Marketing Optimization Modeling

1. Marketing Optimization Modeling Theme Park Case Study

3. Situation The client is a small regional theme park. It�s core marketing budget is modest, about $2.5M and is spread across outdoor, radio and print advertising. Apart from this, there is a special TV advertising effort in November and December to promote the park�s special Holiday Lights program. In the past year, overall attendance has been flat. Theme parks are very seasonal businesses and are significantly impacted by short-term weather patterns. For the past year, the management of the theme park has been concerned about the impact of rising fuel prices. Their main interest is to be able to understand how to leverage their modest marketing budget for re-igniting attendance growth at the park.

4. Outline Model Architecture Decomposition of Attendance Drivers Marketing Variance Analysis Seasonal and Days-of-Week Effects Sensitivity Analyses Media Gate Price Fuel Prices Weather Impact of Promotional Events Marketing Efficiencies: Revenue per Expenditure Marketing Spending Optimization Media Schedule Optimization Attendance Simulation and Forecast Model Validation

6. Decomposition of Theme Park Annual Attendance

7. Decomposition of Theme Park Attendance by Week

8. Marketing Variance Analysis: Drivers of Annual Attendance Trends Oct �06

9. Monthly Seasonal Effects

10. Theme Park �Day of the Week� Effect

11. Theme Park Media Sensitivities

12. Gate Admissions Price and Average Daily Attendance

13. Impact of Auto Fuel Prices on Theme Park Daily Attendance

14. Temperature & Weather Impact on Daily Attendance

15. Impact of Special Events and Holidays on Theme Park Daily Attendance

16. Theme Park Media Revenue per Dollar of Ad Investment

17. Incremental Impact on Attendance from a $100 increase in Media Spending

18. Theme Park Current and Optimal Marketing Investments

19. Theme Park Total Attendance and Returns per Media Investment

20. Optimizing the Media Schedule The next two charts compare current versus an optimized schedule. The optimized schedule places each media, as per the overall mix optimization, in the weeks such that its overall impact on attendance will be maximized. This schedule calls for increases in print, radio and Holiday Lights advertising, and reductions in magazine and outdoor media. The overall effect of this schedule optimization is to place more �weeks-of-execution� for media in a more continuous fashion. Doing so, per the plan outlined, is expected to increase attendance +1.5% with the current and constant dollars.

21. Current Media Schedule

22. Optimized Media Schedule

23. Theme Park: Projecting Results of Optimal Media Spending

24. Conclusions and Recommendations The results of this modeling exercise has enabled us to crystallize some key insights regarding key drivers of the Theme Park business. We learned that the Theme Park�s attendance trends have been flat to stagnant over the past year. While cooler weather, rising fuel and admissions prices were major negative factors, total marketing efforts barely covered these short-falls. We know that temperature and weather has a significant impact on short-term daily attendance and we succeeded in quantifying those effects. We uncovered and quantified a new challenge to the park�s efforts to grow attendance, rising fuel prices. Continued increases in fuel prices are likely to pose a major challenge and risk to growing the park�s attendance. We accurately quantified the regular and recurring seasonal and days-of-the-week effects on park attendance. We learned that the +5% increase in admissions price at the park cost -3.7 percent in foregone attendance. Over the past year, the park�s marketing efforts, while generating greater than break-even revenues of $1.56 per dollar spent, fell short in terms of driving substantial growth in park attendance. With the impact of pricing factored in, the net effect of all media and marketing efforts generated only a +0.3 percent year-over-year impact. That there was a -22% decline in the efficiency of media in terms of revenue per expenditure. A major reason for this decline in efficiency is due to the large reduction in radio advertising. Going forward, our modeling has uncovered a key opportunity for the Theme Park to re-ignite attendance growth and improve overall marketing efficiencies. Our optimized solution calls for a shift in marketing spending by the park Increase investments in print, radio and Holiday Lights TV advertising Reduce spending on outdoor and magazine ads Improve media scheduling by maximizing weeks of activity and minimizing ad hiatus�. In addition, the park should continue and expand past successful efforts through special themed events and promotions By optimizing spending going forward the park can reverse stagnant attendance trends and grow overall attendance by +9.3 percent, all without the requirement of increasing total marketing budgets.

25. Model Validation The insights presented here are only as good as the models produced. To assure the highest level of integrity from this analysis, the following is a summary of our validation efforts. This validation effort is designed to demonstrate the �predictive ability� of these models. In order to demonstrate and validate this validity, we withheld 15% of the data observations completely from the models. We then compared how well our models predict actual performance across these unknown data points. The results of this exercise are shown on the following chart. In all cases, our holdout forecasts showed high predictive capabilities and were well within tolerances so we can conclude that these models are all robust and highly predictive.

26. Actual v. Model Fit

27. Contact Michael Wolfe, President Bottom-Line Analytics LLC 404.841.1620 MJW@bottomlineanalytics.com www.bottomlineanalytics.com