Starting out with dynamic pricing is a bit like learning to swim. But what if promoters just can’t bring themselves to jump into the deep end with dynamic pricing? Is there a way to wade into it cautiously, without diving in headfirst?
The new Disney seasonal pricing has some asking, “Has Disney gone too far?” The better question is, “Has Disney gone far enough?” Variable pricing is a step in the right direction, but has its limitations.
Disney announced on February 27 that it was implementing “seasonal pricing” for its California and Florida theme parks. Or was it “surge pricing?” Maybe “variable pricing?” Perhaps it was “demand-based pricing.” It might have been “dynamic pricing.” We take a closer look at what Disney did and did not do with pricing.
“Walt Disney Co.’s move to lift prices at Disneyland and its other theme parks on busy days was a novel step for the entertainment giant, but the news made perfect sense…”
Sometimes the optimal price for a ticket is less than the minimum price you’ve established. Decide ahead of time whether you’ll be willing to break your own constraints if the data tells you that a lower price is optimal.
Surge pricing may be necessary for Uber to manipulate its supply of independent-contractor drivers. But that’s not what all, or even most, dynamic pricing programs look like. There are many you don’t hear of, because there aren’t angry customers to write about!
The best pricing strategy is one that blends the best available data science with the art of pricing — that is, with management experience and judgment. The question is, how do you put in place a process for blending the best available “art” and “science”? Here are three steps we take to help our clients achieve the optimal balance.
In most dynamic pricing implementations, there are multiple business goals in play, requiring combination into a single, well-defined economic problem for dynamic pricing to solve. Therefore, it’s easy to see that a generic pricing algorithm cannot serve every client without customization.
Some businesses are positioned to see greater return on investment in dynamic pricing than others. Wondering whether your business is a good fit for dynamic pricing? Consider these three factors that predict dynamic pricing success.
Trusting an algorithm to make pricing decisions can be intimidating. But a recent study published by the University of Pennsylvania’s Wharton School shows that “algorithm aversion” is normal and can be overcome.