Monday, July 23, 2018


Analytics permeate the business world across every industry. Everyday companies employ analytics to increase profitability. Starting with defining the business problem, the stages of an analytical project typically then include data preparation, resource allocation, analysis, results, and implementation. Data sources for analytics are varied and numerous. Survey data, customer data, operational data, financial data, third-party data are all candidates for analytics. Analytics help an organization to link seemingly unrelated data in search for patterns and knowledge. Results produced from analyticsPhotoxpress_4761063 can help an organization to become more proactive and precise with marketing efforts. Research projects can also be designed with specific analytics in mind, as is often the case for customer segmentation research.

Thorotrends' analytical capabilities include techniques such as...

  • Correlation/Regression (for Key Driver Analysis, Derived Importance, Predictive Modeling)
  • Cluster Analysis (for Segmentation)
  • Conjoint Analysis (for Choice/Preference Modeling and Pricing Insights)
  • Factor Analysis (for Data Reduction)

These and other analytic techniques can help to distill knowledge from new or existing data collections. Thorotrends will always advocate a thorough inventory of existing data sources before recommending primary research, especially in organizations that wish to employ analytics for the first time.

A specific challenge facing the Thoroughbred racing industry is that a key form of customer data (i.e., pari-mutuel activity) is not typically captured at the individual level, especially for high-value on-track customers. Although there are exceptions to this in the case of loyalty programs and advance deposit wagering systems that lend themselves to database marketing, by and large racetrack operators do not know who their customers are and how much they spend. This challenge can be met in the near term with primary research (surveys) which can pave the way to utilize customer behavior and opinion data in analytics.