Stellar Play: Data Assessment

What you need

Data and Integrations

A single data integration is all that’s required, though this Play scales very well with additional integrations.

• Ticketing data

For added value, include multiple data integrations, such as:

• Email
• CRM
• Merchandise
• Food and beverage

StellarAlgo Tools

• Fan Universe Dashboard
• Segment Builder

When to run this Play

The Data Assessment Play can be executed on an annual or one-off basis. It will typically be most useful to you when:

• Onboarding into the StellarAlgo Platform
• Determining data append requirements
• Informing fan segmentation strategies
• Evaluating the effectiveness of data capture strategies

At a minimum, we recommend conducting the Data Assessment Play on an annual basis during the post-season or off-season.

Scope and effort required

The StellarAlgo Platform makes it easy for you to execute the Data Assessment Play quickly and with low effort.

A single analysis will take less than one week.

Strategy Sequence

1. Opportunity Identification

Opportunity identification is where you will assess whether undertaking the strategy outlined in this Play is a worthwhile investment of your time and resources. The Data Assessment Play spans your entire fan universe and is an opportunity to better inform the rest of your seasonal strategies – this Play drives high value with relatively little input required.

A rich fan data asset bridges the gap separating ambitious fan strategies and what is supported by your fan data, such as:

• Strategic fan universe growth
• Elevated segmentation and personalization
• Attract data-driven sponsors and corporate partners

In the Opportunity Identification phase, identify what fan segmentation strategies your team would like to run during the season, if this information is already available to you. You can then focus on segments of fans or defining characteristics to determine whether your fan data can in fact support these segmentation strategies.

2. Baseline

Match rates is the key metric in the Data Assessment. In the Baseline phase, you will focus on determining data match rates for your entire fan universe. You can then use this baseline compare data match rates of specific sub-segments of your fan universe against.

Identify the match rates for your overall fan universe – in the Fan Universe Dashboard, your match rates are automatically and conveniently displayed for you. Select the data type of interest in the Fan Universe Dashboard to view the match rate (e.g., age, gender, in-market, etc.).

3. Plan

The planning stage is where you identify what segments of fans within your fan universe you want to identify data match rates for.

We recommend investigating segments of fans that are of interest across the various departments within your organization. Often, we see partners investigate data match rates based on the products their fans are buying (e.g., full season buyers, half-season buyers, group buyers, single game buyers, etc.). The results of the Data Assessment Play can then be served to the appropriate departments to assist them in informing your segmentation strategies for the season.

The complete, unlocked Play provides StellarAlgo partners with a checklist of activities mapped to each part of the season to help you plan ahead and execute successfully.

4. Execute

In this stage, you will leverage the Segment Builder to calculate your match rates for the specific segments of fans that you identified in the Planning stage.

Identify the match rates for specific segments of fans:

• In the Segment Builder, first add the appropriate filters to identify your fan segment of interest
• Then add the area of interest; set the filter to include the entire range of possible values or all value types
• Record the count of fans captured in each data type. Remember to clear the filter after recording the fan count for each data type

The complete, unlocked Play provides StellarAlgo partners with Platform-specific details to empower you to execute successfully.

5. Measure

Calculate your match rates for each data type of interest. Divide the count of fans by the total number of fans in the segment and multiply by 100%.

6. Results Capture

Once match rates have been calculated, strengths and deficiencies of the data should be identified and captured.

Some suggested criteria to help with assessing your match rates include:

• Data types with high match rates (~80% or higher)
• Data types with low match rates (~10% or lower)
• Data types above industry trends average
• Data types below industry trends average

For the specific segments you investigated, compare the data match rates for those segments against your overall fan universe to identify where match rates are above or below your fan universe average.

The complete, unlocked Play provides StellarAlgo partners with additional data and strategies to enhance your data match rates.