Thought Leadership
8 minutes

Estimated read time: 6 minutes, 24 seconds

Artificial intelligence is transforming the ticketing industry. Whether by using machine learning, deep learning, natural language processing, or another section of the AI umbrella, there are many applications for this technology within the ticketing industry.

From marketing and sales to predictions and fan engagement, AI automates systems and can analyze the billions of data created every day. AI can also help ticketing organizations navigate the "current normal" and win back patron confidence by allowing for touchless transactions and improved customer support.

The following ranges from systems currently used to ideas that have yet to mature. The power of emerging technologies should not be ignored, but neither should the obstacles to reaching those end products.

Here are five ways artificial intelligence is transforming the ticketing industry.

ai ticketing

Dynamic Pricing

Artificial intelligence is helping ticketing services find the right pricing strategy for the right situation.

Dynamic pricing has been the norm for most of human history. It allows businesses to match their prices to their needs, whether selling out the house for the highest profit achievable or lowering prices to fill the venue to ensure revenue.  

By including as many influences as possible, such as presale, ongoing sales results, news about the artist, and search request trends, an artificial intelligence system synthesizes data to supply recommendations on best pricing.

A real-world example of an AI-powered dynamic pricing platform is Remi, which uses machine learning and historical data to create proactive prices for businesses.

By recognizing patterns in large datasets that would take an intense amount of time for humans to find, machines can more quickly present a desired output that can best inform pricing.

Cross-sale/Up-sale Recommendations

Investing in personalization to build customer relationships and create a better experience can pay off well. Personalization can persuade an existing customer base to spend more on related goods and services through cross-sale and up-sale recommendations. According to recent data, 91% of consumers are more likely to shop with brands that supply offers and recommendations that are relevant to them.1

Boost Upsell is an example of cross-selling/up-selling powered by artificial intelligence. The tool supplies additional options and upgrades to a consumer when completing a purchase. 

An artificial intelligence system picks the recommendations by selecting products relevant to those in the purchaser’s online cart, encouraging impulse buying. The service claims to increase sales by 250%.2

With customer data, organizations can pair traditional cross-sell models with artificial intelligence to understand future customer behavior and choose channels in which to engage them. Eighty-three percent of consumers are willing to share their information to create a more personalized experience.3

Event organizers and ticket vendors can build nuanced customer profiles by combining information such as historical data of past event attendance, responses to post-event surveys, or even information as simple as providing an email to a website but not making a purchase, and match those profiles with future events and other offers.

Attendance Forecast

Selling a ticket does not end with the purchase. Artificial intelligence can help event organizers better understand where their patrons are in the patron journey, even helping to predict and mitigate no‑show trends down to the seat.

Seatcycle is a real-world example of this AI use case. With historical data and trends, artificial intelligence systems can predict the who, where, and when that might affect how full a venue may look for different performances. This is especially important during a show recording or ensuring that entertainers are confident a venue is beneficial for them.

Beyond predictive analytics, Seatcycle offers a chat function that allows event organizers to gauge the possibility of a patron’s attendance; sometimes, all it takes is an automated reminder an event is coming up. Ticket holders can even be incentivized to share their status, and if they need to return the ticket, vendors can offer a refund or a donation.

AI can also forecast how patrons may arrive at the venue, both by arrival over time and through different entrances to help adjust queue processing. This information can also help with procurement planning for stocking categories such as merchandise, food, and beverage.

Combining this with a technology like geofencing can provide another layer of direction, future event advertisement, and invite patron feedback to understand and address potential pain points.

Facial Recognition

Access control has already been improved by different digital methods, evolving from scanning paper tickets to using a patron’s phone to today’s contactless ticketing option. But facial recognition could make any kind of ticket unnecessary as patrons are checked in with a simple face scan.

Modern facial recognition solutions currently available on the market offer up to 99% accuracy.4 In addition to faster queue processing, another benefit of facial recognition is identifying persons not allowed to be in certain areas of the venue, such as staff only or VIP.

However, there are a few disadvantages to this facet of AI:

  • May need more steps in the ticket purchase process to capture the customer’s face and its patterns (i.e., different expressions).
  • Customers may not be willing to opt-in to facial recognition, requiring a fallback option or system.
  • May need more hardware and/or software during the check-in process.

Another question that goes with facial recognition is, is this technology invasive? It is easy to run a Google search on facial recognition and turn up many articles about alleged surveillance, police misuse, and a marketplace for items that block the technology.

Ticketing organizations may want to consider if the value of this technology outweighs the obstacles involved in making customers feel safe handing over this biometric information.


The conventional chatbot is a dime a dozen, popping up on websites all over the internet. And yet they have fallen short of the lofty expectations we have set for them, sometimes leading to a frustrating experience for customers.

Only 9% of customers felt that they would be best served by a chatbot for serious inquiries, with instead 80% preferring a voice call with a human being.5

Today’s current chatbot must evolve to supply the value expected of them. With rapid improvements in natural language processing (NLP),  voice bots could help with customer support, assist those with disabilities to complete a ticket purchase, or be integrated into physical ticket‑selling kiosks. 

Some examples of voice bots include Alexa, Siri, and Google Home, which you might already own. These bots can integrate with different services and make performing web searches or ordering from online marketplaces a breeze. And they can be combined with voice authentication, which has the potential to provide better security and customer service. 

This is especially important considering the pandemic, which has overwhelmed contact centers. With an emphasis on live interaction, intelligent chatbots that understand sentiment can handle simple inquiries while streamlining complex questions to a customer service representative. Sentiment analysis is the next evolution for NLP and will aid in the evolution of the chatbot.

As for disadvantages, in my opinion, the adoption of this technology requires a significant amount of time and resources to set up, maintain, and improve. Maybe in the years to come, it will evolve to be more easily adoptable.


While AI makes many think about the USS Enterprise’s computer, it is very real and often used in our day-to-day lives. It’s already being used in the ticketing industry, and is making it easier for ticketing organizations to match events to patrons.

The above areas are just a few implementations of AI within the ticketing domain. By 2024, worldwide spending on artificial intelligence is expected to reach $40.6 billion, so who knows what new use cases and proofs of concept we could see in the future.6

With the right application of research and development, anything is possible.


1,3 Personalization Pulse Check. (2018). 
2 Boost Upsell: Skyrocket Your Order Value and Sales with Smart Upselling. (n.d.).
4 Facial recognition: Top 7 trends (tech, vendors, markets, use cases and latest news). (n.d.). 
5 Cantor, B. (2018, October 17). Special Report: The State of Chatbots
6 Artificial Intelligence for Business 2016 Archives. (n.d.). 

Lyubomyr Nykyforuk
Lyubomyr Nykyforuk
Head of Solution Creation department, Ticketing Program Manager