4.   IP Address and ISP-Based Tracking:

This method adds data provided by Internet Service Providers (ISPs), such as the device's IP address. The IP address remains a valuable parameter, enabling reasonably accurate inferences about the user’s geographic location and creating a contextual profile.

Recently, companies like Utiq have emerged, collaborating with major telecom operators (Deutsche Telekom, Orange, Movistar, Vodafone) to offer unified user consent. Utiq generates a pseudonymized identifier with the user's explicit consent, ensuring no access to personal data, tracking, or profiling.

The key difference between solutions like Utiq and Universal Identifiers lies in the data source. Universal Identifiers rely on user-declared data, such as email addresses, while operator-based technologies generate pseudonymized identifiers from connection data.

Recently, Utiq extended its solution to include home internet connections via routers (Wi-Fi or cable), enabling seamless user identification across mobile and domestic connections. This allows precise, deterministic user identification while ensuring secure, encrypted, and scalable targeting with maximum privacy.

It is important to note that in both techniques the user decides whether to accept to share this information or not in an explicit and declarative way, always safeguarding their privacy and in no case seeing their personal information exposed.

Device vs. Application Tracking

It's crucial to differentiate between tracking based on device information and tracking based on the application being used.

At device level , operating systems like Amazon Fire, Roku, Samsung Tizen, LG WebOS… provide their own Ad IDs and control data availability for app developers. Data availability may vary by ecosystem and device OS.

Apps like Netflix, YouTube, Hulu… use their own tracking strategies, based on a combination of device identifiers with user behavior and consumption data, thus building a detailed profile.

A “collaboration” can be established between applications and devices (OS) to share anonymized data to enrich the user experience, combining Ad ID with contextual information generated by the application used at each moment If the device is owned by the streaming platform (e.g., Roku), integration is complete, granting full access to user data.

These techniques comply with privacy regulations, reduce third-party dependency for tracking, and efficiently personalize user experiences using contextual and behavioral data.

However, persistent market fragmentation, device/application differences, and the technical complexities of adopting these solutions remain significant challenges.

The future lies in a cookie-less ecosystem driven by technologies like those discussed above. Advancements in unique identifiers and predictive models based on user behavior not only enable effective personalization but also ensure privacy and regulatory compliance.

As a result, the way brands interact with audiences continues to evolve, driving constant innovation in this space.