The Cookieless Revolution: How Businesses are Embracing the Change?

by Charmee Patel

As the digital advertising industry undergoes a significant transformation, businesses face new challenges in tracking and targeting users due to the deprecation of third-party cookies. This paradigm shift forces companies to rethink their strategies and find alternative approaches to collect, manage, and utilize customer data effectively.

In this blog, we will delve into how the cookie-less world is reshaping the industry and its implications for businesses. We will explore the importance of first-party customer data, data enrichment techniques, strategic data partnerships, and the adoption of customer data platforms (CDPs) and reverse ETL solutions. 

These emerging strategies are helping companies adapt, thrive, and maintain their competitive edge in a landscape where traditional methods of tracking and targeting users are no longer viable.

What is happening in the industry?

As of April 2023, the global number of internet users reached an impressive milestone of 5.18 billion, representing approximately 64.6 percent of the world’s population. Moreover, the compound annual growth rate for internet users was 6% during 2018-2023. 

With more people actively engaging in digital platforms, the need for safeguarding personal information and ensuring user privacy has become paramount in recent years. Browsers have been making changes to address these privacy concerns. Safari and Firefox were among the first to take action, blocking third-party cookies since 2013. 

Google Chrome, the largest browser with a significant market share, has now joined the initiative to phase out third-party cookies. While they were not the first to do so, their decision carries significant weight, given their prominent position in the browser market.

In early 2020, Google introduced the Privacy Sandbox initiative to develop privacy-preserving alternatives to third-party cookies, aligning with the industry-wide trend toward enhanced privacy and user control over data. This decision sparked discussions and led to the popularization of the term “cookie-less world.”

Here is what the timeline for the deprecation of third-party cookies by Google looks like:

As businesses adapt to this new reality, they must prioritize ethical data practices, transparency, and user consent to build sustainable customer relationships in the cookie-less world.

How does it impact companies?

With the deprecation of third-party cookies, targeting ads based on user behavior has become considerably more challenging, requiring businesses to seek novel methods to reach and engage their desired audiences effectively.

One of the notable effects experienced by companies in the cookie-less world is a decrease in ad effectiveness. The absence of third-party cookies diminishes the ability to track and understand user behavior, resulting in ads being less precisely targeted to individuals who have demonstrated genuine interest. 

Furthermore, the loss of third-party cookies has led companies to spend more on other forms of online advertising. While contextual advertising and programmatic buying can help fill the gap, they lack the precision targeting power of third-party cookies. 

First-party data, collected directly from a company’s own customers, enables the most relevant and precise ad targeting. Although building robust first-party data sets requires investment, this approach gives companies the highest quality data about their customers’ interests, needs and behaviors. 

What are companies doing to deal with a cookie-less future?

In the cookie-less world, companies are facing challenges in tracking and targeting users due to the restrictions on third-party cookies. As a result, companies are looking for alternative approaches that have been discussed one by one below:

Shifting their focus to collecting and utilizing first-party customer data

Companies are leveraging data enrichment techniques, which begin with collecting first-party data from all possible internal systems and enriching it further. This data can originate from various sources, including onsite or app engagement, in-person interactions, data from the company’s internal systems, and call center interactions.

Collection, Management, and Stitching of data:

In this cookie-less world, companies have adapted their data collection, management, and stitching practices by adopting alternatives such as first-party data and contextual targeting.

Exploring strategic data partnerships: 

These partnerships allow them to access external data sources for enrichment using data clean rooms. These rooms offer a secure, controlled environment for authorized collaboration on anonymized datasets. However, loss of granularity and specific details might make the process more challenging to understand consumer behavior or preference.

Seeking alternatives to third-party activation platforms like DMPs

Companies are turning to Customer Data Platforms (CDPs) that leverage first-party data, enabling companies to create comprehensive customer profiles and gain insights into customer interactions across multiple touchpoints. 

Another emerging option in the cookie-less world is the adoption of reverse ETL (Extract, Transform, Load) solutions. This helps companies with robust data stacks make their data more accessible and actionable, allowing companies to effectively leverage their first-party data, derive meaningful insights, and make informed decisions.

Several case studies showcase how companies have successfully implemented alternative options in response to the changing landscape of online advertising:

1. Companies focusing on first-party customer data strategy

First-party data encompasses all the information that users willingly provide to companies, such as user registration data, progressive profiling, purchase history, and more. Over the years, It has proven to be a reliable and direct source of data for both brands and customers.

Brands like Nike and Home Depot are actively building meaningful connections with their customers. Nike, for example, has accumulated valuable first-party data from their website, mobile app, and retail stores using their customer data platform (CDP). This data helps Nike gain insights into customer preferences and behaviours, enabling them to personalize experiences and tailor marketing efforts. 

Similarly, The Home Depot has also made significant strides in leveraging first-party data. Using a combination of online and offline data sourced from across its organization, the retailer will enhance its customer data platform (CDP). This will allow them to create personalized campaigns that can be activated within 24 hours, dramatically reducing the previous seven- to 10-day process. Home Depot utilizes this data-driven approach to offer product suggestions to customers, assisting them in completing their projects more efficiently.

2. Companies collecting, managing, and stitching the data

Companies are turning to Customer Data Platforms (CDPs) to ensure clean data, carry out identity management (data stitching), and create audiences for activation across multiple channels. Additionally, companies utilize cohort analysis to connect different data points and group users based on shared characteristics or behaviors.

According to a study by the Harvard Business Review, companies that collect and manage first-party data can expect to see a 23% increase in revenue and a 10% increase in customer satisfaction.

Marriott, the renowned global hotel chain, focuses on gathering data from their hotel guests, loyalty program, and website to enhance the guest experience. 

On the other hand, Disney, a well-known entertainment company, also actively collects and manages first-party data. Disney delivers content through their streaming services like Disney Plus, Hulu and ESPN+, which means they have a mass first-party data with them.

This wealth of first-hand customer information assists Disney in scaling operations, prioritizing workloads, and empowering data analytics and machine learning teams to evolve the business continuously. 

Consequently, Disney must govern this customer data responsibly. Through data compliance programs and policies, Disney ensures customer information security while leveraging its utility.

Through their efforts in gathering and utilizing first-party data, both Marriott and Disney aim to provide their customers with memorable and customized interactions that cater to their unique tastes and interests.

3. Companies using strategic data partnerships (clean rooms, aggregated data, individual-level

Companies have embraced strategic data partnerships that involve clean rooms and aggregated data, where two parties share data for agreed-upon purposes while strictly enforcing data access limitations. These partnerships have improved consumer targeting, advertising, and overall performance.

Importantly, consent plays a crucial role in these collaborations, as no personal information is shared between the parties. The focus is on utilizing aggregated data to gain insights while respecting privacy and maintaining data security.

Amazon’s introduction of AWS Clean Rooms and identity resolution solutions, along with Walmart Connect’s utilization of walled garden clean data rooms for monetizing brand data, exemplify how businesses are preparing for the expected deprecation of third-party cookies and prioritizing data privacy.

In the case of Amazon’s AWS Clean Rooms, the service enables AWS customers to collaborate and analyze combined data sets without revealing the underlying raw data, safeguarding privacy while fostering data-driven insights. 

Similarly, Walmart Connect’s data clean room use case demonstrates how retailers are leveraging aggregated customer data to enhance customer experience (CX) by providing advertisers with the ability to run their own analyses for targeted campaigns, all without compromising individual privacy.

4. Find alternatives to third-party activation platforms (DMPs)

A data management platform (DMP) is a tool that predominantly relies on cookies for activation, allowing it to gather behaviour data from diverse sources, such as online, offline, and mobile channels.

Since they primarily rely on behaviour data, the loss of third-party cookies makes it harder for

DMPs to track users across different websites and devices. Consequently, creating comprehensive and accurate customer profiles becomes more difficult, leading to limitations in targeted advertising and personalization efforts.

But with the end of third-party cookies, it is time to look for alternatives for marketing.

a. CDPs for MarTech heavy companies

For companies that have heavily invested in MarTech, they have chosen to use CDPs to unify and activate customer experience on their platforms. CDPs ingest and unify first-party customer data from multiple sources. It creates a comprehensive customer database accessible by other systems to analyze, track, and manage customer interactions. 

Dick’s Sporting Goods Inc., the largest sporting goods retailer in the United States and a Fortune 500 company has adopted a Customer Data Platform (CDP) for managing its customer data. The strategic implementation of the CDP empowers Dick’s Sporting Goods to deliver more personalized and targeted experiences to its customers, enhancing customer satisfaction and loyalty in the evolving cookieless landscape.

Similarly, NatWest Group, a large financial services company, has also adopted CDP to replace DMPs. This partnership allows it to offer its customers access to a wide range of solutions.

Through the adoption of CDPs, both Dick’s Sporting Goods NatWest Group are enhancing their data management capabilities to deliver more targeted and impactful advertising solutions for their clients.

b. Reverse ETL for companies that are stronger on data stack

Reverse ETL syncs data from the data warehouse back to operational systems, enabling frontline business teams to leverage it for optimized and personalized customer experiences. It allows real-time data activation and analysis at the operational level, empowering teams to make informed decisions and execute personalized marketing campaigns. 

Airbnb, a global hospitality platform, leverages reverse ETL for travel recommendations, accommodations, and promotional offers. Similarly, the music streaming service Spotify generates music playlists based on listeners’ preferences and history and activates using reverse ETL.

How is Syntasa able to help companies?

As your marketing tech stack expands, stitching together data and workflows becomes increasingly complex. You need robust tools to consolidate first-party data across all your source systems. Data quality must be monitored proactively to spot issues before they reach your activation platforms. Too often, teams resort to a patchwork of band-aid solutions for managing data. This creates technical debt and hampers agility.

Syntasa is a leading provider of advanced data analytics solutions that empowers companies to unlock the true value of their data and drive personalized experiences for their customers. With a deep understanding of advertising, digital behavior, and enterprise data sources, Syntasa seamlessly manages, cleanses, and enriches first-party data at scale. Powerful AI detects data quality issues and alerts your team in real-time. This prevents downstream impacts while optimizing data for analytics and activations.

One of Syntasa’s key strengths lies in its ability to seamlessly ingest first-party behavioral data from a wide range of adtech and martech systems. As businesses increasingly focus on aggregating first-party data from multiple internal systems, such as onsite or app engagements, in-person interactions, internal databases, and call center interactions, Syntasa’s adeptness in integrating data from these various channels becomes a highly valuable asset.

Ready to navigate the cookie-less world with ease? Don’t miss out on Part-2 of our exclusive blog, where we delve deeper into how Syntasa helps companies to cope with the cookieless world!

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Charmee Patel

Head of Innovation and Data Science, Syntasa

Charmee Patel leads Product Innovation activities at Syntasa. She has extensive experience synthesizing customer, visitor, and prospect data across multiple channels and scaling emerging big data and AI systems to handle the most demanding workloads. This experience guides her work helping clients deploy innovative ways to apply AI and Machine Learning to their marketing data and developing the next generation Marketing AI Platform.