Predictive analytics reveal valuable insights regarding consumer behavioral patterns. The data acquired can be the basis for business decisions moving forward. More companies are also turning to predictive analytics to boost event turnout. We’ll show how some of the top corporations of the world are using big data to increase ticket sales and attendee satisfaction.
Predictive Analytics in the Sports Industry
Predictive analytics is now used in various industries, including professional sports leagues. The Houston Astros, for instance, used its analytics to boost ticket sales after turnout for one of its games failed to reach projected numbers. Data was gathered through surveys, and it was determined that turnout was subpar due to many fans being unaware of a scheduled post-game fireworks show. The analytics revealed deficiencies in the team’s marketing department, and the issue was promptly corrected.
The Cleveland Indians had a similar predictive analytics plan in place, taking advantage of big data to determine different ticket offerings. Data from fan surveys also led the team to create a Kid’s Clubhouse, a family-friendly membership program that provided exclusive access to entertainment events.
You can read more about the strategies implemented by the Astros and Indians here.
Predictive Analytics Best Practices
The strategies used by sports teams can be adopted by various other industries for elevating their own ticket sales. Various sports teams routinely study big data to make decisions regarding individual game and season ticket sales. Data can be studied by establishing multiple metrics and key performance indicators. Ticket sales, for instance, can be measured based on factors like:
- Time of week
- Team ranking
- Promotional giveaways
- the opponent the team is matched against
- whether the team won or lost the last game
Non-sport industries can use many of the same metrics above or tweak it to make it fit their field.
Understand Your Demographic More Deeply
Big data allows companies to get to know their demographic at a deeper level. Data can be collected from a number of sources, including email responses, social media activity, and buying patterns. Furthermore, companies can also learn a thing or two about the people the buyers are buying a ticket for if not for themselves. With new beacon technology, companies can even gleam some information about the seated attendees. It can be determined for example, whether the attendee seated in row 4 aisle B is a ticket purchaser or the guest of a buyer.
It doesn’t end there. Companies can also gauge consumer behavior. Perhaps you can track the consumer interaction with sponsors to determine which sponsor product or brand is eliciting the most engagement. Share the data with the companies funding your event to help them raise their own ROI. That, right there, is good buddy-buddy behavior that keeps sponsors on board for the long-term.
The offerings and freebies provided on an event app not only increases attendee engagement but also provides valuable data in the process. What can be included in an event app that also doubles as big data? Consider push notifications with customized content, such as:
- special offers for products promoted at the event
- in-seat concession orders
- mid-event surveys
- discount ticket prices for the next event
- instant live guest services
The activity on the app provides further data that can influence decisions for future events. If a particular product received a lot of pre-orders at the last event, for example, then that product or similar ones can receive extra promotion for the next event.
There is a famous saying in business that 80% of business comes from 20% of customers. That 20% are repeat consumers and event attendees who consistently turn to your company over the competitors. What are you doing to retain and expand that loyal customer base? You can acquire data about your current repeat customers. Sports teams, for example, often measure the ratio of one-time ticket buyers vs. frequent season ticket buyers. Metrics to consider include:
- Event attendee rate of customers with a loyalty membership
- Average in-event spending rate of loyalty program members vs non-members
- Average number of guests loyalty members bring vs non-loyal members
The behavioral patterns of loyal members can determine future decisions. Perhaps the attendee rate of loyalty program members, for example, aren’t as high as projected. This can be remedied a number of ways, such as providing a special discount, early bird, or free VIP upgrade as part of the loyalty membership package. These offerings in themselves also serve as yet another form of metrics.
Predictive analytics go beyond raw ticket sale numbers. With big data, you have so much information at your disposal that enables you to know your consumers from the inside out. When you know your audience, you can cater to them in a way that elicits a response.
This is a guest post by Dan McCarthy, Event Manager at JD Parties, an event management company based in the UK. Dan has five years of event project management under his belt. He has worked on many successful events, and currently he shares his knowledge by writing on the company blog. Follow him on Twitter @DanCarthy2.