Key city tourist destination econometrics BLA GLOBAL 2014


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Some extracts from a recent key city destination marketing mix model. Evidence of long term media effects and integrated synergies.

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Key city tourist destination econometrics BLA GLOBAL 2014

  1. 1. Some extracts from a recent key destination Media Mix Model
  2. 2. Client Situation and Challenges Ticket sales for a major tourist destination had stabilised whilst marketing spend which started pre- launch had continuously edged upwards across a broad mix of channels. The challenge for the client management team was to understand: 1. The extent to which media investments in driving visitors and ROI 2. Media saturation and diminishing returns 3. Long term brand building effects from media spend 4. How to grow ticket sales by optimising spend allocation Objectives Build a predictive econometric model to evaluate the financial ROI of media spend in driving ticket sales for the brand X tourist destination. A secondary objective was to provide guidance on how a reallocation of spend across media channels will help to increase tickets sales and revenue into 2014. Please note: all data points have been altered to preserve client confidentiality
  3. 3. Overall Media contributions Overall, media and marketing have contributed to around 22% of ticket sales revenue. Of this, online paid and owned (website) media have contributed 5%. Offline media channels have jointly contributed to the remaining 5%. Long term media carryover effects are evident accounting for 12%. Baseline sales driven by seasonality, inbound & domestic tourists, city events and consumer confidence. Overall contribution from marketing and media activity Significant long term media effect on ticket sales
  4. 4. Overall Media contributions over time Grand opening Pre-opening marketing and media generated a heightened level of exuberance and a long term effect from media and marketing. Significant long term media effect on sales. Baseline = seasonality, tourist numbers, city events and consumer confidence
  5. 5. Full Media Spend Optimisation – Constant Spend This optimised allocation will lead to a 5.2% increase in ticket sales. This solution suggests cutting back on TV and outdoor and reallocating that same spend on other media channels. Any website related spend should be focused on search optimisation. Annually, this represents approximately 32,166 more ticket sales. At stable prices and economic conditions, this would approximate to £771,973 of additional revenue. £1,639,139 £1,639,139
  6. 6. Guidance on future integrated media execution 43% Using our simulated modelling results we have assessed media interactions and the resultant payoff. This insight provides us with steer into future integrated campaign executions. 49% Outdoor and local Press are most effective when activated together. There is about a +43% synergy or additional lift due to simultaneous activation. Online and Radio are most effective when activated together. There is about a +49% synergy or additional lift due to simultaneous activation.
  7. 7. Modelling Accuracy and Forecast Validation Model accuracy is measured by R2 – this is measure of the variation in actual sales that is explained by the modelled series in Red.(pooled) Our final econometrics model has produced a very accurate representation of actual historic ticket sales. We held out 10% of the data to test for forecast validation which is also very high. Overall Model Accuracy is 98% Model Forecast Validation Accuracy is 97%
  8. 8. Appendix 1: Consumer Confidence and Ticket Sales This is a statistically significant improvement in the confidence metric between April 2013 and Aug 2013. Slight drop into Q4 2013, but up in 2014
  9. 9. Michael Wolfe CEO Bottom Line Analytics Global E: M: 770.485.0270 Masood Akhtar Partner, Analytics (EMEA) Bottom Line Analytics Global E: M: +44 7970 789 663