, promotions, seasonality, the latest trends, weather and capacity. Without normalization, companies can end up with incremental results totaling more than 100 percent of the produced revenue – which is obviously more than just questionable;
- Examining the noise. Though the analysis has separated out the noise, that doesn’t mean airlines should forget about it altogether. Instead, they should quantify the revenue impact of those factors;
- Performing a regression analysis. Analysis of the normalized data is needed to calculate the return on investment for each campaign, determine the average impact from each channel, and predict the incremental uplift expected from each marketing vehicle going forward.
This approach has worked in other industries, and can work for airlines. For example, an international retail and specialty service provider with 11,000 stores undertook Marketing Mix Optimization. The analysis showed that the company spent very little on national cable TV advertising, despite the fact that this vehicle yielded the biggest results.
The recommendation – that 40 percent of marketing spend go to a year-long national TV campaign – drove a 1 percent uplift in demand based on brand awareness marketing alone.
Airlines can maximize the return on their marketing spend by leveraging predictive analytics, which provides an edge over the competition and drives revenue growth.