Simply using the phrase “cookieless advertising” is enough to induce a sense of helplessness and desolation in many people working in digital marketing. For several years, marketers have had access to a vast quantity of data, including user ID, user interests, and user behavior, all of which they can use to support any strategic choices. However, these glorious days are quickly ending since Google has announced that it will no longer save this data in the form of cookies beginning in 2023. Creative automation aims to generate a massive quantity of content, and scaling content is the first step toward a future without cookies.
Cookies have provided companies and advertisers with a view into the world of consumers and a window into the behaviors of consumers for more than 20 years. Cookies, the little bits of data that keep track of people who visit websites, are no longer used in Firefox, and Google Chrome is planning to eliminate them in 2024.
So companies will now enter an era of advertising without cookies. In terms of marketing, this will be a loss of catastrophic proportions since the capability to trace the purchasing path of a prospective consumer on the web gives valuable knowledge that may be used to inform future advertising efforts. Hence, in this article, we’ll discuss how programmatic solutions can ‘save’ advertising in a cookieless world.
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What are cookies, & why are they essential?
Cookies were first introduced in 1994, and at that time, they mimicked a function that real-life retailers needed to perform, which was to make a mental note of the visits and possible customers they had. Cookies are files that contain little bits of data that store information about your browsing session, such as where you are, who you are logged in as, and what items are in your shopping cart.
As customers could not be identified if they shopped anonymously online before cookies were introduced, it is not an exaggeration to say that cookies changed online shopping. Although not a healthy food option, cookies are the kind of digital sustenance that new businesses and startups depend on to construct their customer profiles and formulate their marketing strategies. As a direct consequence, consumers saw fewer advertisements that needed more relevance.
Cookies make the user experience better for those who shop online because marketers and advertisers can use the information they get from cookies to target their audiences more strategically and relevantly.
Why are cookies becoming less common?
As stated by a Director of Engineering at Google Chrome, the primary concern for the impending deprecation of cookies is users’ personal information and privacy. Users are expecting greater openness and choice regarding how their data is gathered and used, and they want it now. The ePrivacy Directive, often called the “cookie law,” was enacted to monitor the guarantee of confidentiality and consent in electronic communications. In addition, this directive has been known as the “cookie law.” This resulted in the continuous pop-up windows on this website, requesting that you either accept, deny, or adjust the cookies it uses.
The General Data Protection Regulation has strongly impacted this shift toward the obsolescence of cookies. There have even been investigations begun into whether or not the method Google uses for creating consumer profiles in digital advertising is in accordance with the privacy regulations that are in place in Europe.
However, there will always be a gray area, and it will only be possible for marketers to base their strategies on this area. As was previously said, audiences are looking for more variety. Because of this, consumers have the option to “opt in” if they so desire. On the other hand, audience numbers will certainly decrease to the point that the data is no longer scalable for any worthwhile media purchasing activity, which will likely result in poor conversion rates.
SEE ALSO: What is uplift modeling, how it works & what are its benefits?
What are the drawbacks of cookie-free advertising?
In a future where cookies do not exist, gaining targeted audience insights will be far more difficult. Advertisers will no longer have an easy way to get into the proven interests and habits of those buyers they want more information on. In a survey conducted in 2021 and directed by Boston Consulting Group in collaboration with LinkedIn, the researchers came to the following conclusion: 39% of marketers admitted that data losses have already started affecting their marketing performance, and 56% anticipated the impact would increase over time.
Signals such as product affinities, geolocation, or Customer Relationship Management (CRM) data are examples of live and historical user signals that can be utilized to reach the right person. One current example of this is dynamic display advertising, an example of how these signals can be used. As cookies are becoming extinct, dynamic display advertising, a kind of ad format used in the Google Display Network that modifies different aspects of an ad, depending on who is seeing it, may be greatly impacted as a consequence. They attract the attention of the individuals who are most likely to acquire your product, services, or solutions, which means that they are inherently cost-effective. However, in a world where cookies are not used, Google’s possibilities for rotating advertisements based on individual data are far more constrained.
Marketers needing help to develop new approaches to targeting advertisements will see a severe impact from this loss. Nevertheless, there is no justification for doing business without any prior research.
What other options do companies have?
A poll carried out by Hubspot in 2022 discovered that 54 percent of marketers were looking at alternative targeting methods. More than half of these companies are investigating the possibility of leveraging social media platforms to provide customized advertisements instead of employing third-party cookies. Another top method is to collect first-party data from their clients, and Google’s Topics API is also quite useful in this regard.
Viewers still anticipate seeing tailored advertising, even when they have expressed a desire for more personal privacy. You have a few different alternatives to choose from to provide this. Listed below, with more explanation, are some of these available choices:
Once third-party data becomes a resource with limited availability, you should look at new methods to collect and utilize first-party data. This refers to information gathered from a direct source, including a user’s purchase history, email marketing, questionnaires, reviews, other feedback programs, guest WiFi, and user registration, among other methods. It is only possible to share it with people within that domain.
Content restriction and progressive profiling
The following phase, after user registration, involves more extensive data gathering about the user, which may involve asking for demographic, firmographic, or other user information. This may be the next step after user registration. This kind of profiling is known as “progressive profiling.” It may be carried out by gating content or even whole websites. Users are required to provide their informed permission before freely sharing this information.
Cohort Federated Learning
Federated Learning of Cohorts (FLoC) is an algorithm built into web browsers that organizes internet users into “interest cohorts” so that users may be handled more effectively as groups than as individuals. The browser reconfigures the cohort, but the information is not shared with the browser company.
A group of individuals with the same identity is called a cohort. Identifiers may include a particular place, an event that was attended, or an application that was downloaded.
How can testing help address the cookieless advertising problem?
Utilizing material to its full potential and ensuring a significant amount of it accessible to be exploited are essential components of cookie-free advertising. Advertisers are provided with peace of mind in a post-cookie future by technologies such as Creative Automation. This is because these technologies enable the creation of hundreds or thousands of ad variants from a single template, which opens up unlimited possibilities for ad testing. This makes it easier to go from anonymous targeting to more specific targeting, with the specifics being determined by the outcomes of these studies.
The more menial versioning activities, such as pushing the proper ads, are a sophisticated process that should be backed up by professional (human) thinking. However, these chores should be left for the robots to do. Contextual targeting and advertising will continue to play an increasingly important role as the advertising business adjusts to a world without cookies. This indicates that contemporary cookieless targeting will use machine learning and artificial intelligence (AI) to display appropriate advertisements based on the content of a page that a user is currently seeing at that precise moment (or even the location or weather at the time).
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Even though it may seem difficult, using Creative Automation to personalize ads at scale while avoiding the use of personally identifiable data is rather simple. It involves putting the creative resource at the forefront and applying template thinking to reshape this creative asset into different variants, the performances of which may be tracked and evaluated. Putting the creative resource at the forefront also involves applying template thinking to convert this creative resource into multiple versions.
It has been used up to now to test a large number of different ad creatives to determine what viewers are looking for. Scaling content has taken on greater significance than ever due to recent developments in creative production technology and the absence of cookies.
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SEE ALSO: What is People-Based Marketing and What are its Benefits?
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