Everything you need to know about audience targeting without relying on third-party cookies

Following the passage of landmark consumer privacy laws, Google announced its intention to phase out third-party cookies on Chrome browsers by next year. This is undoubtedly a victory for the conscious consumer wary of selling data to advertisers, but it might also leave businesses scrambling when the cookie jar disappears. But these businesses should be more excited than alarmed. While the death of third-party cookies is an obstacle, it’s also an opportunity: As alternatives to third-party cookies emerge, advertisers might find themselves better-equipped audience targeting and acquirement methods.

The forthcoming phaseout will pressure marketers to rethink their strategies for accurately targeting audiences. Third-party cookies haven’t always been perfect right out of the oven. Their quality was largely dependent on factors such as the data provider’s methodologies, the latency and recency of that data, and any related acquisition costs. Although occasionally stale, these prebuilt audiences allowed advertisers to scale their audiences quickly.

What are the alternatives to third-party cookies?

Publisher-walled gardens (where publishers trade free content for first-party data) are a solid starting point for advertisers seeking alternatives to third-party cookies. These audiences won’t come cheap, but it will be possible to find publishers with audiences that strongly align with your customer base. And because these data sources are generally authenticated, they’re also an accurate source of modeling data to use as you construct your user databases.

Many purchases begin with online research, so savvy marketers explore contextual advertising as a third-party cookie alternative. Mapping out the sales funnel for your product or service will help you identify opportunities for targeted advertising as your audience performs research. Still, it’s essential to be precise at the same time. Use negative search terms and semantic recognition to prevent your brand or product from appearing in potentially embarrassing or unsafe placements. (Consider the word “shot,” which in this day and age could relate to anything from COVID-19 or health and wellness to debates surrounding the Second Amendment.)

There’s still time for a smooth transition away from your dependency on cookies, but you shouldn’t wait much longer to get started. As you explore new ways to get your message out to precise audiences, these strategies are a great place to start:

1. Lean on second-party data

Second-party data (such as the kind provided on publisher walled gardens) can offer accurate audience targeting for advertisers hurrying to replace third-party cookies. This data type can inform people- or account-based marketing strategies, helping you identify individuals in a specific industry or those with a particular relevant job title. Similarly, integrating second-party data with your broader digital marketing strategy can create use cases for lookalike modeling or provide a strong foundation for sequential messaging.

Because second-party data will come at a potentially high cost, try to partner with publishers and providers for the long term to keep rates as low as possible. As an added benefit, this will give you time to experiment and use various data types differently.

2. Implement mobile ad ID (or MAID) targeting

MAID targeting is based on an anonymous identifier associated with a user’s mobile device operating system. MAIDs have always been the go-to for application targeting because they’re privacy-compliant and serve as a great way to segment audiences based on behaviors and interests. Everyone expected MAIDs to grow as mobile and in-app usage has accelerated. In the U.S., for instance, mobile users spend just over an hour more on those devices than their computers each day, and they spend 87 percent of the time on their smartphones in-app. But the death of third-party cookies will undoubtedly accelerate the usage of these audiences across channels even more.

One of the most potent insights offered by MAIDs is the ability to track a user’s location data. For example, if a device is frequenting an NFL stadium, you can infer that the user is a football fan, which allows a host of other inferences to form. You can also enrich MAIDs with offline deterministic data, allowing you to construct a complete picture of the user, their demographic information, and their relevant interests. Recent changes to Apple’s iOS 14 platform might limit this targeting on the company’s devices. Besides this, it’s also essential to verify the precision and accuracy of the provider giving you location data.

3. Build custom models and indexes

Algorithmic targeting or lookalike modeling caught a bad rap from advertisers who worried the modeled audiences would broaden targeting too far. But as the quality of your audience input increases, your modeling output also increases. In other words, concerns are justified only if you’re modeling audiences after modeled data. On the other hand, models can be an excellent source of additional insight if you use deterministic data.

This information comes from various sources, including social media platforms, questionnaires and surveys, and e-commerce sites on user purchase history. In short, it’s data you can trust — meaning it can inform the creation of accurate audience segments and models that capture real customer intent. With deterministic data at the helm, you can create your models and indexes to aid your targeting efforts. First-party data from customers and active social media followers generally provides the best source for models. Be aware of outliers regarding audience insights; signals should be strong enough to imply the target audience’s actual behavior.

4. Use Unified ID solutions

The death of third-party cookies doesn’t mean the end of all your strategies. You can expect various sophisticated solutions to emerge in the coming years that offer audience segmentation with increased control for advertisers and enhanced consumer privacy protections. Some companies are working collaboratively to create Unified ID solutions that modernize audience targeting and measurement.

Their solutions aim to collect user information (such as email addresses) in exchange for free content. Those addresses will then be assigned encrypted IDs transmitted along the bid stream to advertisers. If publishers widely adopt unified identity products, they’ll provide an excellent alternative to an overreliance on walled gardens. However, one of the biggest hurdles for a suitable ID solution will be scalability: It will likely not be a solution that can stand alone for some time.

The death of third-party cookies will shake up the advertising world, but that’s probably a good thing. Cookies were never designed to be the backbone of digital advertising. Their disappearance makes room for alternatives to third-party cookies that deliver a better experience for advertisers and the audiences they’re looking to target. As advertisers gain more granular control over who hears their messaging (and when) and customer data is ensconced behind modern encryption and privacy protection tools, it’s not hard to argue that everyone wins when we put away the cookie jar.