Google’s Anti-Discriminatory Targeting Rules Require Legal and Analytic Collaboration

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While the ad world is still game-planning for how to operate once Google sunsets the cookie, the media giant went ahead and made another decision that effects targeting and goes into action much sooner.

Earlier this year in June, Google announced it will no longer allow advertisers to target or exclude consumers from employment, housing, and credit messages based on gender, age, parental status, marital status, or ZIP code. These anti-discrimination laws are not necessarily new, but renewed attention to enforcing them is a major statement in the digital ad business. Google’s new policy, which goes into effect at the end of this year, is a positive step in the quest toward wiping out discrimination in advertising. Still, the change is likely to confuse a lot of ad buyers and their agencies.

As brands and agencies continue to bring in third-party data to help with their audience targeting, the enforcement of anti-discriminatory rules in digital advertising requires careful consideration of audience strategy, and the teams responsible for executing those strategies. The challenge isn’t simply just eliminating the use of audience segments that violate the law (that’s part of it and necessary) but it also requires verification that no offending attributes were used in the case of modeled segments. Fortunately, brands and agencies can achieve this through better planning and collaboration.

A digital conundrum

Google’s decision follows a similar, though involuntary move by Facebook in 2019, and while it certainly deserves recognition for complying with well-established federal guidelines, both ad giants are essentially passing the burden on to the advertisers and their agencies, who may not be well versed into how they can ensure compliance with these rules.

Advertisers and agencies can either stop making audience selections that are based on protected classes – such as building lookalikes of existing customers – or they can define the ideal audience they want to use in a campaign and remove any offending attributes from the audience models, including those that implicitly discriminate.

While the former option may sound logical, it’s not only the lazier approach but also does not eliminate the risk that marketers could make selections that might disfavor protected classes. A lot of audience targeting is about segmenting on gender, age, ethnic background, or financial means. This, in itself, is discriminatory from the start. It might make sense to target CPG products to men under 50, but if the ad campaign is for housing, you can’t use an audience that eliminates all women and people over 50. That’s clear discrimination. Digital platforms never really saw this as a problem before, but the actions by Google and Facebook mean that certain advertisers can no longer purchase targeted audiences and apply them indiscriminately.

Clearly, trying to force compliance onto an existing digital audience seems easier on the surface, but it presents more problems. Whether the audience is built from an advertiser’s own first-party data, or it’s a third-party, off-the-shelf audience available through a marketplace, taking this route carries a far greater risk of running afoul of federal laws because both cases may include implicit discrimination (which is the second phase of HUD’s charge against Facebook). The safer way to approach compliance is to build audiences with compliance in mind from the beginning, which requires more active work and planning.

Plan for compliance

The challenge then is for advertisers and agencies to make anti-discriminatory targeting part of their overall campaign plans. For too many advertisers, audience planning can be an afterthought, tacked on to a campaign at the very end. This can no longer be the case for insurance, housing and financial services advertisers buying inventory from Google, and in 2020 it shouldn’t be the case for any advertisers, running any kind of campaign across any platform, regardless of that platform’s policies. Step one is to manage the compliance piece of an audience strategy much earlier in the planning cycle. Doing that requires more collaboration and alignment between in-house teams at the advertiser.

This means advertisers can no longer completely outsource the request for compliant audiences to their agencies. These new policies require advertisers to educate their agencies so that they understand the requirements and what needs to go into audience buys. Audience planning can no longer be passed down to an entry-level junior buyer who lacks context or expertise. If this happens and you, as an advertiser, somehow violate federal anti-discrimination law, you might be hit with a fine, even if the agency is the party that purchased the audience data on your behalf.

This is one of the main reasons why Google and Facebook are publicly adopting these stances—by announcing new policies, they can pass responsibility off to the advertiser. It’s imperative that all advertisers plan on handling FHA compliance when they sit down and start thinking about how they’ll run their campaigns.

In-house alignment

The marketing staff is normally tasked with making decisions around online campaigns, including audience targeting. It’s critical now that this team collaborates with legal so that they are aware of what first-party data assets they can or cannot use in putting campaigns together, and they know how to assess third-party audiences as well.

The marketing team itself also has to bear a bit more of the burden. As discussed before, the brand will ultimately risk the consequences if they run a discriminatory campaign, so it doesn’t make sense for the agency to be the sole party responsible for acquiring compliant data. Brand marketers need to know what they’re asking for and what goes into a compliant audience. Understanding audience compliance issues need to become part of this marketing team’s DNA.

The truth is that while anti-discriminatory campaigns may not apply to every vertical and every advertiser, the best practices required for getting these campaigns up and running eventually will. Compliance is an increasingly big part of working with consumer data, whether it’s how the data is collected (CCPA and GDPR) or how segments are created and used (FHA). For brands and agencies, the importance of understanding compliance laws and getting assurances from their partners will only become more complex and mistakes will become more costly. Audience targeting is one of the most powerful tools in an Advertiser toolbox to deliver messaging to the right consumer and can remain so with the right knowledge and partners.


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