An inaccurate reflection

Editor's note: Pepper Miller is president of the Hunter-Miller Group. She can be reached at peppermiller1@me.com. This article is adapted with permission from a chapter in Miller’s new book “Let Me Explain Black Again.”

The market research industry shamefully lacks diversity and inclusivity. According to Media Post,1 the breakout of race and ethnic representation in the research industry is: 68.9% white; 13.2% Asian, 10.2% Latino, 4.9% Black American, 0.2% American Indian and Alaska Native.

This lack of representation leads to a deficit of insights. Diverse talent and relevant tools and practices would direct recruiting and interviewing of underserved segments and help brands understand and better communicate with them. Business leaders must unlearn the one-dimensional traditional practices to fix the deficit and incorporate a new approach.

I am grateful for the clients who invest in Black studies and the respondents who participate in them. Yet, comparatively speaking of the industry at large, throughout my market research career, there has been little designated research conducted with Black Americans by Black Americans.

Most of my work has been conducting qualitative research – focus groups, ethnographies, one-on-ones, executive interviews, listening sessions and the like with Black Americans. What I love about my work is the opportunity to converse with respondents – real people – who, in addition to sharing their opinions about particular products, services or advertising, talk about their dreams, hopes, experiences and challenges as Black Americans. I’ve learned so much about the Black community and myself from these conversations. I live in a Black community in Chicago and appreciate how daily interactions with it have served as my lab for observations. But it’s the research projects, combined with my personal experience, that has been a major resource of Black insights for my work over the years.

Away from focus groups

Today, some major big-spender brands are moving away from focus groups. The quest for Black (and any) insights from this methodology has become questionable. They believe little is achieved from the process and say they aren’t learning anything new.

Here’s the problem: In today’s culture, where diversity has become one of the drivers for inclusion, for market research, diversity is meant to cover a variety of ethnically homogeneous studies. But that rarely happens. Very few brands are investing in Black-designated research. They pat themselves on the back for practicing “fair representation” by including one or two Black people in predominantly white focus groups and look to Census population numbers as their rationale – if Blacks are 14 percent of the population, then 14 percent should be represented in a mainstream focus group. Again, “They speak English, don’t they?” is a rationale for not investing in Black research and, therefore, rolling Black respondents in with mainstream. Many Black respondents in this situation are less honest and authentic. They tend to tell the truth but not always the whole truth.

The power of the introduction

More than 20 years ago, when conducting focus groups in some of the top Black-populated markets, a few respondents from various markets stopped to chat with me before exiting the focus group room, offering comments and questions such as:

“Why the all-Black group?”

“Why are they separating us from everyone else?”

“I wanted to share something about being Black [in America] but I wasn’t sure what was happening.”

Black people should be comfortable in focus group settings, especially with a Black moderator, but they aren’t always. Given our history, it’s common for Black people to be suspicious. Consider the Black focus group experience, whether in person or virtually:

  • They are likely screened and recruited by a white recruiter.
  • They are likely to be greeted by a white hostess.
  • Most are not “virgin” respondents and believe those observing are white.

So, the revelation of the exit questions from Black respondents years ago inspired me to invite Black respondents to be ... Black. In every group since then, during the introduction, I ask: “How many have participated in a focus group discussion – virtually or in person?” Hands go up. I then ask, “How many have participated in an all-Black group?” Maybe one hand of six to eight respondents is raised, but most often, none.

I then explain that sharing their honest opinions helps brands better understand and serve the Black community. Thus, it is essential for them to share their honest perspectives from the Black lens and to be authentic during this discussion. “Think about Thanksgiving,” I would say, “and how some of us have moved from the formal dining room table to the kitchen to have dessert, which might be ...” I pause, and many shout out: “sweet potato pie, banana pudding, pound cake, etc.”

I continue with, “So when it’s just us, sitting around the table having our favorite dessert, I want to have that conversation here!”

None of this is leading. Blackness and Black culture are on our radar every day. Most Black people think about Blackness 90 percent of the time, versus whites, who think about being white 10 percent of the time. So in research, especially in this industry that lacks racial diversity, it’s important to make respondents feel comfortable by introducing relevant and relatable examples in the methodology.

Create a connection

Non-Black interviewers can have conversations with Black respondents in qualitative research studies but Black interviewers create a better connection and encourage honest conversations.

Recently, my company conducted focus groups for a major drugstore chain. Included in that study were separate groups of Black men. I hired a Black male moderator to run the virtual groups. The men were ecstatic over his presence. Following introductions, the moderator allowed them a few minutes to express their delight in participating in an all-Black male focus group with a Black male moderator:

“This is really cool!”

“I never expected to see all these brothers and a brother leading the discussion! No offense, man, I just knew you were going to be white.”

“No one ever asks for our opinion.”

More comments like these were shared and similar comments from previous mixed-gender groups are often heard as well. 

If you’re a non-Black interviewer addressing an all-Black group, it’s important to begin by addressing the elephant in the room. Tell your “truth.” Be honest and authentic: “I’m ____ (white, Asian, etc.). I am not going to pretend that I fully understand Black culture.”

Then encourage respondents to tell their truth. Invite Black respondents to be authentically Black. Help respondents understand why their honest opinions matter.

More work on inclusivity

Technology is another area where more work is needed on inclusivity. I welcome progress driven by technology, even in the face of machines replacing humans. While I’m not a fan of people losing their livelihood to technology, I enjoy the convenience of an ATM, digitally reserved parking lot spaces, toll passes, etc. It’s progress. It’s where we have evolved.

Market research is evolving, too – to automated information data and artificial intelligence, which are designed to streamline the research process. Some of these benefits include using time more efficiently and measuring results more accurately. Improving technology also allows researchers to tap into unused resources and discover new opportunities. 

It’s great to have a program that captures words and phrases from focus group recordings, organizes them into similar categories and tabulates them – versus listening to them and manually performing the tabulations – what a time saver! 

The problem? Biased information is often baked into AI methodologies. Everyone has biases and people embed them into technology. An algorithm is a procedure used for solving a problem or performing a computation. Algorithms act as an exact list of instructions that conduct specified actions step by step in either hardware- or software-based routines.2 Automated intelligence and algorithms as related to market research are often developed from standards and experiences by non-diverse engineers, programmers, coders and technicians. Their biases and misunderstanding of Black culture can lead to information that promotes stereotypes, which would continue to widen the gap of ethnic understanding, connectivity and intersectionality.

Artificial intelligence prioritizes user preference, while our civil rights laws prioritize equality of opportunity.3 In the 2020 documentary film “Coded Bias,” then-Massachusetts Information Technology student and Ph.D. candidate Joy Buolamwini shares her experience with artificial intelligence and facial recognition programs. She decided to build an “Aspire Mirror” as one of her class projects. The mirror would be an inspirational tool to motivate her, especially in the morning before she started her day. It could include various images of animals or people that she could transpose over an image of her face. She chose an image of Serena Williams and used computer vision software to create the mirror. It didn’t work. Well, it didn’t work for her dark skin. Her face was not detected. So, Buolamwini put on a white mask and the software detected her face. When she took off the white mask, there was no detection. She checked the lighting and camera position. Still the same results without the white mask. During further investigation of the program, she learned that most faces in the program’s database were of men, lighter-skinned individuals, etc. In other words, not faces like hers – darker skin, with a broader nose and full lips.

More truth than we realize

Hollywood creates stories about machines that not only think but reason. And while we look at these stories as entertainment and pure fiction, there is more truth baked into these themes than we realize.

The Journal of the American Medical Informatics Association suggests that if those models use data that reflect existing racial bias in health care delivery, AI that was meant to benefit all patients may worsen health care disparities for people of color. While the sophisticated technology may be new, the Federal Trade Commission’s attention to automated decision-making is not. The FTC has decades of experience enforcing three laws important to developers and users of AI:4

Section 5 of the FTC Act. The FTC Act prohibits unfair or deceptive practices. That would include the sale or use of, for example, racially biased algorithms.

Fair Credit Reporting Act (FCRA). The FCRA comes into play in certain circumstances where an algorithm is used to deny people employment, housing, credit, insurance or other benefits.

Equal Credit Opportunity Act (ECOA). The ECOA makes it illegal for a company to use a biased algorithm that results in credit discrimination on the basis of race, color, religion, national origin, sex, marital status, age or because a person receives public assistance.

Enthusiasm and caution

We have to approach this new world of technological market research with both enthusiasm and caution. As business leaders and market researchers we must be vigilant about planning, foresight and inclusion. In particular, we must determine how the market research industry can harness the benefits of AI (and traditional market research practices) without inadvertently introducing bias or other unfair outcomes. 

We must ensure that Blacks and other people of color are at the table and their ideas and voices are welcomed through their respective cultural experiences. These collective ideas would surely be useful in creating programs, methodologies and tools to ensure a broader reach, effective participation and insightful analysis in our studies.

Relevant market research matters! 

References

1 “Lack of diversity in market research: What can we do?”, Scott McDonald, MediaPost, September 17, 2021.

2 techtarget.com

3 “Artificial intelligence: How the internet gatekeeper can affect your civil rights,” Lindsey Nako, Impactfund.org, March 1, 2020.

4 “Aiming for truth, fairness and equity in your company’s use of AI,” Elisa Jillson, Business Blog, FTC.gov, April 19, 2021.