6th January 2023
Moderated by Bob Lord, IBM Senior Vice President, Weather Company and Alliances, the panel featured:
1) Our consumers of today may not look like our consumers of tomorrow.
Today, there are opportunities for marketers to align their media and messaging with the changing complexion of the U.S., to reach more diverse audiences that hadn’t previously been reached at scale but will purchase your products.
Yet, most audience strategy in advertising is developed by analyzing past behaviors to predict the future, often with overly simplistic and stereotypical associations of consumer identity with behavior. Imagine if someone in the real world said, “You’re old, so you wouldn’t like this tech product.” We’d definitely find that inappropriate and biased at best…but this is essentially how targeted digital advertising has worked over the past 20 years.
2) Data strategies have historically lacked empathy and an understanding of changing human behavior.
The new competitive advantage lies in the injection of empathy into your data strategies, where to date, marketers have relied too heavily on rational data. At Mindshare, we call this data strategy framework—one that balances accuracy and empathy—Precisely Human Intelligence. But harnessing empathy in your data strategies requires data ethics and responsible use of AI to ensure increasingly human advertising experiences are delivered with intention.
3) A lack of empathy exacerbates the growing issue of Fairness in advertising.
And there’s a misperception that addressing it means it might have to come at the expense of performance. Marketers haven’t had the tools to fully interrogate the data science that is being performed to direct advertising dollars to groups of consumers. If we can analyze the underlying data and optimize the modeling itself, we can deal with the missed opportunities and inequities created by unintentional bias. As an example: Using IBM’s Advertising Toolkit for AI Fairness #60, toolkit, Mindshare developed a three-stage analytics framework to address unintentional bias in advertising: locate bias, mitigate bias, and validate that bias mitigation doesn’t have to come at the expense of marketing and business impact. We found that you can design strategies that better balance fairness and performance; now we’re bringing this to live client campaigns this year.
4) Good media strategy is still about reach and context to deliver growth to your business— the goals and KPIs haven’t changed, but you can maximize reach and find the right context in ethical ways.
And by doing so, you’ll drive both your business and social responsibility. This has been a priority for Tyson Foods’ media and marketing strategies. For example, the brand partnered with Mindshare as the alpha client for the launch of the Impact Index, which uses AI to examine the social impact of editorial content on minority communities and optimize paid media spend accordingly.
And the proof points are there. Doing good, like: investing in minority-owned media, increasing inclusivity in media placement, and driving more fairness in audience design–is good for business. But marketers must put in the work by leaning into new partners, new tools, and measurement approaches.
5) In order to drive both fairness and performance overall, companies need to have regular, open, and honest dialogue about their intentional marketing practices.
It starts at the top, with CMOs making it a priority to create advertising programs that invest in media environments and tactics that create a more equitable industry and ecosystem. Contributors to that dialogue should range across your organization, from IT to legal to marketing and PR and more. From there, you can take actions on how to align your ethical principles to your values; define your risk tolerance; create a framework for filtering marketing decisions through before you execute them; and test-and-learn because ultimately buy-in comes from performance.