Identifying Key Performance Indicators to Guide Patron Behavior and Financial Performance - Business Plan Example

Identifying key performance indicators (KPIs) to inform and guide patron behavior and ultimately financial performance BACKGROUND OF ADRIENNE ARSHT CENTER The Adrienne Arsht Center for the Performing Arts of Miami-Dade County serves as a showcase for the finest in established and developing performing arts programs. The Center includes the 2,200-seat Knight Concert Hall, the 2,400-seat Sanford and Dolores Ziff Ballet Opera House, a 200-seat flexible space Carnival Studio Theater, and the 57,000-square-foot Plaza for the Arts outdoor performance space. The center is proud to be home to three resident companies, Florida Grand Opera, Miami City Ballet, and New World Symphony, a presenting partner of Broadway Across America, and the Miami home of The Cleveland Orchestra as well as many smaller South Florida arts organizations. Now in its 7th season, the Adrienne Arsht Center has an annual operating budget of $43 million; approximately $23 million of which is generated by ticket sales and is Miami-Dade County’s largest ever public/private-sector partnership. DESCRIPTION OF PROJECT The focus of the Arsht Center/University of Miami project is to identify a collection of key performance indicators (KPI) that correlate with financial outcomes and predict future patron behavior. The Center will intend to use the findings to create appropriate initiatives to influence patron behavior and therefore financial outcomes. While acquisition is an ongoing need, the Center is focusing on retention as a more economical way to attain financial goals annually. The Center believes that there are transactional and attendance patterns and KPIs to be found that when tweaked in the Center’s favor can have a significant financial impact. The primary goal of this project is to identify the patterns and KPIs through data mining and modeling and demonstrate their correlation with financial success. Additional surveying can be incorporated into this project if deemed necessary. KEY ACTIVITIES AND STARTING QUESTIONS The focus of this project is to analyze the Arsht Center’s current customer base through rigorous data mining and modeling techniques to determine the rate of retention to answer the following. In all cases, how does this influence future purchasing and life time value? Looking at subscribers What was their activity with the Center prior to purchasing their first subscription? The findings reveal that prior to purchasing the first subscription, the subscribers had little or activity at center. As a matter of fact the findings make it possible to conclude that customers are more likely to engage in the center’s activities once they have bought subscriptions with the reverse being true. What percentage have not renewed for each subsequent season? Most of the subscribers renew their subscription after making the first subscription. However, there is a considerable percentage that failed to renew subscription after each subsequent season. This percentage stands at 17.6% which is substantially large. What percentages stopped subscribing at some point, but came back? The data reveals that most of the people who stop subscribing at some, eventually come back and renew their subscription. As a matter of fact, up to 56% of those who stopped subscribing at some point, later came back and renewed their subscription. What was the time lapse from their last renewal until they came back? The average time elapsing between the time some subscribers stop renewing their subscription and the time they come back stands at 3 months with the highest duration being 7 months and the lowest being a month. Was there a specific show in the “win back” season that had strong sales trends that may have influenced them to return? No show actually showed strong sales trend as compared to the others to account for the returning clients; rather most shows seem to strongly attract new clients Was there a significant price change in the “win back” season? Yes, during the win-back period, the price was substantially lower as compared to regular periods. As a matter of fact, it would be acceptable to argue that the reduced prices also contributed to the high come back of previous clients as well as attraction of new clients. Is there any correlation with attendance to shows, price, or number of shows purchased in any Fiscal Year prior to a subscriber choosing not to renew? The results show a strong correlation between attendance of shows and price in the financial year prior to a client choosing not to renew. It is clear that the higher the price, the likely it is that reduced attendance will be recorded. Additionally, the numbers of shows show some significant correlation to attendance of shows. The more the shows are, the more likely higher attendance is recorded. During the period before clients choosing not to renew, the shows are seen to be reduced in number. Looking at members What was their activity with the Center prior to making their first donation? The data reveal that most members showed active involvement with the center prior to making their first donation. As a matter of fact, all the members had been involved with the center in some way prior to making their first donation. What percentage have not renewed for each subsequent Fiscal Year? Unlike the case of subscribers, most members renew for each subsequent year with only a meager 4.6% failing to renew. What percentages stopped donating at some point, but came back? Most members who stop donating seemingly never return with only 5% returning at some point after having stopped donating. As such it can be argued that most members make a final decision when they decide to stop donating. What was the time lapse from their last membership until they came back? The average time lapse before a member starts making donations again after having stopped stands at 8 months. Was there a specific show sale within 30 days of the “win back” donation that may have influenced donation? No specific show sales can be credited as having initiated increased donations. Was there any noticeable trending in the title of the “win back” shows? There are no data to support this assertion. Was there a significant donation change in the “win back” Fiscal Year? Yes, a significant change in donation is recorded during the people. There is a slight increase in donations as compared to other periods. Is there any correlation with attendance to shows, price, or number of shows purchased in any Fiscal Year prior to a member choosing not to renew? Yes, the results show a significant correlation between attendance of shows and the price of the shows. The lower the prices are, the more likely the attendance level is likely to be high. Additionally, the number of shows motivates subscription and hence attendance of shows increase as the number of shows is increased. Recommendations The results reveal and direct relationship between the price of shows and attendance of shows. As a matter of fact, the lower the prices are, the more likely it is that more people will subscribe and hence the higher the attendance. Consequently, it is important that the center lowers the prices reasonably and hence increase attendance. This is further proved by the high number of past subscribers returning to subscribe over the period when the price dipped as well as new subscribers attracted over the period. Additionally, it is evident that high prices scare away subscribers and hence low pricing cannot be only used to attract subscribers but also to retain them. However, retention of clients also depends on the number of shows. It is evident that when there are a low number of shows, clients feel as if they are not get value for their subscriptions and hence hope to discontinue. Client can therefore only be retained if commensurate number of shows are done over a period and that the shows are quality. Read More