Business Objective

• A sports team wanted to identify and prioritize fan segments that were ripe for business-building opportunities. To do so, they needed to understand what motivated the fan base to attend games so that attitudinal segments could be developed.
• At the time, the sports team only had a ticket-based segmentation of the fan base. These segments were limited to frequency of game attendance and age-based profiling.

The Challenge

• They wanted to understand what motivated loyal fans to attend live events despite the team’s inability to maintain a winning record.

Our Approach

• Schmidt’s advanced analytics experts managed the segmentation process, leveraging the team’s 3,500-member Fan Insight Community to run both qualitative and quantitative aspects of the project. This approach allowed for an accelerated timeline. The work was delivered within a 2-month period, outpacing the typical 4-5-month timeframe usually required for this type of project.
• Schmidt’s approach took client budget sensitivity into account. By utilizing the Fan Insight Community and leveraging the client’s own research team on qualitative aspects of the project, our team was able to deliver the project at nearly half the cost of what might have been expected utilizing research sample from the market.

Business Objective

• To grow revenue, a popular entertainment venue knew it would need to attract new customer segments and increase visits among existing customers.

The Challenge

• The client didn’t have an extensive customer list or rich customer database to leverage for customer research.
• Without a CRM database, the client was unable to enrich the attitudinal segments created via custom research with demographic, media consumption, and behavioral metrics by appending the data.

Our Approach

• Schmidt enlisted the help of a market sample panel partner that not only offered qualified respondents, but these respondents were already part of Acxiom—the leading third-party targeting database. These respondents were enriched with data profiling variables related to their entertainment behaviors and demographics.
• Leveraging an advanced analytical segmentation approach, Schmidt developed segment profiles based on economic value and interest in entertainment types.
• Media consumption, entertainment habits, and other variables were then appended to enrich the learning and provide for accurate media targeting.