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Ipsos Callout Optimizer
Optimizing Callout Messages on Scratch Tickets
Have you ever wondered what the optimal message to include on a Scratch ticket is? Should you focus on the total value of prizes available or on the number of top prizes to be won? Additionally, what combination of callout messages will yield the highest sales or share of sales?
Determining which message will maximize the sales potential on a Scratch ticket’s limited space can be critical for the success of the ticket.
Use Ipsos Callout Optimizer to help select the optimal callout messages for each of the Scratch ticket price points offered.
What Goes Into the Ipsos Callout Optimizer Research Design?
The Ipsos Callout Optimizer research is based on the following principles:
Focus on your target market.
Ipsos' team of Lottery and Gaming researchers work with you to tailor the research to better understand the needs of your players.
Customized and flexible approach.
The research design can include the wide variety of callout messages customized for each price point by you, including but not limited to potential combinations of:
- Top prize amounts
- Number of prizes available within a dollar range
- Number of top prizes available to be won
- The number of winners
- The number of ways to win
Experimental randomization process.
Each respondent does not have to see every possible combination of callouts and price points, nor do all respondents have to evaluate the same choice sets. The model works by identifying patterns in players’ choice behavior using conjoint design.
The Result: Ipsos Callout Optimizer Simulator
The Ipsos Callout Optimizer research results are analyzed and used to develop a Simulator, a powerful tool which allows you to model scenarios and determine the optimal callout messages to include on tickets that will appeal most to your players. All of the elements that went into the
research design are incorporated into the Simulator and the "What If" possibilities are virtually endless! The Simulator can also provide results by subgroup of interest; for example, Scratch player segment, Hispanics, or 18–34 year olds (dependent on sufficient sample size).