Kiwi.com founder: data is what keeps cheap flights alive

Oliver Dlouhý, founder and CEO of the Czech travel startup Kiwi.com, has described how the company uses data to survive in an extremely competitive, low-margin business. According to him, without analytics the company could not set prices that are simultaneously profitable for the business and attractive to customers.

Dlouhý appeared as a guest on the Money Movements podcast alongside Visa's director of consulting services, Hana Wasserburger. The conversation focused on how companies make decisions based on data rather than intuition — and why that directly affects profit.

According to research by McKinsey and the Harvard Business Review, data-driven companies show 20% higher revenue growth and 30% better customer retention than competitors that rely on intuition. "Many firms have paid dearly for making decisions based on gut feeling," Dlouhý noted. He said Kiwi.com has relied on data from the very start, since the business operates with extremely thin margins and fierce competition — predicting customer purchasing behavior is critical here.

One concrete example is a study Kiwi.com conducted together with Visa, which showed that the company is successful in the budget flight segment but is missing opportunities in business travel and more expensive long-haul flights. "We found that purchase fragmentation among our competitors is greater than we assumed, and that we have an opportunity to move into segments where we haven't been especially active. We've already launched several initiatives that should let us grow our share in these markets," the entrepreneur said.

According to Dlouhý, the key to working with data is first to clearly define the problem that needs solving — for example, customer retention or sales growth — and then to choose which data to track, and how to clean and analyze it. After evaluation, a pilot program is launched and then refined based on A/B testing results.

The travel industry, where Kiwi.com operates, is especially well suited to data analysis thanks to the huge volume of transactions, which makes it possible to build full customer profiles — where people are traveling from, for how long, in which season, and which products and services they are looking for.