Martech has a bias problem. It is a problem that continues to haunt digital marketers and platforms, capture headlines, and create reputational and legal risk for brands. It is also an opportunity to examine the implicit bias impacting how we, as digital marketers, think about the complexities and nuances of people and communities. At Kinesso, we are deeply committed to delivering consumer experiences that are respectful, fair, and create value for stakeholders, especially individuals. Instead of chasing data points, teams across Kinesso are pursuing human understanding.
A vital component of delivering respectful experiences to people is acknowledging the inherent bias in the data ecosystem. This may show up in the form of algorithmic bias by machines, survey bias in collection practices, or confirmation bias in how audience data is interpreted and applied. Bias is especially prevalent in data representing BIPOC communities, resulting in mis or under representation. The result can skew strategic insight, detrimentally impact campaign performance, reinforce stereotypes, and deepen societal inequity. There is a lot at stake. This is not just about impressions, clicks, reach, or frequency. It is about how we see one another, not simply as consumers, but as human beings, with rich cultural and racial identities, values, and belief systems—and how that translates into the audiences that we are designing.
When an IPG partner agency approached Kinesso to support their latest campaign for travel brand Black & Abroad, it presented an opportunity to pilot an innovative connection with Black audiences. This agency created BlackElevationMap.com, an interactive experience of the United States highlighting Black population data, historical marketers, Black-owned businesses, and social media activity. The map was designed to encourage Black travelers to explore the United States through the lens of community and cultural engagement. We at Kinesso built upon our existing data to design the ideal audience to target and drive to the map.
We started with research into culture, values, and beliefs. We opted not to check a “Black” racial qualifier in our data selection. Instead, we relied on internal and external research to identify the behaviors, preferences, lifestyle, and values of Black travelers and what is influencing their travel decisions. Research reports we’ve reviewed gave us insight into changing behaviors and attitudes during the pandemic. We also created addressable data attributes around the importance of race/identity, cultural traditions, and honoring ancestry – all attitudes that would indicate interest in the Black Elevation Map. In combination with our rich Kinesso audience data, this enabled us to create a High Value Audience (HVA) of 10M+ individuals who possess attitudes and beliefs that predisposed them to be a Black American interested in domestic travel.
To ensure that our HVAs reached actual Black-identifying audiences, our addressable buying teams designed a media plan that sought out relevant contextual environments aligned to the data attributes in our audience definition. Contextual areas around African American history, Black culture, Black travel, and Black community were identified. Within social environments, seed audiences were constructed based on audiences engaging with the Black & Abroad content. We also leveraged our IMPACT Marketplace of BIPOC-owned media properties.
Teams across Kinesso dedicated 1000+ hours designing, executing, and managing this pro bono campaign. Overall, audience match rates, traffic and engagement with the Black Elevation Map are strong.
Data is meaningless without the context of a story. Throughout my career in advertising, I have recognized the need for greater insight into BIPOC communities to leverage the data more effectively in uncovering the broader story. In the future, I would like to see a marriage between advertising and academia, which connects Audience Designers/Planners/Strategists to panels of scholars for personal education and professional insight. While Kinesso Data Scientists work to solve algorithmic bias from a data integrity perspective, so too must Audience Strategists educate themselves on cultural and behavioral trends. This becomes an essential bias-mitigating filter to the data, and it is only the first step.