Privacy has become one of the main topics in digital marketing over recent years. Following the gradual phase-out of third-party cookies, stricter GDPR requirements, and restrictions on user data collection, the advertising ecosystem is undergoing radical changes.

As a result, marketers face a new reality: there’s plenty of data, but access to it is restricted, familiar tools provide superficial reports, and building full-fledged attribution becomes increasingly difficult.

To overcome this transparency crisis, Google created Ads Data Hub (ADH) — a secure environment with controlled access to event-level advertising logs.

Ads Data Hub — an analytics space for advertising data

Ads Data Hub (ADH) is a Google solution that provides marketers and analysts with controlled access to Google ad logs, including data on impressions, clicks, video views, and conversions, without violating user privacy.

In simpler terms, ADH is a tool for secure analysis of advertising data that operates in Google’s protected environment and allows running analytical queries against aggregated event-level logs, without acting as a centralized data storage. The system enables SQL queries to various ad log datasets, including Google Ads, Display & Video 360, and Campaign Manager 360, combining them within BigQuery under permitted access and aggregation rules.

All this is done without revealing user identities: ADH works with aggregated data, ensuring reporting accuracy while complying with modern privacy requirements.

Why is Ads Data Hub needed, and who benefits from it?

Google created Ads Data Hub as a response to global changes in advertising:

• blocking of third-party cookies by browsers,
• stricter GDPR and CCPA requirements,
• shift to first-party data models.

Traditional analytics systems like Google Analytics 4 (GA4) limit ad data granularity. ADH allows deeper insights: analyzing user interactions at the level of segments, audiences, campaigns, or creatives, without access to personal data.

This solution is suitable for:

• large businesses and brands working with big data arrays;
• agencies creating custom reporting;
• analysts and data engineers who want more accurate insights from Google Ads data.

How Ads Data Hub fits into the Privacy Sandbox strategy

Google is developing the Privacy Sandbox concept — a set of tools and standards that allow advertisers to work with data without violating user privacy.

Ads Data Hub is one of the key components of this ecosystem:

• it replaces traditional cookie-based tracking,
• enables analytics based on aggregated data,
• and ensures advertisers do not gain access to personal identifiers (ID, email, cookies).

Thus, ADH is part of a cookie-less future where marketers continue to receive data but work with it on new, secure principles.

Ads Data Hub comparison with other Google Analytics solutions

Tool	Primary Purpose	Detail Level	Privacy	Data Format
Google Analytics 4 (GA4)	Tracking events and behavior on the site	Medium	High	Events/users
Looker Studio (Data Studio)	Data visualization	Low	Depends on the source	Reports/charts
BigQuery	Big data analytics	High	Depends on configuration	SQL/tables
Ads Data Hub (ADH)	Advertising data analytics without access to personal information	High	Maximum (aggregation)	Aggregated ad data

ADH combines the precision of BigQuery with the security of Privacy Sandbox and is, essentially, an “analytical ad hub” containing data from all Google advertising systems in one place.

How Ads Data Hub works: architecture and principles

To understand how Ads Data Hub functions, consider it as a secure environment for running SQL queries against Google’s ad logs within the Google Cloud infrastructure.

Ads Data Hub provides controlled access to ad logs generated by Google’s advertising platforms, including:

• Google Ads — aggregated data on impressions, clicks, and campaign performance (availability depends on scenario and ADH version);
• Campaign Manager 360 (CM360) — event logs for media campaigns, including view-through conversions and impression frequency;
• Display & Video 360 (DV360) — programmatic campaign logs: reach, impressions, basic media metrics.

You can combine these sources in one environment to see the full picture of advertising effectiveness.

How queries are processed in Ads Data Hub

Data in Ads Data Hub is not uploaded directly as tables or stored as separate datasets accessible to users.

Analytical queries are executed in the Ads Data Hub environment, which uses BigQuery as the computational backend. Users interact with ad logs via SQL queries, and results are returned only as aggregated tables permitted by access and privacy rules.

The process works as follows:

1. The user (analyst or agency) creates an SQL query in the ADH environment.
2. The query runs against event-level ad logs generated by Google platforms.
3. Computations happen on Google’s side, without providing access to raw data or user personal identifiers.
4. Query results are returned exclusively as aggregated data, such as impression counts, CTR by segments, or reach frequency.

The obtained results can be exported to BigQuery and then visualized in Looker Studio or any BI tool.

Aggregation as a key security principle

At the core of Ads Data Hub’s operation is data aggregation. The system does not allow queries that could potentially reveal information about specific users.

To achieve this, several levels of protection are applied:

• Minimum sample threshold: the query won’t execute if the audience is too small (to avoid identification).
• Anonymization: user data is always aggregated (e.g., 1000 video views, not “view by user X”).
• Access control: queries run only within permitted datasets, without the ability to export raw files.

This approach ensures a balance between analytics accuracy and privacy compliance, which is critical for the advertising market today.

Benefits of using Ads Data Hub

This powerful analytics platform helps reveal the full picture of advertising effectiveness by consolidating data from all sources into a single data hub. As a result, companies gain deeper insights into user behavior, better campaign optimization, and confidence in privacy compliance.

Analytics: deeper understanding of user journeys

One of the main advantages of Ads Data Hub is the ability to see advertising effectiveness in full context, regardless of device or platform.

• Cross-device and cross-platform analysis: enables aggregated interaction metrics for audiences across stages and devices, for example, how YouTube video views correlate with banner clicks in mobile apps and subsequent desktop conversions.
• Custom metrics and attribution: unlike standard Google Ads reports, ADH allows creating custom metrics, such as contact frequency before conversion or unique attribution models tailored to your business.
• In-depth audience analysis: analysts can evaluate behavioral patterns of different user segments and build strategies based on real ad data, not generalized metrics.

This paves the way for data-driven marketing, where decisions are based on facts, not intuition.

Privacy: working within modern rules

The advertising world is rapidly moving toward a cookie-less future, and Ads Data Hub already meets these requirements today.

• Full compliance with GDPR and CCPA standards: ADH is built on a privacy-first principle and does not store or process users’ personal identifiers.
• Aggregated data instead of individual profiles: every query returns only generalized statistics, making de-anonymization impossible.
• Secure Google Cloud infrastructure: all data processing occurs within Google’s environment, without exporting sensitive information outside the ecosystem.

Integrations: working with all data in one environment

Ads Data Hub easily integrates with other Google products and business systems, creating a unified analytical space (data hub):

• Google Cloud and BigQuery — for storing and processing large volumes of data;
• Looker Studio (formerly Data Studio) — for building convenient reports and dashboards;
• CRM and first-party sources — for combining Google Ads data with your own customer data.

Efficiency: optimizing campaigns and budgets

Access to accurate and structured ad data enables businesses to make better decisions:

• Budgeting: helps understand which channels and campaigns truly deliver value and allocate investments more efficiently.
• Creative optimization: allows analysis of which formats, messages, or platforms work best for different audience segments.
• Media-mix analytics: simplifies measuring the mutual impact of channels — for example, how video advertising supports search campaigns or remarketing.

Limitations and challenges of Ads Data Hub

Like any professional tool, it has its technical, organizational, and operational features. Understanding these nuances helps realistically assess the resources needed to implement the data hub in your company.

Technical skills required

Ads Data Hub is a data workspace, not a “ready-made dashboard.” To generate reports and analytics, you need:

• to know SQL (query language for databases);
• to understand BigQuery principles and Google Cloud services;
• to have a basic understanding of ad data structure (impressions, clicks, conversions, etc.).

Without technical specialists or analysts familiar with Google Ads data, using ADH can be challenging. Therefore, in many cases, its setup is handled by marketing agencies or data teams.

Minimum sample threshold

To ensure user anonymity, Google has set a minimum sample threshold. This means that if a segment is too small (e.g., fewer than a certain number of users or impressions), the query simply won’t return results.

This approach guarantees privacy-first principles but complicates analysis of narrow segments, such as small remarketing audiences or local campaigns.

Data not in real-time

Another limitation is data update delays. Ads Data Hub does not operate in “real-time reporting” mode: data enters the system with a delay (usually from several hours to a day).

This means ADH is not suitable for operational campaign monitoring, for example, to check CTR or CPA daily. However, it is ideal for deep strategic analytics: media mix effectiveness analysis, attribution model building, and reach or contact frequency measurement.

Does not replace Google Analytics 4 or other systems

It’s important to understand that Ads Data Hub is not an alternative to GA4, but rather its complement. While GA4 shows user behavior on the site or in the app, ADH focuses on ad data from Google’s advertising platforms.

Ideally, these systems work together:

• GA4 provides insights into onsite behavior;
• ADH reveals the user’s path to the site through advertising.

Limited access and connection procedure

Ads Data Hub is not a public tool that can simply be “turned on” in a Google Ads account. Access is granted upon request and is usually available to:

• agencies and large advertisers with significant impression volumes and budgets;
• companies working with Google Marketing Platform (DV360, CM360).

This means that for small or medium-sized businesses, ADH may be unavailable without the mediation of an agency or Google partner.

How to implement Ads Data Hub: quick guide

The first step is to gain access to Ads Data Hub. The tool does not activate automatically: you need to contact your Google representative or Google Marketing Platform partner (like newage. level agencies)

After access confirmation, an Ads Data Hub account is created within your Google Cloud environment. All data is processed inside Google’s secure infrastructure, and only the results of aggregated queries are stored in your Google Cloud.

Next, connect the data sources that will form the basis of your data hub:

• Google Ads — search, display, video advertising;
• Display & Video 360 (DV360) — programmatic and media campaigns;
• Campaign Manager 360 (CM360) — tracking impressions, clicks, frequency.

This will allow consolidating all Google Ads data in one environment for further analysis. It’s recommended to verify access rights immediately — all accounts must be linked to the same Google Cloud project.

BigQuery is the “analytical heart” of Ads Data Hub. This is where all data queries are executed.

• Create a dataset for storing query results.
• Set up access rights for the team or agency.
• Define the table schema — what specific parameters interest you (e.g., date, campaign, device, audience, conversion).

BigQuery allows working with massive arrays of ad data, processing them quickly without needing your own server infrastructure.

At the next stage, an analyst or data engineer creates SQL queries that determine exactly what information you get from Ads Data Hub. For example:

• impression and click counts by campaigns;
• conversion distribution by devices;
• average contact frequency by audience (aggregated);
• creative effectiveness across different audience segments.

The result of each query is an aggregated table without personal data but with all necessary metrics for business analytics. If you don’t have your own SQL specialist, newage. can help create a ready-made library of queries for typical reports.

After obtaining aggregated results from BigQuery, they can be visualized or integrated into other systems:

• Looker Studio (Data Studio) — for creating custom dashboards that update automatically;
• CRM or BI systems — for combining advertising metrics with internal business data (e.g., sales or revenue).

Once dashboards are ready, the most important part begins — analytics and action. Use the obtained insights to:

• assess channel and format effectiveness;
• redistribute budgets between campaigns;
• test new creatives based on data;
• build your own attribution models.

Ads Data Hub is not a one-time report, but an ongoing analytical tool that helps make strategic decisions based on verified data.

A look into the future: Ads Data Hub as the new analytics standard

In a world where third-party cookies are disappearing and privacy is becoming the main value, Ads Data Hub (ADH) is turning into a key tool for the future of marketing.

This is not just another way to report or aggregate metrics, but the foundation for building your brand’s own data model, where every impression, click, or conversion becomes part of a strategic decision-making system.

Companies that invest in the data hub approach today gain a real competitive advantage — analytics that cannot be replicated with standard tools, and the ability to quickly adapt to new privacy-first environment requirements.

Want to integrate Ads Data Hub into your marketing?

The newage. team will help:

• design data architecture and build Google Ads data collection logic;
• create SQL queries for deep analytics;
• build Looker Studio dashboards for real business insights.

Contact us to turn your advertising data into a competitive advantage.

FAQ: Frequently Asked Questions about Ads Data Hub

What is Ads Data Hub in simple terms?

Ads Data Hub (ADH) is Google’s analytics platform that lets you analyze advertising data (ad data) from Google Ads, DV360, and CM360 without access to users’ personal identifiers. All data is aggregated to ensure privacy and GDPR compliance.

How does Ads Data Hub differ from Google Analytics 4?

GA4 shows user behavior on your site or app, while Ads Data Hub focuses on data from Google’s advertising platforms. ADH enables custom SQL queries, building tailored attribution models, and integrating results with CRM or BigQuery. Together, GA4 and ADH provide the full picture — from ad impression to purchase.

Who is Ads Data Hub suitable for?

Ads Data Hub is best suited for large advertisers, agencies, and companies with advanced analytics infrastructure. If you have high traffic volumes, multiple data sources, and a need for deep analysis, ADH is the ideal solution. For small businesses, Google Ads and GA4 are sufficient for now.

Can you connect your own (first-party) data to Ads Data Hub?

Yes. ADH allows combining first-party data (from CRM, ERP, analytics systems) with Google Ads data within BigQuery. This helps better understand customer behavior, conduct lead scoring, and build personalized campaigns without using third-party cookies.

How to get started with Ads Data Hub?

To begin, you need to:

1. Obtain access to Ads Data Hub through your Google representative or partner.
2. Connect Google Ads, DV360, and CM360 accounts.
3. Set up BigQuery and SQL queries for the reports you need.
4. Integrate results into Looker Studio for visualization.

If you need help with setup, the newage. team can design data architecture and automate reporting for your business.