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#ChooseToChallenge part one: Data bias

For many of us, March marks a full year of living with a pandemic and adjusting to our new work and life environments. It’s crazy to think that just one year ago Steve Sirich wrote about the launch of Marketing with Purpose. Together we’ve embarked on a bold mission, “born out of a few important things that have taken place in our industry over the past several years: the decline of trust in the digital space.”

One thing I’ve learned is that Marketing with Purpose is not just how your company stays relevant, but how it aligns to our society in the face of uncertainty. Take a breath and for a moment think about the person you trust the most in your life, that trust that has built an incredible bond — some might even call it loyalty — and that loyalty is there because this person understands you and your values. Replace that person with a brand that makes you feel similarly, and you have Marketing with Purpose.

85% of consumers say they’ll only consider a brand if they trust the brand.

 

As marketers, we want to forge conversations with our customers in hope that we build that brand loyalty that stands the test of time. We play a role in building trust and business value through purpose-driven marketing — are you still wondering how? In honor of International Women’s Day and Women’s History Month, #ChoosetoChallenge is the call to action you’ve been waiting for.

In upcoming posts, I’ll be sharing three ways you can #ChoosetoChallege your brand’s data bias, brand values, and how to tie these two together with your consumer values. As Rik van der Kooi, CVP of Microsoft Advertising put it “Data without trust is a commodity, and increasingly less valuable. Data with trust unlocks countless opportunities to be more valuable to consumers and brands alike. That’s what we are optimising for.”

We all appreciate automation, artificial intelligence (AI) and machine learning, but most large data sets are generated by systems that are known to be biased. While we mitigate that with evaluation and modeling by humans, why not #ChooseToChallenge the dataset and learn if there is enough diversity represented, or diversity in the humans doing the research? Check out FairLearn, Microsoft’s open source toolkit to help catch and reduce bias in your systems.

Marketing considerations to prevent data bias

 
  • Compare the value of nonbrand search vs. brand search by any dimension of diversity, like ethnicity, gender, sexual orientation, geographic, economic to name a few. Make sure you influence early the populations that favour nonbrand segment strategies to capture their early consumer research.
  • Use broad match modifier to uncover new nonbrand queries for keyword expansion.
  • Invest in audience-based cross-channel strategies. Microsoft Audience Ads have been shown to drive lift in search clicks.
  • Use demographic bid modifiers to capture gender, geo, age-specific audiences with aligned ad copy to the diverse audience trend behaviour uncovered by the nonbrand search analysis.
  • Consider non-traditional dimensions of demographics like a nonbinary consumer, or someone who identifies as female but shops for men’s products, and vice versa.
 

Throughout our industry, data bias shows up in marketing models and how we, as marketers, make decisions about who we target and how we communicate to them. Perhaps your lifetime value data and analysis show you who is the “model customer” due to conversion rate or cart size. Focusing on just your “model customer” puts you at risk for missing growth opportunities. I invite you to challenge this thinking and be deliberately curious about your brand’s long held beliefs. Plus, data collection in this way usually excludes a category of customers who are of another gender, nonbinary or third gender. Like the assumption that only men buy or have interest in cars, when in fact 51% of SUV sales are driven by women.

Join us in this effort and #ChooseToChallenge your brand with our checklist above, plus check out the full Marketing with a Purpose playbook if you haven’t yet. Next time, we’ll dig into how values create trusted relationships with our customers.