Part 1 - When big data meets athlete sponsorship everyone wins.
Big data has been tossed around the marketing and tech world for the better part of the last five years, but it is just now starting to become an invaluable tool to help brands determine their roster of sponsored athletes. To date, sports marketing programs have involved finding the most famous or successful athletes your budget could afford and hope this affiliation would yield some positive influence and, ultimately, sales.
In today’s world, fans have direct access to athletes via social platforms, providing immediate feedback to those who are tracking the reach, engagement and overall earned media value generated from sponsored athletes.
In the first installment of this three-part series, we are going to explore how you can take a data-driven approach to determining which athletes you should invest in and who on your current roster is not delivering.
Before we go to deep into how you determine which athletes you should enlist, let's first touch on the shift that has happened in the last decade for fans. When we wanted to get up and close to our favorite athletes, it mostly happened over a broadcast or a live event. Fans would show up early to catch batting practice or watch their favorite rider turn a few hot laps and then stand in line to get a poster signed. This was about as close as we could get to "knowing" our favorite athletes.
Fast forward to the age of on-demand content, self-publishing and social media where enjoy instant access to athletes with a tap or click. Athletes are also aware that their communities are following along— sometimes with audience sizes that rival some of the largest traditional publishers.
The motive for brands endorsing athletes is still the same as it was a decade ago. However, the ways to evaluate an athlete’s value to the brand have fundamentally changed.