Future-Proofing Marketing & Data Strategies in a Post-Cookie World

William Skelly

Data Strategies, Post-cookie solutions, Digital IT News

March 25, 2024

Future-Proofing Marketing & Data Strategies in a Post-Cookie World

This was first published in Digital IT News.

The cookie has finally crumbled… third-party cookies that is. On January 4, 2024, Google began restricting third-party cookies for 1% of Chrome users. By third quarter 2024, Chrome plans to restrict third-party cookies for all users of the web browser.[1]

Third-party cookies have been important for advertisers, brands, publishers and data providers for nearly 30 years. In addition to tracking consumers’ website activities, third-party cookies have been used to streamline and personalize online experiences, such as simplifying logins for returning visitors or showing relevant ads.

Forward-thinking organizations have been preparing for the sunsetting of third-party cookies. They proactively optimize their first-party data, the information their customers and website visitors share with them.

Fortunately for advertisers, marketers and publishers still relying on third-party cookies, alternative solutions are available for targeting audiences on the web, retargeting consumers, as well as attribution on Google and Meta.

1. Alternative Identifiers Alternative identifiers replicate the functionalities of third-party cookies – minus the privacy issues. Alternative IDs rely on other data assets to identify users accurately. There are two types of alternative IDs:

  • Deterministic IDs rely on an email address or other personally identifiable information (PII) about a user. An integer value is assigned to the user’s email address, or hashed, making the ID anonymous to protect the user’s privacy. The IDs are based on user consent, usually obtained during sign-in. The user sets preferences, similar to third-party cookie permissions received under GDPR (General Data Protection Regulation). Deterministic IDs rely heavily on advertisers and publishers gaining an authenticated registration from first-party audiences. Deterministic IDs are hard to scale because consumers don’t have to login during the bulk of the time they’re online.
  • Probabilistic IDs don’t rely on first-party data because the solutions approximate the identity of users. Through a variety of signals across multiple channels, probabilistic IDs provide a best guess for who a user might be. IDs are approximated using IP address, operating system, device type and screen resolution. While probabilistic IDs can deliver more scale compared to deterministic IDs, there may be data inconsistencies, and it may be difficult to connect people across different devices.

An example of an alternative identifier is Google’s Privacy Sandbox, which aims to protect people’s privacy, while creating technologies for organizations and developers to build thriving digital businesses and keep online content and services free for consumers. Tracking Protection is a new feature on Chrome limiting cross-site and cross-app tracking by restricting third-party cookies.[2]

Other options for alternative identifiers are:

Unified ID 2.0 (UID2), which is championed by The Trade Desk. UID2 leverages encrypted email and phone number data to provide a privacy-conscious, secure, and accurate identity standard for the entire digital advertising ecosystem. Since consumers are everywhere, including mobile apps and connected TV, UID2 allows cross-device and cross channel frequency management, a more holistic targeting and measurement for modern marketers.

RampID, from LiveRamp, works by deterministically matching offline PII and online devices to people-based IDs. User IDs are created using a combination of third-party behavioral data, first-party data and offline data. Each individual is assigned a cross-device anonymous identifier, or ‘RampID.’ The RampID solution also plays a key role in the Advertising ID Consortium, which is an independent entity made up of ad tech companies, delivering an open identity solution to the digital advertising ecosystem.

2. Retargeting Retargeting is an advertising method which targets people who have previously visited a website. When previous visitors read a blog or go to a search engine or social media platforms, they will see an ad featuring a solution or product from the original website. While many online advertising methods are designed to attract new visitors, ad retargeting prompts previous visitors to return to a website to complete a transaction or desired action, such as buying product or sharing PII so that the organization can continue nurturing the lead.

Technology solutions such as Snowflake Data Cloud enable a single repository for a single copy of your audience data, helping marketers build robust 360-degree views of customer behavior. With its robust data sharing capabilities, the Data Cloud facilitates the creation of data clean rooms, which give marketing, media, and advertising teams a secure place to share data together analysis that comply with data regulations such as GDPR and California Consumer Privacy Act (CCPA).[3]

3. Attribution on Google and Meta Marketing attribution is the way advertisers map the customer’s journey, determining which marketing tactics and consumer interactions contributed to sales, conversions or other goals. Marketing metrics are used to identify the channels and messages that move consumers to buy or take a desired action. The marketing tactics, messaging and customer touchpoints may include emails, paid search, social media channels, streaming services and other myriad digital marketing interactions. Data analytics of the complex customer journey are imperative to support marketing attribution and determine the ROAS (return on ad spend).

  • Google Ads Attribution Model Google’s data-driven attribution (DDA) looks at all the interactions – including clicks and video engagements – on a visitor’s Search (such as shopping), YouTube, Display and more. DDA uses an account’s past data to give credit to the ads that make the biggest impact on Search, YouTube, and Display. DDA is using the account's history to determine which ads provide ROI (return on investment).[4]
  • Meta Ads Attribution Meta Ads Attribution sets a 7-day timeframe for clicks and 1 day for views. Meta will optimize to get the most conversions within 7 days of clicking and 1 day of viewing.[5]

Now that third-party cookies are being deprecated, it makes sense for marketers, advertisers and publishers to partner with data consultants to help them optimize their first-party data. There are solutions available now to ensure they continue to reach their audiences and attract new customers.

William Skelly is founder and CEO of Causeway Solutions, a leading provider of Acquisition Analytics and innovative data services. Bill serves as advisor with some of the nation’s most influential organizations—from grassroots public affairs efforts to U.S. Presidential campaign strategies. Causeway Solutions empowers clients to make smart, timely, data-driven decisions through real-time consumer insights to better reach target audiences. Learn more at Causeway Solutions.


[1]: “Preparing fo the end of third-party cookies,” Privacy Sandbox, Google for Developers
[2]: “The next step toward phasing out third-party cookies in Chrome,” Google
[3]: “Audience Targeting in Media, Advertising, and Marketing,” Snowflake
[4]: “About data-driving attribution,” Google Ads Help
[5]: “About the attribution setting,” Meta