First Order Controls and Fine Tuning In Pricing

I have only been to a handful of major league baseball games. Every time I went,  someone else was paying for it.  But for every seat that was occupied in the stadium there was someone who paid for it, be it purchased individually or as a bundle. Every seat in the stadium whether or not occupied has an expected value for its profit. The profit comes from the price paid for the ticket and additional margin from what the fan spends in the stadium.

The notion of expected value means there is a probability associated with whether or not a given seat will be sold. In fact it is not a single value, it is a probability distribution for different price points. The distribution is not only different for different teams but also is  different for  different opponents, different game in the season, weather etc.  Even more complicated is the fact the probability distribution is dynamic for the same game, it changes from the time the game schedule is announced to just before the Umpire calls  Play Ball. After that the expected value falls to zero, at lest after first two innings.

But most if not all ballparks do not go to this level of pricing. They practice multi-version pricing, but pricing is static or fixed. That is not true however for the secondary market where the price fluctuates and is determined by customer’s willingness to pay. One company is making it easier for ballparks and other event managers with limited capacity that is not inventoriable (that is it expires after certain period). That company is, QCue,

Qcue is the world’s only dynamic pricing engine for live entertainment events. Using a scientific approach to pricing, Qcue combines computational analysis and external data sources to allow organizations to adjust pricing multiple times per day.

Solutions like the one from QCue break down the barriers to adopting complex probabilistic models and multiple regression based predictive models in pricing. But I still want to point out that application of analytics in pricing is still a fine-tuning knob, the one you employ after you have achieved larger first order control.

The  first order controls involve the basic tenets of marketing – segmentation and targeting. Marketing strategy is about understanding the different customer segments, the value to the different segments and producing multiple versions that add value to them at price points that maximize your profit. If your first order controls are not correct or optimized, any additional benefit you achieve through other optimization scheme will only result in sub-optimal profits.

You stand to gain lot more profit from analytics engines like QCue, but only if your marketing strategy is correct to start with.

One thought on “First Order Controls and Fine Tuning In Pricing

Comments are closed.