NY Jets Show How To Leverage Non-Endemic Influencers To Drive Fan Engagement

BY ADAM GROSSMAN

Sports properties (typically leagues, teams, events, and / or athletes) often ask how they can attract non-endemic companies as corporate partners. One question they do not often ask is how sports properties can partner with non-endemic (or not directly related) influencers to better reach their own target audiences.

While the problems appear dissimilar on the surface, there is a common answer to both questions. During the 2019 season, the New York Jets created and implemented a strategy to work with non-endemic influencers that maximized reach, targeted new and existing fans, and created organic content that maximized audience engagement.

John Wall Street of Sports Illustrated highlighted the Jets’ success in a post earlier this week. The Jets started by finding non-endemic influencers that shared the same audience demographics as the team’s fans. The Jets recognized that many of these influencers can reach a large and different audience than the team could on its own. However, the Jets needed to ensure that this new audience was the right audience for its specific goals. Therefore, working with non-endemic influencers’ followers that shared similar demographics as the Jets’ current fans meant that team was maximized its probability of success.

The Jets also recognized that non-endemic influencers frequently generated the highest engagement with organic content. The team created unique, gameday experiences for each influencer that resonated with their interests that included pre-game festivities and sideline passes. Senior director, content marketing and strategy, Jessica Ciccone said that Jets’ social media impressions reached a season high because Method Man and the Wu Tang clan posted about their experiences on their own volition during a game with the NY Giants in November.

It can appear to be easy to say that finding non-endemic influencers that share the same demographics and interests of a fan base is something all sports properties should consider. The challenge comes from determining how sports properties find these non-endemic influencers in the first place in a similar way to the Jets.

B6A’s Audience Inference Platform (AIP) and Influencer Analysis Platform (IAP) enables properties (and corporate partners) to address this challenge. AIP platform leverages B6A’s natural language processing (NLP) and proprietary algorithms capabilities to examine the conversation by an influencer’s followers. This enables us to determine who people are (demographics) and what people are interested in (psychographics) based on what followers say in their posts.

AIP enables properties and partners to both better understand their own and virtually any non-endemic audiences. This is critical because it is not always clear which non-endemic influencer is the right fit specifically because they are non-endemic to a property or partner. Therefore, they should examine as large a universe of potential non-endemic influencers as possible to find the ones that can best help engage with new and existing fans or customers. Leveraging machine learning, such as the AIP, to accomplish this goal at speed and at scale is absolutely critical.

B6A’s IAP then enables our clients to track current and potential non-endemic influencer partnerships once again by leveraging NLP. More specifically, B6A can examined owned and earned conversation generated from campaigns or content created by non-endemic influencers for sentiment, engagement, awareness, and value. We can then track how lifts in these metrics translate to lifts in specific revenue and brand goals for a property or partner using our Corporate Asset Valuation (CAV) model.

The Jets provide a good benchmark for how properties and partners can potentially develop new relationships with non-endemic partners. This strategy can, and likely will, be replicated by industry leaders. Leveraging machine learning tools, such as the ones B6A provides, is critical to implementing this approach effectively.