EnglishDeutsch
Adello white

In the last few years, we have been witnessing how the world and especially people’s behavior are changing. Our attitude to privacy transformed as well. In particular, the changes affected the approach to personal data in the digital space.

With that, countries all around the world began implementing data privacy regulations. Now, marketing companies whose businesses were built on third-party cookies collections are obligated to find new ethical data collection methods. Third-party cookies are like a drawing boat, where marketers, brands, and advertisers try to leave it and stay afloat.

Why is third-party data collection unethical?

Let’s take a step back and find out again why third-party data is so problematic.

Previously, when users visited a website, the banner popped up informing them that the website collects cookies. Back then, not everyone was aware of what such an innocent notion of “cookies” meant and rushed to close the annoying banner. Some websites were trying to limit the options, so the users would have to agree. As a result, website visitors allowed third-party data collection. That’s how it leads to the first problem - consent. The users were forced to press “agree”.

Even more so, many companies collect users’ data without their contest. For instance, Zoho Privacy Survey Finds 62% of businesses don’t tell their customers about third-party ad trackers collecting their data.

Another reason is privacy invasion. Businesses managing third-party cookies track user activities on the web and then often sell the collected data without the consumer being aware of it.

Third, there is a big risk behind personal data storage. The data could be leaked or fall into the hands of scammers.

Nevertheless, the positive changes regarding the data collection are already happening. Google announced that it will stop the use of third-party cookies in Chrome by the end of 2023. Apple, in its turn, within iOS 14.5 and latest versions, implemented the requirement to ask users for permission to track them across apps and websites. Moreover, there are several solutions on the market to collect the users’ data harmlessly. However, it is still unclear whether some of these solutions are entire “non-cookie based” or a combination of methods.

In a world where people are sensitive about their data protection must exist an ethical solution. And that’s how the zero-party data gets in the game.

What is zero-party data?

Imagine a world where the users can voluntarily and proactively share their data, deciding to whom and what kind of information to provide transparently. Such data is considered as zero-party data.

What differentiates zero-party data from first, second, and third-party data is the customer-centricity, transparency, and respect for the intentions of the customer.

There are several principles on which zero-party data is based:

Transparency of data collecting process

One of the requirements of GDPR is transparency while collecting data. What does this mean? When a company asks its web visitors for some additional information, it clearly states what information will be kept and how it will be used.

Transparency when utilizing data

Transparency when utilizing data means a company respects customers decision to reinforce their zero-party data and helps to do that. The customer doesn’t need to do anything excessive – a simple message addressed to the brand must be enough.

Letting customers change their decision

The customer’s preferences can change. The ability to change user preferences will not only benefit businesses but improve the service and tighten the business-customer relationship.

GDPR

How to get zero-party data and use it?

So we learned what zero-party data is. Now there is a question: how to collect it? It might not be as easy as it seems. The main challenge is to build the customer trust before they would consider sharing with the brand their personal information. But as a bonus, the company will receive valuable, trustworthy data!

There are several ways in how zero-party data can be collected.

Discovery experience

Discovery surveys and quizzes could be an option to help customers receive a personalized experience. Thus, brands explicitly ask their web visitors about their preferences to offer a particular product according to the survey results.

Some companies, like NARS Cosmetics, already implement the quizzes as a part of their zero-party data collection strategy. Their survey “Lip shade finder quiz“ interrogates the consumer about their mood, beauty mantra, going-out look and skin tone, and other questions via mail. After the company receives the survey results, they provide their customers with recommendations on the products.

Custom product

This method is a bit similar to the previous one. In this case, companies create an absolutely new product or service according to the customer preferences.

Proven Skincare uses this method. They invite their customers for the “Skin quiz”. After receiving quiz answers, Proven Skincare creates a personalized skincare routine for each customer.

Personalized offer

Unlike the previous ones, this method focuses on learning who the customers are. The main prerequisite is customer trust and loyalty. Customers, in their turn, will appreciate the special attention they receive. It works on the exchange base: consumers share their basic information such as date of birth, profession, name, and email, and in return, they receive a small award.

For example, Starbucks offers a free drink to the members of the “Starbucks reward account” on their birthday.

Preference centers

Many brands have already been using preference centers for a long time. This strategy creates a users’ database where they can voluntarily share their interests. Think about Spotify: when the user signs up for the first time, they choose the preferred artists, so the app can recommend other music. Same with Pinterest: it suggests choosing topics the user likes and automatically selecting the pictures for them. Amazon, for one, has an advanced preference center, where users can fill it up with information about their interests and modify it. Accor Group suggests their loyalty program members mention their interests and use them to create a better guest experience.

And this is not the final list. Soon there will be more zero-party data collection methods.

A critical point of view: challenges

Despite the fact that zero-party data makes an impression of the good resolution of personal data collection, there are still some challenges.

One of the biggest challenges will be encouraging customers to provide their data. The brands would have to ensure that this is for their own benefit.

This leads to the second issue: didn’t the exact same thing happen with the third-party cookies collection? Marketers used to claim that third-party cookies actually benefit their customers...

We would have to find a way to ask customers for their data ethically and without pressure.

Another challenge is the way the brands inform about zero-party data collection. In all examples listed in this article, companies only indirectly ask their customers to consent for zero-party data collection. It’s doubtful that users were clearly informed about the method and purpose of their data usage.

Consequently, it might be suggested that despite all the good intentions of zero-party data, there is still room for abuse. Just like with any other personal data, zero-party data requires protection as it can be leaked or sold to scammers.

Bottom line

Despite all the doubts, the world is changing and becoming safer for private data. Indeed, the old unethical data collection method will be a lesson for the future for marketers. Zero-party data is a new beginning that will pave the path to other more ethical marketing and data collection methods.

In one of our previous editions, we discussed the different data privacy regulations around the globe. Despite some differences, they have the common purpose of protecting user privacy. Another radical change that has affected the advertisement world is the 3rd party cookies policy, which will be regulated according to the privacy laws, as well as the latest iOS implementations that curtails advertising data.

The new regulations provoked concerns in the advertising industry. Marketers are no longer able to collect user data in the same way as previously. The privacy data regulations demonstrated how vulnerable the marketing industry actually is. For one, the billion-dollar company Facebook in just a few months suffered a double-digit drop in advertising revenue, meanwhile, their targeting is continually becoming less accurate. Moreover, most MarTech companies still rely on cookies in some form. Google announced back in January 2020 that it would remove 3rd party cookies from Google Chrome in 2023 (the date has been postponed in the meantime). So what will happen in the industry in 2022?

Cookieless world

Cookies are a relic from the desktop world. They are a “simple technology” used to collect extensive data about users’ online behavior, which advertisers can use to learn more about their customers and develop targeted offers for them.

However, customers are increasingly concerned about who and what, in what way, and what kind of information is collected and sold. The main problem with cookies is not personalization: customers have little objection to needs-based advertising and product offers. Their objection lies with privacy and a lack of control over their data.

Adello has been developing targeting technology that does not rely on cookies since inception in 2008. The idea that mobile marketing deserves a better solution than the prevailing “desktop goes mobile” approach, which relies only on cookies and clicks, stems from founder Mark E. Forster’s background in app development and his interest in analytics and data. Not relying on cookies proved to be the right move in the long term, considering that cookieless approaches are now the focus of all major MarTech companies.

Fortunately, authorities around the world respect user privacy; Apple, one of the industry leaders, has moved to handle advertising data more strictly in the newer iOS versions. For cookies, this means the end in the long run.

What are the expected changes in a cookieless world, and how will 3rd party cookies policies look like?

The new regulation requires asking users about their consent before storing or accessing information. The principle of user consent is freedom, specification of information, and it has to be based on an explicit affirmative action. EU Data protection authorities are aware that 3rd party cookies restriction can complicate the work of businesses, which used this technology before. Therefore, authorities released recommendations on the alternative methods to get user consent.

EU recommendations

Previously, visiting websites, users could see a pop-up banner where one could choose to accept cookies or decline with minimum to no additional information about cookie policy. Now EU websites should comply with the following three conditions:

Many companies have already started reworking their websites. According to the report, cookies are down by 22% across news websites. However, the majority of the websites are still using 3rd party cookies and do not meet the GDPR requirements yet. Advertisers working with non-compliant publishers put themselves at risk.

Alternatives

The end of cookies does not necessarily mean that advertisers have to move away from personalization entirely. The challenge is to find an approach that is both efficient and ethical.

The good news is that there are several alternatives. Adello, for example, has never used 3rd party cookies but developed AdCTRL™ starting in 2011. The name derives from the objective at the time: End users should have control over whether and what kind of advertising is desired. Originally, an app was developed for iOS and Android where in cooperation with all publishers the consent and rejection to advertising should be shared. However, since there was no cooperation with the publishers (respecting that users may not be shown any ads at all proved to be a critical point), the technology pivoted towards sustainable data collection for precise targeting.

Technology for a Cookieless and Privacy-Friendly World

Here are the main targeting alternatives:

Probabilistic methods

For probabilistic methods, the systems detect different sorts of data points in order to identify the personality as best as possible. This is usually achieved by blending a combination of observed behavior with “soft identifiers”.This includes device type, publishers visited, on-site behavior, and the IP address. This method aims to provide tracking and attribution.

Deterministic data is difficult to collect. The challenge of the probabilistic method now is to identify a unique user, which in turn is not privacy-compliant. It’s a fine line that companies like Drawbridge in the U.S. and, more recently, 1+X in Switzerland are walking.

Such solutions are mostly “non-cookie based” and include a combination of methods. Nevertheless, one thing is clear: Probabilistic methods are technically challenging, and the results are not always correct. Many customers have rejected probabilistic methods in recent years.

Unified ID 2.0

In the partnership with Unified ID 2.0, Trade Desk released their own solution for the post-cookies era. Since popular web browsers such as Safari, Firefox, and Google Chrome rejected the cookies, Iteration 2.0 will replace the use of 3rd party cookies with hashed and encrypted email addresses.

The developers claim this ID will remain open and, moreover, will implement significant upgrades to consumer privacy and transparency. This framework can be used by all companies, not just those working with The Trade Desk.

However, this method mirrors the functionality of cookies too. That is the reason Google criticizes Unified ID 2.0, claiming it might be a not sustainable long-term investment.

Advertising ID Consortium (mainly IDentity Link IDL by LiveRamp)

The Advertising ID Consortium is an open and independent group, which is operated by representatives from well-known AdTech companies, such as Index Exchange, LiveRamp, The Trade Desk, dataxu, and others.

The Advertising ID Consortium provides privacy-conscious and people-based interoperability for the advertising ecosystem. The method they suggested is cookies ID utilization via AppNexus’ domain as well as a people-based identifier supplied by LiveRamp’s Identity Link. The idea is to hash login-email data. Also, apply the same hashing method whenever a user receives an advertising email and clicks a link. That hashed information will create an ID that will be captured in local storage and will be turned into a 1st party cookie.

Speaking about disadvantages, same as with previous methods, this solution also uses cookies.

Apple SKAdNetwork

Apple has a range of solutions and one of them is SKAdNetwork (or SKAN). SKAN allows accurate attribution of app installs. This framework includes three main entities:

Publishing app, the ad network which signs the ad, and the app advertisement. The important thing to understand is that the entire process is unrelated to Apple’s device identifier for advertisers (IDFA).

After iOS 15 was released, new versions of SKAdNetwork appeared (now in 3.0). Developers and marketing measurement platforms, such as Appsflyer, Adjust, Kochava, Branch, and others, are using SKAdNetwork, to install validation postbacks, and perform their campaigns on their own.

There are several disadvantages of SKAN. Firstly, it only works for in-app, and secondly, it is designed for iOS. Moreover, the data presented is limited to the 100 campaigns for an app or a network. However, Adello uses SKAdNetwork for in-app solutions and sees this framework as reliable and future-proof.

Adello: AdCTRL™ & Adello Instant Classification «AIC»

Adello AdCTRL™ relied from the very beginning on user consent and observed human behavior in order to maintain privacy. It complies with all applicable data protection laws, including the European Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and the Brazilian General Data Protection Law (LGPD).

Currently, the methods of data processing within AdCTRL™ fall into three main dimensions:

1. Content (publishers). Traditional and proven media planning relied on the selection of relevant environments. Adello extends this with the latest technology, continuously searching and classifying publisher data (mobile sites, apps), so that the system understands the content’s environment, keywords, and ratings. Based on this metadata, it can be checked whether an app is trustworthy or not. Does the app have only 2-star ratings? Is the app is Indonesian, but the ad space is offered in German? The system continuously maintains a content quality index based on different, statistical models. The detailed understanding of content, quality, and environment allows better targeting, is robust and absolutely privacy compliant.

2. Context (contextual, temporal, and spatial data). It’s all about when and where an ad is placed. For example, the time when the ad is posted may very well be relevant for an ad for coffee. Furthermore, the place where the ad is placed contains additional data such as the current weather or the type of location, which can tell something about the behavior of the device in question (Adello has drawn polygons of all major airports, train stations, and most retailers and includes such data). Is the location a coffee shop, an office building, or a residential area? That could play a significant role. This method relies on identifying legitimately available 3rd party data (e.g. weather providers, static data e.g. from OpenData/Statista/Federal Statistical Office) and combining appropriate data with its own data (e.g. polygons) to create an understanding of locations. Thus, the algorithm knows in which situation an advertisement will be served.

3. Behavior: The last dimension is the manner, of human (inter)action. This goes far beyond the click. It starts with technographic information (which device is used with which firmware and browser), through connection speed, response, and dwells times, to interact with content and ads (i.e. swipes and clicks). This provides a good understanding of interests and relevance, i.e. currently observed human behavior, and is used in combination with the two methods described above in real-time. This, of course, requires user consent.

AdCTRL™ was developed for processing large amounts of data in real-time, and patented accordingly. The latest generation of AdCTRL™ provides a robust and future-proof targeting framework - while fully preserving privacy.

Adello Instant Classification AIC is a new, simplified version of the more elaborate classification in AdCTRL™. The main difference is that AIC leverages the power of in-stream data processing to instantly classify users into just three categories (age, gender, interests) without having to draw on all of AdCTRL™’s available historical data. The before and after are largely masked out. This reduction results in a coarser but faster identification with similar accuracy - it is generally superior to current probabilistic methods.

Bottomline

There are currently several alternatives, and there will appear more as soon as companies become privacy-conscious and demand cookieless solutions. The elimination of 3rd party cookies is not the end, but on the contrary, the new beginning of a more ethical, sustainable, and privacy-friendly approach to marketing. Choosing the right tools and adapting them will save you time and increase your competitiveness.

A data strategy that focuses on all customer touchpoints and leverages current technologies is a good first step and important for sustainable digital marketing. In the future, we might well see how giving up cookies might have been a blessing in disguise: the inflection point which allowed the industry to finally achieve fast and qualitative growth.

Copyright 2008 - 2022 © Adello