At a recent D: All Things Digital Conference, Ticketmaster CEO Irving Azoff proclaimed, “We haven’t done enough dynamic pricing for tickets, and we should, and that will help make people happy.” Mr. Azoff is right, dynamic pricing is the key to pricing for profits and growth in the rock concert industry.
The challenges of setting concert ticket prices come down to two key issues: (1) uncertainty and (2) properly scaling the house (setting the right price for different seats).
In an industry where high financial guarantees to artists are the norm, promoters need to set the right ticket prices to survive. There may be 12,000 fans cheering for an encore, but if a promoter had bet that the attendance would be 13,000, s/he is sulking over a big loss.
Their profit comes after selling those last 1,000 seats. Given that tickets are routinely sold six months before a show, it’s impossible to undertake an accurate pricing/attendance analysis. Much can change in six months: An artist may get heavy airplay and high promotion, other similar acts may be playing the same week, there might be poor weather, and so on.
Even if a challenge is known, it’s hard to quantify its effects. A Hall of Fame band may have sold well two years ago, but will its classic rock fans be as enthusiastic this year? We all know that this summer will be economically challenging for concert fans. So why are some bands doing well, while others aren’t?
It is difficult to properly scale a venue. Having just two or three price levels won’t capture the value of every seat. Standing in Row A is a lot better than sitting in Row Z. But at most venues, these tickets are priced the same. Similarly, being in the center of Row A is more valuable than in a seat at the end of the same row. Profits are being left on the table.
One solution, of course, is to add more tiers. But if it’s a challenge setting accurate prices for three tiers, it’s hard to believe that setting 10 would be more precise. Should the price differential between Rows F and G be $25 or $50?
Some have suggested using an analysis on historical data to set prices. Yes, using past data in conjunction with experience is always better than not doing so, and analysis may help set initial ticket prices. But an analysis on years-old data cannot capture the uncertainties of today’s demand and ensure that Rows C and R are priced properly.
Would you risk losing $100,000 by relying on an analysis of one- to five-year-old data that “estimates” those crucial last 1,000 seats will be sold? I wouldn’t. There’s too much uncertainty. Mining past data can provide good insights, but it won’t solve the concert industry’s pricing challenges.
What do industries that use dynamic pricing such as airlines and hotels have in common? They all have high demand uncertainty and offer perishable products.
