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The Challenge of Pricing and Selling Tickets for the Best of Both Worlds Tour
Answered

Too much demand, not enough supply

Peter Ericson, the VP of operations for TicketMeister, a major supplier of event management and ticketing services, sat in his office and nervously contemplated the drama unfolding on the message board before him. He had received an e]mail from Donnah Sumners, who managed the popular etween songstress Miley Cyrus (a.k.a.) Hannah Montana, directing him to a heated online exchange among fans about the pricing and availability of tickets for Cyrusf ongoing gBest of Both Worldsh tour.


Message after message excoriated what fans called the predatory pricing policies of Montana, Disney and TicketMeister in particular. Due to Montanafs overwhelming popularity, demand for her concert tickets vastly exceeded the venuesf available supply, even with many added tour dates. As a result, tickets that sold at retail for between $20 and $60 dollars had been scooped up by scalpers and were now being resold on the secondary market (via sites such as eBay and StubHub) for sums in excess of $500 per ticket.

Many younger fans and their parents felt that this situation was somehow condoned by the various parties involved in the concerts, and their clearly vented rage threatened to undermine the singerfs popularity and damage TicketMeisterfs already sullied reputation among the general public.

For years, ticket sales for large events at stadium and concert hall venues had been priced based on seating location and sold to the general public starting on a pre]announced day. While fans camping out and long lines at the box office were the outcome of excess demand in years past, the advent of online ticket sales, the emergence of secondary market players and changing regulatory environments had created a very different ticket sales experience for the modern concertgoer.

Now, when tickets when on sale on the allotted day, they frequently sold out online within minutes, and a sophisticated new breed of ticket scaler had begun using software to automate the purchase process and acquire as many tickets as possible through TicketMeisterfs site. With options such as StubHub and eBay now available that allowed scalpers to sell their tickets without standing in front of the venue on the day of the concert, prices for sold out events skyrocketed as they were resold.

It was clear to Peter that the old method of selling tickets via a box office at prices based on seating alone was threatened by this new gdigitalh way of doing things. He needed to find a way to price and sell tickets for events where demand outstripped capacity that would increase revenue for TicketMeister, the performer and the venue, decrease the revenue gstolenh by scalpers and other resellers, and still appease fans who felt that concert tickets should be affordable for all fans, not just rich Columbia MBAs and their children.

Changing patterns in event ticket sales

To tackle this problem, Peter asked his Pricing and Revenue Optimization Manager, a bright, recent graduate of Columbiafs Graduate School of Business named Patty Chenthier, to devise a solution. Patty was competent in quantitative methods and quickly realized that a solution could be found by estimating demand for the concert, and using that demand to optimize Ticketmeister revenue. Once this demand had been determined, Patty would develop a pricing scheme that would meet all of the objectives for TicketMeister and other concert stakeholders. But first he needed to find a set of data that could be used to estimate the true demand for Hannah Montana tickets.

Patty needed to estimate willingness to pay (WTP) data for those on the demand curve who were willing to pay more than the $20/$60 prices TicketMeister was charging. She collected demand data from eBay and StubHub by taking the final sales prices of all tickets being sold for a previous Hannah Montana concert (Exhibit 1). The data is believed to be representative of demand in most mid]sized to large cities, and can be used to construct a demand curve for future concert dates.


The next scheduled concert for the tour is in Charlotte, North Carolina. Exhibit 2 gives some basic demographic information about the city and estimated information about the total size of the potential market for Hannah Montana concert tickets. Exhibit 3 shows a diagram of the concert venue in Charlotte and provides expected prices for tickets in the venue given TicketMeisterfs current pricing scheme.

. Concert audiences for the tour to date have been primarily composed of girls, aged 10]16


. In local marketing surveys, approximately 50% of the target demographic in Charlotte indicated an interest in attending the concert


. Younger concertgoers are accompanied by older parents / chaperones at a ratio of roughly 3:1


. Approximately one in 10 HM concert]going fans is a fan club member

1.) Given the WTP data provided, find the optimal, revenue maximizing price that TicketMeister should charge for tickets to the Memphis, Tennessee show. What is the total revenue possible from this price level? How are fans and the general public likely to respond to this kind of pricing?


2.) Instead of charging a single price, TicketMeister is considering a tiered pricing scheme, with some tickets sold as gpre]saleh tickets at a higher price and the remainder sold at a lower price closer to the date of the concert. Assuming Memphisf demand for tickets is similar to previous concerts, what are the prices TicketMeister should charge for both the gpre]saleh tickets and the regular tickets? How many tickets should it set aside for gpre]saleh prior to the sale of regular (cheaper) tickets?


3.) What are the advantages of the time]based pricing scheme over current pricing policies and a single, revenue]maximizing price? What are the challenges TicketMeister might face as a result of this new scheme? When would this sort of policy be a good or bad idea? What could it do to prevent public outcry over ticket prices while still maximizing revenue?

Erik Diehn and Peter Wolfgang prepared this case with the assistance of Miranda Chen, Patricia Porto, Kristie Waulthier; all are members of the MBA class of 2008. Professor Costis Maglaras supervised the preparation.

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