What are first-party cookies, and how are they different from third-party cookies?
All cookies, whether first- or third-party, are stored in a user’s browser and designed to collect data about a user when they interact with a website.
First-party cookies are limited to a single site but perform an important function. They can be used to remember that a user has previously logged into a site, set correct language settings, or even keep a shopping cart filled across multiple sessions.
So far, so benign, which raises a question:
Why are people so worried about the privacy implications of cookies?
Well, unlike their site-bound counterpart, third-party cookies (also known as tracking cookies) can be used to track users across multiple websites. This allows companies to collect an enormous amount of data about a user’s browsing habits across the entire internet.
This is incredibly useful for advertisers, who can use this information to understand what products or services, and what aspect of those products and services, a user might be interested in. However, the sheer scale of data collection has led to significant privacy concerns, and will ultimately lead to the elimination of third-party cookies as a tool. That said, the more privacy-friendly first-party cookie is here to stay and remains a powerful tool for marketers.
How are first-party cookies used?
First-party cookies are remarkably flexible tools, limited only by the domain that they’re assigned to. Even before the cookieless future, first-party cookies have been actively integrated into many types of campaigns.
In general, the way first-party cookies work is the same regardless of campaign type. First-party cookies can be used to collect data about a user’s interaction with a website or app, which can help tailor content to that user. This could include product searches, a user’s shopping basket, or what content they’re choosing to interact with.
The advertiser or publisher can use first-party cookies to deliver personalized ads on a specific website with a given first-party cookie. This approach enables personalized ads that respect the privacy of the user.
How first-party cookies are used in retargeting campaigns
In a retargeting context, the advertiser is using data that either they or their client already own, called first-party data. For retargeting campaigns, this will typically be information about how a user is interacting with an e-commerce site, which enables the advertiser to understand what products that user is interested in, what their likely order value is going to be, and where they are in the purchasing process.
While first-party cookies cannot be directly used to personalize ads on other websites, they can help create privacy-preserving interest groups, for example, by using the Protected Audience API, which can then be targeted across the internet.
Let’s say you know a user has already looked at several products in the Ultrabook products category, but not made a purchase, then you place them in the “considering Ultrabook products” interest group. You can then show all users in this group adverts demonstrating the benefits of multiple products, giving them the information they can use to make a final decision and convert to a purchase.
How first-party cookies are used in branding campaigns
In branding campaigns, advertisers typically leverage publisher data. This includes information about the content that users on a site are interacting with, how they interact with that content, and how often they interact with the site.
The publisher can then place these users into interest groups that marketers can display adverts to, without ever needing to know the user identity. This provides many of the benefits of third-party tracking cookies, without needing to track a user’s actions across multiple sites.
Where do first-party cookies fit in the cookieless future?
The methods already discussed will continue to function in the cookieless future, and will likely become an essential part of your advertising strategy. However, there will also be innovations in how we use first-party cookies, and one of the most interesting is the CHIPS API proposed by Google.
This will enable developers to create cookie partitions, which allow tools like Google Maps to be embedded in a publisher’s website and remember information about a user only on that website while enabling the proper functioning of this tool across the web.
For example, if you search for “Rome hotel” on the imaginary Awesome-Italy-Hotels.com, the website will remember your search and input it the next time you log on. If you want to compare prices on another website using the same maps service, it will not load the same cookie, as the tool will not be able to recognize you as the same user.
Why not use fingerprinting technology instead?
Now is a good moment to address the elephant in the room: while first-party cookies are powerful, there is a reason that marketers have relied so heavily on third-party cookies – they provide more precise targeting of individual users which enables heavily personalized ads.
So, why shouldn’t marketers just double down on other tracking technology that provides the same granular data as third-party cookies?
Well, some advertisers are turning to tools like fingerprinting technology, which tracks users by unique features such as their device, browser, or specific configuration. These methods can track users but are highly invasive, and if the advertising industry adopts them as standard, they will demonstrate to consumers that they don’t care about their concerns. Nearly 80% of Americans are concerned about data collection, and if the advertising industry doesn’t adapt to address these concerns, those users may take matters into their own hands and use aggressive anti-tracking or ad-blocking tools.
This would be bad for users who will lose personalization, bad for publishers who will lose revenue, and bad for advertisers who will lose any way to effectively reach customers.
Okay, so how does RTB House use first-party data?
At RTB House, we’ve always been strong privacy advocates, so first-party data already forms the core of our strategy, particularly for retargeting, and branding/audience targeting. Our Deep Learning technology is uniquely well suited to this kind of data, as it is capable of understanding and interpreting data from diverse sources, and using that to deliver actionable insights.
How RTB House uses first-party cookies in retargeting
RTB House already has nearly ten years of first-party retargeting experience, so we saw an immediate opportunity to work closely with Google to create the Protected Audience API, previously called the FLEDGE proposal, which is a powerful retargeting tool that is based entirely on first-party data. The proposal is designed to meet remarketing and custom audience use cases without allowing third parties to track user browsing behavior across sites. The API enables on-device auctions through the browser, selecting relevant ads from websites that the user has previously visited without revealing any identifiable information to the advertiser.
We are one of just three companies that are already actively using the Google Sandbox in real browsers, and we are using this experience to build privacy-respected advertising solutions that still provide advertisers with the ability to effectively target users and maximize the value of their ad campaigns.
In April, the Google Ads team released a report that compared the effectiveness of applying the Topics API, contextual signals, and publisher first-party IDs instead of cookies for Interest-Based Advertising (IBA). The report showed that when a range of solutions were combined, it was possible to achieve comparable results to methodologies that rely on third-party tracking cookies. However, it should be noted that it is still early in the process, and the data gathered has been done with limited real-world testing to date.
How RTB House uses Deep Learning to maximize the benefits of first-party cookies
RTB House uses Deep Learning to better leverage first-party data in all of our retargeting campaigns. Our proprietary Deep Learning algorithms can parse complicated first-party datasets to better select the optimal user groups, helping to maximize the value of first-party data.
The key to successfully using first-party data is to start with a large amount of data and then slowly generate more granular results based on your initial results. This can be challenging, as first-party data sources are currently fragmented and difficult for many companies to work with. This is where RTB House’s secret weapon comes in: Deep Learning algorithms.
Deep Learning is particularly useful with first-party data as it can understand complicated, unstructured datasets and derive useful insights, even if the data sources differ significantly in terms of metadata and labeling.
Test first-party cookie solutions today and stay ahead of the competition
The best time to adapt to the cookieless future was yesterday, the second-best time is right now. The RTB House team is standing by to help your brand adopt privacy-friendly advertising solutions today, enabling you to build a comprehensive future-proof advertising strategy.
Reach out to our team today, and we’ll help you determine the best way to implement first-party cookies into your advertising strategy.
