Josh and his team built their own, customized enterprise data platform. It's based upon conversational AI (artificial intelligence) with an Alexa integration so that users can actually ask it questions and get detailed answers based upon the reams of data stored within. They quickly identified business intelligence (BI) champions in each business

unitSales,

Ticketing, Finance, Food & Beverage,

etc.that

could help them. With input from these stakeholders, the team built a data warehouse but enhanced it with some non-traditional techniques that added value to how it stores information. It's comprised of dimensions and facts that everyone can intuitively understand. For example, the warehouse stores information about the tickets that fans buy: When do they use them? Do they respond to specific promotions? Several members from the Ticket Office were key in getting this project off the ground.

The new system allows stakeholders to query the system themselves in order to get answers to their questions, so these users are more engaged with the process as opposed to having to submit endless requests to Josh's team for information. When the different Phillies functions can get direct and easy access to a lot of data, it encourages managers to use the data in innovative ways.

Today, the team's real-time enterprise data warehouse stores information from every section, row, and seat ticket dating back to its first game at Citizens Bank Park in 2004. The database includes information from over 20 different business systems, broken down by transaction, section, row, and seat. It contains over 154 million records. Now business intelligence reports/visualizations and analytical applications use these core views as their foundation to produce analytics.

And to be sure users take full advantage of all this information, Josh's team strategically placed large 4K interactive displays throughout the Phillies' executive area, ticket office, meeting spaces, and concessionaire office. These displays offer real-time business intelligence visualizations with access to 17 seasons worth of data. Now these visualizations get integrated into bi-weekly staff meetings. They allow larger groups within the Phillies to interact with all of the data to help with their decision-making processes. The power of Big Data when it's easier to use allows Phillies management to hit a home run with the information that's now at their fingertips.

How the Phillies Measure Success

The team uses a variety of real-time KPIs (key performance indicators) that users can see in a very dynamic and interactive way. These include Ticket Sales, Revenue, Ticket Revenue per Capita, Year-over-Year Sales for every sales channel, and Predicted Sales and Attendance.

The Phillies' new real-time enterprise data warehouse.

Which of these actions enabled by the Phillies' new AI system is an example of one-to-one marketing?

A.

ticket discounts offered to specific customers based on past attendance records

B.

coordinate with team management about the starting lineup

C.

concessions supply ordering in bulk using season long consumption data

D.

calibrate vendor deliveries with expected daily needs

E.

forecast revenues on a game-by-game basis

Which of these metrics would be considered a key performance indicator that signaled the Phillies' new AI system was successful?

A.

improved vendor satisfaction

B.

better employee morale

C.

fewer data entry mistakes

D.

increased ticket sales

E.

lower employee turnover

One of the functions of the Phillies' new AI data system is to

A.

identify unruly ballpark attendees.

B.

conduct emotional analysis.

C.

warehouse data.

D.

mine unstructured data.

E.

conduct facial recognition analysis.

Which of these actions might trigger an individual ticket discount to attend a Phillies game?

A.

the team lineup combined with previous macroanalysis of ticket sales

B.

analysis of traffic patterns combined with someone's physical address

C.

a customer checking on ticket prices for a specific date on the Phillies' website

D.

evaluation of a specific customer's purchases at the last game attended

E.

a fan calling in to the local radio station to discuss the season