Measuring the success of sport sponsorship has often been difficult for a sponsor. This research took the first steps in identifying a new sponsorship effectiveness measurement technique based on social media data. The results are based on collecting the most recent 50,000 Twitter followers of each professional sports team that has a sponsor with naming rights. Depending on the size of the sponsor, up to 50,000 followers were also collected from each of these sponsors. The mutual followers between the team and the sponsor were then used as a measure of customers gained through the sponsorship. Using mutual Twitter followers as a measure of success, we are then able to look at how social media data either coincides or differs from traditional means of measuring sponsorship success.
A linear regression was then run to find the largest indicators of sponsor success. The dependent variable, and degree of success, is the percentage increase in followers between the sponsor's followers that also follow the league's Twitter account and the sponsor's followers that also follow the team's Twitter account. The league followers act as a baseline of all fans of each league with which we can compare the success of each team. A higher percentage increase would indicate that being a fan of the team contributes to a higher following of the title sponsor. The independent variables used are sponsor distance from the stadium, sponsor category or industry, and sponsor size. An additional regression was performed to include the results across all professional sports teams in the United States to also test if the league is an indicator of sponsor success. The top teams have the largest percentage increase between the league's followers and the team's followers that are also followers are the sponsor's Twitter account.
About the Author
Moriah Stice is a senior at Samford University with a Mathematics and Economics double major and a Computer Science minor. She is primarily interested in using her quantitative education to find efficient solutions through the use of data analysis. You can learn more about Moriah at https://www.linkedin.com/in/moriah-stice-05b553141/
