Targeted Advertising in a Cookie-Free World

Since the introduction of Apple’s App tracking transparency policy changes, retailers have been searching for ways to rebuild the lucrative world of highly targeted social media advertising. When you add today’s inflationary pressure, brands are being forced to rethink their growth strategies and determine how to keep up with other shifts happening in digital advertising. From the rise of new media channels, data privacy changes, tech innovations, and changing consumer behavior, it seems like the digital advertising world is being turned on its head.

But with advertising, as with most things, the only constant is change. Now, savvy brands are seizing the opportunity created by the chaos of the current environment to shift their strategies, experiment with new approaches, and come out ahead.

A Push for Broad Targeting

Due to the iOS privacy change, the precision and accuracy of tracking and targeting have been removed since almost 80 percent of users have opted out of being tracked. Therefore, large platforms like Meta are shifting tactics. They're pushing advertisers to go broad with their targeting and to refine their approach with highly frequent creative asset iteration, while also removing targeted interest lists. This may help lower cost per impression in the near term, but the creative costs will be higher. And in the long term, this kind of poor targeting can degrade brand equity.

Still, a broad approach may work well for products and services that have mass appeal. But what about more niche products with targeted audiences? For these brands, advertisers must find new ways to reach their more narrow target consumers. For some, an innovative approach that includes a combination of first- and third-party data, plus sophisticated machine learning, is providing the answer.

First-Party Data is a Good Start

Today, brands have more first-party data than ever before. Leveraging this data is key to any brand’s marketing efforts. However, first-party data is still difficult to acquire and most experts agree that first-party data isn't enough on its own. This is partly because it can be limited in scope, as it doesn’t provide insight into new audiences that the brand hasn't yet engaged with. Still, assuming that the quality and accuracy of the data is good, using first-party data can lower advertising costs and reduce the time spent on creating and targeting ads, which is a solid place to start.

The Rise of Anonymized Third-Party Data

In today’s complex advertising environment, brands need more creative solutions — and they're looking more and more to third-party data. Third-party data can help brands build on their profiles of existing prospects and customers, and give perspective on new ones. More importantly, when anonymized and combined with artificial intelligence and data science, third-party data helps brands address the challenges of the current privacy environment.

Using anonymized third-party databases creates a wall between the advertiser and the data, which protects consumer privacy while providing brands with the information they need to acquire the right customers. Decentralizing underlying customer data has a number of benefits for advertisers. These include:

• access to more data, which can help identify new audiences;
• the ability to refine a paid marketing strategy;
• significant increases in prospecting performance and return on advertising spend (ROAS); and
• reduced acquisition costs.

This approach is showing great promise as a win-win for both parties, and it gives us perspective on where the future of advertising is headed.

In today’s environment, companies that practice responsible growth will come out on top. With advertising budgets being increasingly scrutinized, better technology and the introduction of anonymized third-party data is the key to more efficient ad performance. Advertisers have been bottlenecked in recent months, but by leveraging AI and machine learning, advertisers can begin to meet the demands of consumers, brands and media platforms alike.

Alex Song is the CEO and founder of Proxima, the data science company that leverages a proprietary database of anonymized consumer data to help brands better reach the right consumers across all major platforms.