Who decides dynamic ticket pricing?

Dynamic ticket pricing, also known as variable or surge pricing, refers to the practice of using algorithms and big data to adjust ticket prices in real-time based on supply and demand. This allows ticket issuers to increase profitability by setting prices to what the market will bear. But how is it decided when prices should go up or down? There are a few key players involved in making dynamic ticket pricing work.

The ticket issuer

The core entity that enables dynamic pricing is the ticket issuer – this is the company or organization that is actually selling the ticket. The issuer is responsible for choosing whether or not to use dynamic pricing for their tickets and implementing the necessary technology and algorithms. Some major ticket issuers using dynamic pricing include:

• Airlines – For airfare, dynamic pricing has become ubiquitous. Airlines rely heavily on complex algorithms to adjust seat prices frequently.
• Ridesharing platforms like Uber and Lyft use dynamic pricing to surge prices during periods of high demand.
• Sports teams, concerts, and theaters – Many event venues now use dynamic pricing for their ticketing.
• Travel websites like hotels.com and rental car companies use dynamic pricing algorithms.

The ticket issuer is responsible for setting the basic rules and ranges for their dynamic pricing program. They define high and low caps for ticket prices and determine how much freedom the algorithm has to set prices within those bounds based on market data.

Pricing analytics software companies

Most ticket issuers rely on pricing analytics software to handle the implementation of dynamic pricing. There are a number of companies offering solutions that use machine learning and big data sets to analyze market conditions and optimize pricing.

Some of the top pricing analytics providers include:

• Pricefx
• Vistaar
• Competera
• Prisync
• Zilliant
• Marguard
• Navetti
• intelligence

These companies employ data scientists and economists to build algorithms that can analyze past sales data, competitor pricing, and market trends to forecast demand. The software lets ticket issuers input their pricing rules and constraints. Then the algorithms take over pricing from there within those guardrails.

The market

Ultimately, dynamic ticket pricing is driven by the market itself. The algorithms work to continuously adjust pricing based on fluctuations in supply and demand. Some key market factors that impact pricing include:

• Competitors’ pricing – Prices will be adjusted based on how much competitor venues and ticket issuers are charging.
• Current and forecasted demand – The number of tickets being sold and forecasts for future sales drive pricing up or down.
• Date and time of event – Prices fluctuate based on when an event falls on the calendar and time of day.
• Group size – Larger groups booking tickets can trigger price drops to incentivize their business.
• Changes in venue size or capacity – Price will rise or fall as capacity is changed.

In essence, the market governs dynamic pricing through the forces of supply and demand. The algorithms are just optimizing pricing based on these ever-changing market conditions.

How the pricing process works

To summarize the full dynamic pricing process:

1. The ticket issuer first decides to implement dynamic pricing for their inventory.
2. They contract with a pricing analytics software company for their algorithm and dashboard.
3. The ticket issuer inputs their pricing guardrails and rules into the software.
4. The pricing software ingests huge data sets on past sales, market conditions, and competitor data.
5. The machine learning algorithm analyzes all this data to forecast demand and optimize pricing.
6. The algorithm starts automatically adjusting ticket prices within the issuer’s defined parameters.
7. The algorithm continues to alter prices based on changing market conditions and new data.
8. The ticket issuer can monitor pricing via dashboards and adjust their pricing rules and constraints as needed.
9. The cycle repeats continuously as the algorithm works to maximize revenue based on market demand.

So in summary, while the ticket issuer initiates dynamic pricing, third-party software runs the actual pricing algorithms, and the market ultimately drives the fluctuations in pricing based on supply and demand factors.

Pros and cons of dynamic pricing

Dynamic pricing has revolutionized how tickets are sold in many categories. Still, the practice remains controversial with consumers. Here are some key pros and cons:

Potential advantages

• Maximizes revenue for ticket issuers
• Increases flexibility and ability to react to market changes
• Allows issuers to capture more value during peak demand
• Can help issuers sell more tickets during lower demand periods
• Provides insights through data collection

Potential disadvantages

• Can anger customers who feel prices are unfair or opaque
• May disproportionately impact lower income consumers
• Reduces certainty in pricing at time of purchase
• Requires significant investment in analytics technology
• Possibility of algorithmic pricing errors

There are merits to both perspectives. Ultimately, dynamic pricing aims to charge each customer the maximum price they are willing to pay. For customers, this means monitoring for price drops and avoiding last-minute purchases when possible.

Case study: Dynamic pricing in airline industry

Let’s look at a case study of how dynamic pricing works for airfare, where it’s most mature and sophisticated. Airlines were early pioneers of variable pricing in the 1980s. Advances in data and algorithms have increased their proficiency.

For airlines, some key factors that influence automated ticket pricing include:

• Date of travel – Prices fluctuate widely based on day of week and time of year.
• Competitor pricing – Algorithms instantly track and adjust to other airlines’ fares.
• Supply vs. demand – Prices rise when seats are scarce at a given time.
• Days left until departure – Prices usually rise the closer you get to travel.
• Group bookings – Group rates can trigger discounts to incentivize sales.

In the table below we can see an example of how dynamic pricing creates fare fluctuation for the same American Airlines flight over a 2 month period:

As we get closer to departure, prices rise even though it is the same flight. The airline’s yield management system analyzes forecasted demand and competitors’ pricing to determine the optimal fare to charge.

Airlines use massive historical data sets and machine learning to build their pricing algorithms. They know that a Tuesday morning flight will need lower fares to fill seats than a Friday evening flight. The algorithm simply optimizes profitability based on these long-term demand trends.

The future of dynamic pricing

Looking ahead, dynamic pricing will likely expand into more industries. Advances in big data and AI will also allow pricing algorithms to become more sophisticated and granular. Some key trends include:

• Personalized dynamic pricing – Using customer data to segment audiences and customize pricing for individuals.
• Predictive analytics – Algorithms that not just react to demand, but predict future trends.
• Cross-channel pricing – Consistent pricing across web, mobile, in-store, etc.
• Hyper-localized pricing – Adjust prices by city or even specific stores.

As algorithms grow more powerful, dynamic pricing may become less transparent. Regulators will likely need to assess how to ensure fairness. But near-term, dynamic pricing will remain a crucial revenue driver for many businesses in our digital economy.

Conclusion

In summary, dynamic ticket pricing involves complex interactions between the ticket issuer setting the strategy, third-party algorithms crunching market data, and supply-demand dynamics determining real-time optimal prices. It aims to maximize revenue through price discrimination and demand optimization. Dynamic pricing is fast-becoming standard across many ticketed industries. Still, its perceived opacity and fairness remain hotly debated.