Study confirms that BIPOC influencers have to work twice as hard for less money.

MLS, an advertising and PR company, recently did a study to determine whether a disparity existed between BIPOC influencers and their white counterparts.

MSL conducted this research project from October 2022 to March 2023, using a multi-platform approach, including expert interviews of 550 U.S. influencers, "review of the cultural, societal and influencer landscape"; and "distinct findings from MSL's proprietary influencer marketing platform, Fluency."

The influencers that were surveyed were asked to report how many followers they have, engagement rate on their posts, views on their videos, pay rates for their posts, race and overall income from various brands.

Additionally, "MSL and Reputation Leaders surveyed a nationally representative sample of 1,000+ consumers in the US about cultural and societal influencers."

The results are exactly as we suspected with BIPOC influencers reporting less income per post than white influencers and a shocking difference in how these two groups get started in the influencer industry. MSL reports, "By the end of their first year in the influencer marketing industry, white influencers are nearly twice as likely (73%) to get a sponsored brand deal than BIPOC influencers (46%)."

Additional findings from the study were equally disturbing.

• Compared with BIPOC influencers, white influencers are twice as likely to secure their first brand partnership in the first six months of influencer work – a critical milestone in a creator’s career (42% white vs 21% BIPOC).

• A strong majority of BIPOC influencers (81%) state they must work harder to be successful on social media compared to white influencers (70%).

• Perceptions of bias driven by a lack of transparency around platform algorithms are significant concerns. BIPOC influencers say that platform algorithms were the top barrier to their success (37%)."

With a computer algorithm in charge of influencer success and AI poised to create even more disparity, it's now more important than ever that we put more pressure on the platforms using these algorithms to address the bias.