The clock is ticking on third party cookies!
Firefox and Safari have long gotten rid of them but Google just pushed their date back to 2025.
Google is probably the most popular of the three in terms of an advertising network and calls from governing bodies says Google’s alternatives ie. Privacy Sandbox is not enough to support marketers just yet.Â
This doesn’t mean we should stop planning. The change is inevitable. It just means we have a little more time to prepare.Â
Cookies Explained
Cookies are small text files stored on a user’s device by websites to remember information like login details, preferences, and browsing activity. They enhance user experience by personalizing content and maintaining sessions.Â
The Two Types of Cookies
First party cookies are used by a single website’s owner to track a user’s movement and activities across that specific website.Â
Third Party cookies on the other hand, are set by other websites than your own, and track usage across the various websites. This can be used for retargeting, cross site tracking and attribution.Â
Third party cookies are the ones that are being phased out!
Let’s also define the term attribution.
In marketing, attribution refers to identifying which channels, touchpoints, or interactions contribute to a customer’s journey or conversion, such as a purchase or signup. Attribution helps marketers understand how various interactions across different channels (like social media, email, search ads, etc.) influence a customer’s decision-making process. By assigning credit to these touchpoints, businesses can see which marketing efforts drive results and optimize their strategies accordingly.
Types of Attribution Models
- Last-Click Attribution: Credit goes to the last touchpoint before conversion.
- First-Click Attribution: Credit goes to the first interaction that started the customer’s journey.
- Linear Attribution: Each touchpoint in the journey gets equal credit.
- Time-Decay Attribution: Touchpoints closer to the conversion receive more credit.
- Position-Based (U-Shaped) Attribution: Assigns more credit to the first and last touchpoints and splits the rest equally among interactions in the middle.
Why Attribution Matters
By analyzing attribution, marketers can:
- Optimize Budget Allocation: Invest in channels that drive the best results.
- Improve Customer Insights: Understand the customer journey better.
- Measure ROI: See the direct impact of specific marketing efforts.
Attribution is especially crucial in a digital age with complex customer journeys involving multiple touchpoints, making it key to successful marketing strategy.
What is Cookieless Attribution?
Without third party cookies, we must now find ways and means of marketing with tracking every attribution that leads to a conversion. This is where cookieless attribution comes in.Â
Cookieless attribution is the use of alternative techniques such as server side tracking, and device fingerprinting to capture data anonymously. Data that can still be used to make marketing possible.
Cookieless Attribution involves relying on :
- Information a user provides directly:Â for example when signing up for a newsletter (first party data).
- Looking at the bigger picture: Instead of tracking you individually, it might look at the overall patterns of many people to figure out what’s working.
- Tracking on the Server: Some information is collected directly by the company’s servers rather than being stored in your browser.
- Focusing on Context: Ads might be shown based on the content of the page you’re on rather than tracking your past behavior
So, cookieless attribution is all about finding new, privacy-friendly ways to understand what marketing efforts are successful without needing to track every move you make online.
Side by Side comparison of Cookie-Based Attribution and Cookieless Attribution
| Aspect | Cookie-Based Attribution | Cookieless Attribution |
|---|---|---|
| Tracking Method | Uses cookies (small data files) to track user behavior across websites. | Relies on alternative methods like first-party data, server-side tracking, predictive insights and probabilistic models. |
| User Identification | Tracks individual users by storing unique identifiers in their browser. | Focuses on anonymized data, statistical models, and context rather than individual tracking. |
| Privacy Concerns | Often seen as intrusive, as it collects personal data across multiple sites. | Designed to be more privacy-friendly and compliant with regulations like GDPR. |
| Data Accuracy | Typically provides more direct and accurate tracking of user behavior. | May be less precise, relying on aggregated or inferred data to understand user actions. |
| Cross-Device Tracking | Can track users across different devices if cookies are synced. | More challenging to track across devices without cookies, often requires advanced techniques like identity solutions. |
| Regulation Compliance | Faces increasing restrictions due to privacy laws and browser policies. | Better suited for current and future privacy regulations, reducing the need for user consent in many cases. |
| Implementation Complexity | Generally easier to implement with widely available tools and technologies. | More complex to set up, requiring new tools, expertise, and approaches to ensure accuracy and effectiveness. |
| Dependence on Browsers | Highly dependent on browser support for cookies, which is decreasing. | Less dependent on browsers, as it can utilize server-side tracking and other technologies. |
| User Experience Impact | Can slow down website performance and affect user experience due to cookie loading. | Potentially faster website performance without the need for extensive cookie management. |
| Innovation | Traditional method, becoming outdated due to privacy concerns and regulations. | Drives innovation in the industry, leading to new solutions and tools for attribution without cookies. |
How to Market Without Cookies
Now that we’ve explored what cookieless attribution is and how it differs from cookie-based tracking, let’s discuss how you, as a business owner or marketer, can start marketing without third party cookies.
Acquiring and Using First-Party Data
First-party data is distinct from third-party data because you own it. You collect this data directly from leads, website visitors, and customers through various means, such as:
- Surveys
- Online signup forms
- Polls
- Direct mail
- Newsletters
Your first-party data is unique to you because it is collected directly and is not shared with any other party or company.
Using Google Analytics 4 Advanced Features
- Enable server-side tagging: Server side tagging tracking allows you to track users on your website and apps using your own server or Google’s server, rather than relying on data stored in the user’s browser.
- Leverage Google Consent Mode V2: The advanced version of Consent Mode lets you collect some data while respecting user privacy. It uses AI-based modeling and to fill in the gaps that cookie-based tracking would typically cover. With basic consent, GA4 collects no data when a user denies permission to be tracked. However, with advanced mode, anonymous data is gathered, helping create more accurate AI models.
Adjusting Our KPIs
Change can be difficult but for most of us, we can’t just close up shop and stop business. And for newcomers in the digital space, they also need to learn the new ways of measuring success. With the death of cookies, there are some success metrics which we will have to rely less on, and some we will have to pay more attention to.
Less Important KPIs: User-level tracking, third-party data-driven metrics, cross-device behavior, and retargeting KPIs will lose relevance. Examples are CTR from retargeting ads that requires cookies, unique visitors/ user count across sessions, multi-device conversions.
More Important KPIs: First-party data collection, engagement, content relevance, predictive analytics, brand loyalty, and privacy compliance metrics will gain prominence. Examples are subscriber growth rate, scroll depth, performance of individual pieces of content rather than the exact users (blog post, videos), AI forecasts based on trends, customer lifetime value (CLV), retention/churn rate, consent optin rates, track modeled conversions based on anonymized data.
Contextual Based Advertising
When running ads, you may not be able to place them based on past user behavior as much. A strong alternative is to place ads based on the content of the website you place ads on. For example if you just wrote a book on Benefits of a vegan diet then you may want to place your ad on an online vegan grocery shop. This way they are directly related.
Conclusion
While planning and adjusting for a cookieless world will take a good amount of upfront work and adjustment to how we market online, it CAN be done. And it will be well worth it because in truth, the more we rely on first party data, your marketing efforts will actually be more accurate.
