Case study

Commercial Analysis

Entertainment, Hospitality

We provided the Finance and Marketing teams with an in-depth understanding of the current state of revenue and customer segmentation in order to inform their strategic planning.


Our client runs two large sports community clubs with multiple entertainment and hospitality venues.


Revenue for our client peaked during the team’s run to the Grand Final then steadily declined over the following 6 months. They needed to investigate the cause of the downturn, and formulate approaches for increasing revenue in the future. The aim of the project was to provide a sound understanding of the current state of revenue in order to inform their strategic planning going forward.


The initial phase of the project involved an exploratory analysis of the disparate data sources collected by our client, including Point of Sale, Gaming, and Visitation systems data. This initial discovery phase assessed the validity of the data, along with planning the next phase of analysis.

After gaining an understanding of the data, there were four main components to the analysis:

  • Lost revenue analysis: Forecast generated a series of subsets and crosstabs of gaming turnover to identify potential trends and establish a baseline for comparison.
  • Promotions analysis: In order to determine the effectiveness of member discounts in generating additional gaming turnover, an analysis was run comparing turnover when members purchased specials to a baseline from before the promotion started.
  • Membership loyalty rewards analysis: Forecast assessed the utility of the loyalty rewards program offered to members, primarily through the reinvestment rate and return on investment of the program.
  • Segmentation: K-Means clustering was run across the gaming data, using a variation on a customer lifetime value method. Recency, frequency, and monetary value were all generated via gaming turnover; with average bet and average session time added to the analysis as well. This was extended by splitting the data by day of week, to account for cyclical patterns in customer behaviour.


Following the analytical review, we delivered a detailed dashboard and report of the current revenue situation, along with potential next steps to enhance the value our client can gain from their data.