Out-of-the-box Approach For Analysis
An NBA team ran short-flighted campaigns to promote games throughout the season with a goal to sell tickets. In the past seasons, the team had run the broadcast campaign near the end of the digital campaign for most of Peak Games and engaged RADaR to find out if this approach was working.
RADaR was tasked to find out if running broadcast near the end of digital campaigns for Peak Games had a positive correlation to ticket sales.
The client asked RADaR to analyze:
• Impact of broadcast on sales
• Overall ticket sales analysis (channel, vendor, campaign)
• Identify trends/patterns
RADaR took the analysis further to include:
• How was the boost in sales impacted by the exact method the broadcast was deployed?
• What other outside factors could be used to predict customers’ interests/actions?
Our custom analysis approach included:
• We broke down into two groups: one with Broadcast and one without.
• Under group with Broadcast: we compared sales revenue from the initial flight (no broadcast yet) with revenue from the remaining flight (with broadcast)
• Under group without any Broadcast: we compared sales revenue from initial flight vs. the last 3 days of flight (i.e. 3 days before the game day)
The results showed that sales revenue tends to increase when game day comes closer whether we run broadcast or not.
• Outside factors, such as the actual performance of the team had a major impact
• There is a strong correlation between point difference and sales <= scatter plot on the left
• If there is a hot game (with superstars for example), ticket sales are still good even if the team was not performing well (dip in the point difference) <= line chart