Want to understand the price sensitivity of your customers and improve the odds of making the right pricing decisions before you go on sale? We used conjoint analysis to set subscription and single ticket prices at the Lyric Opera of Chicago…
When setting prices for events, one question that keeps recurring is: what would our potential audience be prepared to pay for event X? And the answer as always is: “it depends”.
Price elasticity is the measure of the change in demand for a product after a change in the price of that product. So if you can calculate price elasticity then you have a sure-fire way of knowing what you can charge. Without this the danger is that either you set prices too high and lose demand, or you reduce prices below what people would be willing to pay and lose income which isn’t replaced by an increased volume of ticket sales. In order to really understand what people are prepared to pay for an event you have two options. One option is just to set a price and see what happens. But if you want to optimise your pricing in advance, you can predict demand using a research technique called conjoint analysis.
To ascertain what someone is prepared to pay for event X, you firstly have to take into account the other elements that are influencing their perceptions of value. This might include factors such as day of week, ticket type, seat location, production type, competing events and the customer’s knowledge or frequency of attendance.
Once this context is understood, it is possible to start asking about price. Researching price directly is difficult. Firstly, people know why you’re asking and so tend to deliberately understate their willingness to pay. Secondly, you have to be very specific about the offer to get an accurate response. This is where using conjoint analysis helps. Instead of simply asking “what you are prepared to pay for an event?”, conjoint poses the question differently. It asks people to make a decision based on a number of options and then uses trade-off analysis to calculate the value of each element of the potential product on offer. This allows you to piece together different elements to calculate overall price sensitivity for various combinations.
Conjoint analysis allows you to:
- Improve the odds of making the right pricing decision before going to market
- Determine preferences for products based on trade-offs
- Understand the relative attractiveness of different product components
- Calculate the overall price sensitivity of products
- Segment the market (see Membership)
- Predict customer choice allowing you to see what combination of prices are right for you
Using conjoint analysis to set prices at Lyric Opera of Chicago
At the start of 2016, working in partnership with JCA Arts Marketing, Baker Richards undertook a project with Lyric Opera of Chicago with the aim of informing both single ticket and subscription pricing for their 2017-18 season. Multiple conjoint analysis surveys were designed to test price demand for single tickets, choose-your-own subscriptions and fixed series subscriptions in different parts of their auditorium for a range of different operas and time slots.
Single Ticket Results
The single ticket survey was designed to test price demand for five opera titles to represent the wide range of repertoire Lyric offers within a year, ranging from the very popular, such as La Bohème, to the obscure, e.g. King Roger with Falstaff, Queen of Spades and Peter Grimes falling somewhere in between. These titles could then be used as proxies for future seasons. We also offered five different seats in the auditorium to reflect the most desirable to the least desirable. Finally, we tested a range of additional prices (both higher and lower than the current prices).
- Title was the biggest driver of demand.
- Demand for La Bohème was twice as strong as Falstaff, Queen of Spades and Peter Grimes and three times as strong as King Roger.
- Reducing prices for the most obscure repertoire did not drive sufficient additional demand to offset the income lost as a result of the reduction in price.
- Raising prices in the least attractive areas significantly increased income without a substantial loss in sales, especially for popular repertoire.
- Higher prices for the least attractive areas makes the most attractive areas even more desirable and more likely to sell-out. Reducing prices in these areas makes the higher priced areas less attractive and does not generate additional volume.
- The research demonstrated how far prices could be raised in each area for each title and the resulting change in demand. This information gave indications of how far prices could be increased through dynamic pricing before demand dropped.
Combining the findings from the three surveys gave Lyric the ability to re-think their pricing strategy: this included setting fixed series subscription pricing independently of single ticket prices (due to different patterns of demand); moving away from pricing by day of week to a structure that allowed more flexibility in pricing (and more performances of the most popular titles); and using price to encourage customers into certain parts of the house.