Introduction
In the fast-paced world of programmatic advertising, data is not just another component; it is the engine that drives the entire system and enables the magic of personalization at scale. Without a solid and well-executed data strategy, programmatic would be reduced to undifferentiated inventory buying, losing its ability to target specific audiences with relevant messages. Data is, therefore, the fuel that allows optimizing investment, improving ad relevance for the user, and ultimately maximizing the return on investment (ROI). Understanding where data comes from, how it’s collected, the different types that exist, and the technologies used to manage it is essential to leverage the full potential of programmatic.
Data Collection in the Digital Environment
Every interaction we have in the digital environment leaves a “digital footprint”: visiting a website, making an online purchase, using a mobile application, or interacting on social media. This vast amount of information is collected through various identification methodologies, adapted to different digital environments.
For many years, Cookies have been the predominant identifier in the web environment. A cookie is a small text file that a website installs on the user’s browser to remember information about them, such as Browse preferences, session data, or activity on the site. They are distinguished as first-party cookies, installed by the website being visited, and third-party cookies, installed by other domains (such as advertising service providers) while visiting the main site. For programmatic buying based on third-party cookies to work, companies have developed Cookie Matching techniques, creating mapping tables to relate cookies from the same user across different platforms and thus transfer information about them.
However, the cookie landscape is changing dramatically due to growing user privacy concerns and new regulations (like GDPR and CCPA). Browsers like Safari and Firefox already block third-party cookies by default, and Google has announced plans to phase them out in Chrome. This has pushed the industry to seek alternative identification solutions.
In the mobile application environment, identification is primarily done through Device ID or device ID. These are unique identifiers (such as IDFA on iOS devices or Android Advertising ID) associated with each phone or tablet. These IDs are collected through Software Development Kits (SDKs) integrated into applications.
Some large corporations with a significant volume of logged-in users have developed their own persistent identification mechanisms, known as User ID. These IDs allow associating the activity of the same user across different devices, offering a unified view without relying on cookies or Device IDs.
The industry as a whole faces the challenge of finding a Universal ID, an anonymized personal identifier, static over time and applicable across multiple devices and environments, that allows for user identification in a world without third-party cookies. Various initiatives aim to build these IDs using deterministic data such as email addresses or phone numbers.
It is important to note that the collection and use of data are subject to a strict legal framework to protect user privacy. Regulations like GDPR in Europe require transparency and informed consent for the installation of cookies and the processing of personal data for advertising purposes, with severe penalties for non-compliance.
Types of Data and Their Applications
Data used in programmatic advertising is commonly classified by its origin:
- First-Party Data: This is data that a company or brand collects directly from its own sources, where it has a direct relationship with the user and has obtained their consent (e.g., data from its website, apps, CRM, offline interactions, surveys – Zero-Party Data). It is considered the most valuable and reliable data because it comes from direct interaction with the customer. It can include purchase history, website behavior, demographic data provided directly, etc. The “cookification” of offline data allows linking this information to the user’s online activity.
- Second-Party Data: This is the first-party data of another company with which an exchange agreement is established. Essentially, it’s buying or sharing data directly from a trusted source (e.g., customer data from a non-competing business partner). Although the line with third-party data can be thin in some cases, the key is the direct relationship and mutual agreement.
- Third-Party Data: This is data collected by external providers (Data Suppliers) from multiple sources not directly related to the advertiser or publisher, which they then aggregate, anonymize, and sell as audience segments. This data can include interests, Browse behaviors, estimated demographic information, purchase intent, etc.. While it expands reach, the quality and specificity of segments can vary, especially for very specific niches.
- Zero-Party Data: As mentioned, this is a subcategory of first-party data and refers to data that the consumer intentionally and proactively shares with a brand, often in exchange for a benefit or improved experience. Examples include communication preferences, interests, or demographic information provided in surveys or user profiles.
The strategic combination of these different data types allows advertisers to create rich and detailed audience profiles and target their campaigns more effectively.
Data Management Technologies
To collect, organize, activate, and analyze large volumes of data, the programmatic ecosystem relies on specialized technology platforms:
- Data Management Platform (DMP): A DMP is a platform that collects, stores, organizes, reports on, and exports audience data, primarily third-party data (although it can also manage first-party data). Its main function is to create detailed audience segments based on demographic and behavioral information. Advertisers and agencies use DMPs to enrich their user profiles and improve campaign segmentation in DSPs. Publishers also use them to better understand their audience and optimize the monetization of their inventory by offering qualified segments. DMPs are useful for advanced analysis, such as cross-device and cross-channel attribution.
- Customer Data Platform (CDP): A CDP is a marketing platform that unifies customer data from various sources, both online and offline, to create a complete and unique profile of each customer. Unlike DMPs, CDPs focus more on first-party data and individual-level identification (User ID). They allow companies to have a 360-degree view of their customers, facilitating the personalization of the customer experience across different channels and activating audiences on advertising platforms (by exporting data to DSPs). CDPs are valuable not only for marketing but also for other departments by providing detailed insights into customer behavior.
Data Actors and Suppliers
The rise of programmatic has led to the emergence of an ecosystem of data-centric companies. In addition to technology platforms (DSPs, SSPs, DMPs, CDPs), there are specialized data actors and suppliers:
- Data Actors: These are the various companies operating in the ecosystem that use data for their functions, such as Trading Desks, Ad Exchanges, ad verification companies, etc..
- Data Suppliers: These are companies whose primary activity is to collect data from various sources, create audience segments, and make them available for purchase. These providers are crucial for advertisers who do not have enough quality and volume of first-party data, allowing them to supplement their information with third-party data to expand their reach and improve segmentation. They offer identifiers with information on demographics, interests, location, etc..
Legal Framework: GDPR and Privacy
The processing of personal data in digital advertising is strongly regulated, especially in Europe with the entry into force of the General Data Protection Regulation (GDPR) in May 2018. GDPR aims to give individuals greater control over how their personal data is used and protects their privacy.
The implications for programmatic advertising are significant. Explicit consent from users is required for the collection and processing of their personal data for advertising purposes, including the use of cookies and other identifiers. Platforms and companies operating in the ecosystem must be transparent about their data practices and allow users to exercise their rights (access, rectification, data deletion). Non-compliance with GDPR can result in substantial fines, up to 20 million euros or 4% of the company’s total annual worldwide turnover. This regulation applies to any company processing personal data of residents of the European Union, regardless of where the company is located. Adapting to GDPR has been a continuous process for the industry, driving greater responsibility and transparency in data handling.
Conclusion
Data is, without a doubt, the engine that drives programmatic advertising and enables its unique ability to connect advertisers with the right audiences at the right time. From collecting the user’s digital footprint to activating sophisticated audience segments through DMPs and CDPs, the data lifecycle in programmatic is complex and dynamic. The transition to a world without third-party cookies is reshaping the user identification landscape, increasing the relevance of first-party data and the search for Universal ID solutions. Likewise, the legal framework, led by GDPR, underscores the importance of privacy and informed consent at all stages of the process. To succeed in programmatic, it is essential to master data management, understand its different types, and leverage the available technologies to transform information into actionable insights that drive more effective and personalized campaigns. The power of data in programmatic is immense, and its proper handling is the key to unlocking the true potential of this revolutionary form of advertising.