What is the Post-Cookie Era?
How Do Cookies Work in Browsers?
EU Regulations on User Privacy
Online data in Business – how to use them?
How to Collect Data in the Post-Cookie Era?
Privacy Sandbox
Enhanced Conversions
Consent Mode v2
Behavioral modeling
Conclusion

What is the Post-Cookie Era?

Imagine a perfect world of online data, where the user takes center stage. In this world, we can know everything about the online user: where they come from, what they do in our digital products, what their shopping preferences are, and their purchase history on our site. This knowledge is limited only by our imagination in its application. We can optimize ads, creatives, texts, service, checkout, and even manage inventory.

The online data world is available here and now, allowing us to continuously use the information it provides. However, the quality of available data is becoming blurred by regulations concerning the collection of users’ personal data on the site.

Before discussing ways to maintain high-quality online data, we should define why the cookie era is so crucial. Cookies play a key role in the online world and data quality. The online world is stateless, meaning each user interaction with a website is independent of previous ones. Cookies allow for the tracking of these interactions, enabling data collection and analysis. How, then, can we imagine digital analytics without them?

How Do Cookies Work in Browsers?

In the context of e-commerce, data quality is extremely important. With precise data, companies can better understand their customers’ behaviors, optimize marketing campaigns, and make better business decisions.

Comparing this to the automotive industry can be helpful in understanding the role of cookies in online analytics. Imagine coming home and getting into your car, only to find that all settings – mirrors, seat, steering wheel, driving mode, and even the home address in the navigation – are reset. Every time you get into the car, you would need to adjust these settings again.

In practice, if you have one car that you share with a partner, each of you has your own key associated with individual car settings. This key is analogous to a cookie in the online data world. When you use a website, add an item to your cart, log in, and then return to that site, the products remain in the cart.

If you move from a product page to the cart and then to checkout to complete your purchase, a cookie is essential in the stateless world to transfer this information between subpages. One might ask, if cookies are so useful, why are we starting to talk about a post-cookie era in which cookies will be limited?

In practice, technologically we divide cookies into first-party and third-party categories. More important is understanding how the European Union and legislation view cookies. They are seen as essential, meaning the service cannot function without them. For example, without cookies, adding a product to the cart and then completing the purchase would be impossible, as the service would not remember that the products were added.

Unfortunately, from the perspective of data professionals, most cookies are considered non-essential. Analytical and marketing cookies play a crucial role in understanding how users interact with websites and delivering personalized ads.

EU Regulations on User Privacy

The European Union takes a strict approach to privacy issues because companies like Google collect vast amounts of data about users. They track what we watch, read, buy, and even store our financial data if we leave them there. Logging into Gmail, we provide our personal information, giving Google access to a wide range of details.

The EU aims to better protect data of internet users in the future. This process began in 2002 with the e-privacy directive aimed at safeguarding data. However, it was mostly a declaration on paper. Real changes began in 2009, about 10 years after the internet revolution. Websites started displaying banners informing users about cookie usage, which introduced little change in terms of e-privacy and merely reduced site usability.

Significant changes started occurring in the last 4-5 years, starting from 2019. The EU Court of Justice’s ruling turned into guidelines from the European Data Protection Board. Websites must now seek user consent for cookie usage, not just inform them about it. Consequently, cookie management platforms began to emerge, managing and obtaining user consent.

Among these platforms, decisions often arise about what types of cookies can be used. From a statistical and marketing data perspective, all cookies are important. Moreover, GDPR requires active consent, meaning users must opt into cookie usage. There must be an easy way to withdraw consent, and dark patterns, such as hiding the “decline all” button or manipulating button colors, cannot be used.

In 2023, the Digital Markets Act introduced significant changes in the context of cookie usage, which has had a major impact on the world of data. The lack of an ID makes data less contextual. Without an ID, a visit cannot be linked between sub-pages or different time periods, making it difficult to recognize a user. Business, especially online marketing, badly needs this data. The lack of cookies leads to a problem referred to as “Garbage In, Garbage Out.”

Online data in Business – how to use them?

Collaborating with e-commerce and online businesses, we help leverage data in three main contexts. Every business should utilize data regarding:

1. User Acquisition to the Website – It’s essential to know how many times an ad was displayed, how many clicks it received, how many people visited the site, their actions on the site, and whether they made a purchase. This allows linking marketing spend to revenue, visible in analytics tools.
2. User Behavior on the Site – Analyzing how users navigate the site, what they click, and what subpages they visit gives insight into their preferences and needs.
3. Conversions and Sales Results – Monitoring whether a user made a purchase allows evaluating the effectiveness of marketing campaigns and optimizing expenditures.

In practice, the main source of truth is the data warehouse that many companies manage in the context of web analytics. One of the key tools is Google Analytics, which, properly configured, should show about 85% of market reality. This 15% is due to the fact that some people have blocked cookies, especially tech-conscious users. In technology sites, the differences can be much greater.

In e-commerce, especially in fashion, these differences should not exceed 10%, which means that 90% of the data should be available. However, with the changes that began around 2019, we are losing more and more data in online marketing. These losses can be as high as 50%.

How to Collect Data in the Post-Cookie Era?

So what are the solutions? How to act in a post-cookie world to preserve data quality and effectively support marketing and business?

Privacy Sandbox

The first solution preparing the market, specifically Google, is the so-called Privacy Sandbox. This is a bunch of various solutions, including the Protected Audience API. Instead of third-party cookies that transfer user activity data between sites (e.g., someone saw shoes on Modivo, then sees the same shoes in an ad on Onet), the browser will now decide on displaying the ad based on the user’s browsing history. The quality of matching may be lower as competitors like CCC, Answear, or other fashion shops might also appear alongside Modivo.

Currently, all browsers except Chrome block third-party cookies, preventing remarketing on these browsers.

Enhanced Conversions

In the Post-Cookie Era, we must prepare for these changes and hope that solutions will be refined enough that our marketing efforts do not suffer significantly. One solution to implement internally within companies is Enhanced Conversions from Google and Conversion API from Meta.

Enhanced Conversions work by having Google Marketing Platform recognize that user X saw a particular ad if they were logged in to Gmail while viewing it. When cookies are absent, implementing Enhanced Conversions involves sending a hashed email along with the transaction. During the transaction, an email must be provided for confirmation and status purposes. Google, upon receiving the hashed email, can match data and improve conversion attribution accuracy.

The improvement in conversion attribution quality with Enhanced Conversions averages 17% for video ads and 5% for Google Ads. This means that the actual revenue from a transaction is properly attributed, rather than erroneously, to another traffic source. Enhanced Conversions thus rely on sending hashed personal data, which significantly improves the accuracy of ad performance analysis.

Consent Mode v2

Another solution for data gaps is Consent Mode. Consent Mode fills in data based on information without user IDs. Implementing this solution requires the initial element—a cookie management platform—to know what consent the user has given.

The way it works is that if the user agrees to cookies (state granted), everything works as in the cookie world and there is no problem. In the cookie versus post-cookie era, nothing changes here. In the post-cookie era, when the user does not give consent, every interaction sends so-called pings. A ping is a packet of information that does not contain the user ID. There is also a third state – lack of consent. This is a key change that has significantly affected online marketing. Publishers cannot process data if the user has not made any decision regarding the use of cookies.

Behavioral modeling

Digital Market Act (DMA) introduced new regulations, with Google noting the GDPR directives of 2020 requiring companies to effectively manage cookie usage. Top companies like Google, Meta, and Amazon face penalties of up to 10% of revenue for processing data without user consent.

Many companies that did not implement these changes saw a drop in traffic and sales. This was because marketing mechanisms such as Google Ads, which automatically optimize campaigns based on machine learning, need data to work. When the flow of data was interrupted, ads stopped displaying, resulting in a drop in traffic and revenue.

One solution to this problem is behavioral modeling, using so-called pings. Pings, packets of information without user IDs, are sent even when consent is not given, thanks to consent mode. Models created in Excel or Matlab in the past were fairly effective, but today, with machine learning, data is even more precise. In the Post-Cookie era, despite the lack of cookies, we can achieve greater data coverage in data warehouses, up to 85%. In data warehouses such as BigQuery, data is constantly updated.

With consent mode enabled, this data is available without a user ID, but can still be remodeled and used, for example by combining it with data from media and analytics platforms. We often act as an assistant, creating data warehouses for marketing or helping to manage them as the main source of truth. We supplement these warehouses by improving the quality of the data.Conclusion

The online data world is becoming increasingly complex. Mechanisms exist to sharpen the data picture, though they will never be as accurate as in the cookie era. It’s worth preparing for the worst by implementing at least consent mode version two and hoping for the best solutions the advertising industry can offer in the future.

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