The post-regulation airline industry was an era of labor strife, price wars, fluctuating fuel prices, increases in customers, and rapid technological advances. From 1978 to 2001, nine major airlines went under, and hundreds of small carriers went out of business as well.
As a small airline with limited overhead, People Express Airlines could initially afford to pursue an aggressive pricing strategy. By analyzing previous demand for a given route, People Express determined the lowest fare it could profitably offer – and made all tickets available at that price.
American Airlines, in contrast, was one of the first airlines to invest in a central, computerized booking experience. Its management team came to the epiphany that if it categorized its bookings into different segments, it could start to predict demand for its flights going forward. This allowed them to slash prices for some customers, while maintaining regular prices for others.
While People Express offered all of its tickets at a single low price based on historical demand, American’s superior data technology and predictive models enabled it to ensure that only a small percentage of tickets on a given plane (that might have otherwise gone unsold) were available at steep discounts, while vacationers and business travelers would pay different, higher rates.
Ultimately the ability to dynamically change pricing in real-time based on predicted demand enabled American to gain market share, while People Express struggled with debt and was ultimately merged with Continental in 1987. Predictive analytics continue to factor heavily into how prices are set for today’s airlines. Air travel remains a low-profit margin industry and the ability to forecast fluctuations in demand is critical. However, these sorts of tools aren’t just for the people selling tickets anymore. Travel booking site Kayak launched a Price Predictor feature, so now consumers can see their own projection as to whether the current ticket price is likely to go up or down over the next week.