This document is a summary of the measurement and reporting of Ads Data Hub and
its associated processes.

## Introduction

Ads Data Hub follows industry standards for accessing and querying campaign
level data. This data is sourced from upstream platforms such as YouTube and
in-stream video inventory of Google Video Partners purchased through Google Ads
and Display \& Video 360. These platforms are
accredited by the Media Rating Council (MRC). This accreditation certifies that
Google's measurement technology adheres to the industry standards for counting
interactive advertising metrics, and that its processes supporting this
technology are accurate.

## What's included in the audit process?

The audit is focused on querying event level data sets through the Ads Data Hub
user interface and API, and the integration of non-Google data for the purpose
of retrieving aggregated YouTube in-stream video campaign impressions and
viewability results. This includes:

- Reporting of impressions and viewability related metrics across desktop, mobile web, and mobile application environments net of general invalid traffic^[1](https://developers.google.com/ads-data-hub/resources/description-of-methodology#fn1)^ and sophisticated invalid traffic techniques served using Google Ads and Display \& Video 360.
- Processes to facilitate the matching of unique device identifiers across Google first-party and Google client data.

The following table describes in-scope and out-of-scope traffic.

|   | In-scope | Out-of-scope |
|---|---|---|
| Environments | - Desktop web - Mobile web - Mobile app | - CTV / TVHTML5 - YouTube TV web - YouTube TV app |
| Buying flows | - YouTube sold through Google Ads - YouTube sold through Display \& Video 360 - Google Video Partners (GVP) inventory purchased through Display \& Video 360, and Google Ads. | - Any other inventory not purchased through Display \& Video 360 and Google Ads. For example, YouTube Partner-sold Cross-sell inventory. |
| Ad format | - TrueView: View in-stream ads - Standard in-stream - Bumper ads - In-stream select - Non-skippable in-stream video ads | - In-feed video ads - Masthead video ads - YouTube Shorts - Sponsorship campaigns - Multi-format video ads such as video view campaigns (VVC) and video reach campaigns (VRC) - Any other format not specifically listed as in-scope |

> [!NOTE]
> **Note:** Vendors can integrate reporting from Ads Data Hub; however, vendor reporting of Ads Data Hub data has additional considerations.

The following table describes the metrics available in Ads Data Hub.

| Metric | Reporting method | Google Ads | Display \& Video 360 |
| Impressions ||||
|---|---|---|---|
| Gross impressions | API only | Yes | Yes |
| Net impressions (Net of GIVT) | Derivable | Yes | Yes |
| Impressions (Total Net of GIVT+SIVT) | UI and API | Yes | Yes |
| Total invalid impressions (GIVT+SIVT) | API only | Yes | Yes |
| Gross TrueView: Views | API only | Yes | Yes |
| Net TrueView: Views (Net of GIVT) | Derivable | Yes | Yes |
| TrueView: Views (Total Net of GIVT+SIVT) | API only | Yes | Yes |
| Total invalid TrueView: Views (GIVT+SIVT) | Derivable | Yes | Yes |
| Measurable impressions | UI and API | Yes | Yes |
| Non-measurable impressions | UI and API | Yes | Yes |
| Net non-measurable impressions (Net of GIVT) | Derivable | Yes | Yes |
| Viewable impressions | UI and API | Yes | Yes |
| Non-viewable impressions | UI and API | Yes | Yes |
| Net viewable impressions (Net of GIVT) | Derivable | Yes | Yes |
| Net non-viewable impressions (Net of GIVT) | Derivable | Yes | Yes |
| Measurable rate | UI and API | Yes | Yes |
| Viewable rate | UI and API | Yes | Yes |
| Non-measurable impression distribution | UI and API | Yes | Yes |
| Viewable impression distribution | UI and API | Yes | Yes |
| Non-viewable impression distribution | UI and API | Yes | Yes |

> [!NOTE]
> **Note:** Reservation traffic bought from Google Ads "reserve" or Display \& Video 360 "Programmatic Guaranteed Deals" is included in Ads Data Hub reporting, however, this isn't MRC Accredited. More information on how to identify the specific Reservation type can be found on the [Table Schemas resource documentation](https://developers.google.com/ads-data-hub/reference/table-schemas/advertisers).

## Business Partner Qualification

Ads Data Hub business partners include Advertisers, Agencies, Partners, and
Third-Party Ad Tracking or Ad Serving Vendors^[2](https://developers.google.com/ads-data-hub/resources/description-of-methodology#fn2)^. Google vets the use cases
from all Partners and vets initial qualifications to access the product. All
partners that use Ads Data Hub have read-only access and are able to query
Google ads data or join their own first party data with event level ad campaign
data. Additionally, all partners must agree to Google's terms and conditions
prior to accessing the platform. Google filters invalid traffic on an ongoing
basis.

## Device identifiers

In the context of Ads Data Hub, matching through device IDs is utilized as a
mechanism to map YouTube ad activity served through Google Ads and Display \&
Video 360 (e.g., impressions, clicks, ad interactions) to a list of device IDs
maintained by Agency and Advertiser clients.

## Measurement methodology

Ads Data Hub allows Advertisers, Agencies, and Third-Party Ad Tracking or Ad
Serving Vendors to input their data into BigQuery and join it with event level
ad campaign data. An Ads Data Hub query is aggregated over a group of users,
which allows Google to provide more complete data and still maintain end-user
privacy. Ads Data Hub is two BigQuery projects, connected by an API. Google
uploads and manages Google ads data in one of the projects, while the customer
uploads and manages their own data in their project.

While Ads Data Hub enables customers to do user-level analysis in a
privacy-centric way, this access is very sensitive, subject to ecosystem
changes, and is therefore unusual among Google products. Ads Data Hub can ensure
counting events like impressions and clicks matches other Google reporting, *but
counting distinct user identifiers in Ads Data Hub* may not exactly match unique
counting metrics in upstream Google reporting platforms due to specific
precautions implemented in Ads Data Hub for privacy-related reasons, given the
allowance of event-level data manipulation.

Regarding user matching in Ads Data Hub, users who opt-out of advertising cannot
be matched. Match requests sent from apps are unlikely to match, because mobile
devices isolate app traffic and identifiers. For iOS events, match data must
originate from apps on iOS 14.5+ from users who have granted permission under
Apple's App Tracking Transparency framework.

[Learn more about how Ads Data Hub works](https://developers.google.com/ads-data-hub/)

Ads Data Hub provides access to data from multiple Google products (Display \&
Video 360 and Google Ads), all of which adhere to the
appropriate industry standards for click, viewability, and impression
measurement. As such, Ads Data Hub shares click, viewability, and impression
counting methodology with the products whose data we provide. The details can be
found here:

- [Google Ads Description of Methodology](https://support.google.com/google-ads/answer/2616016)
- [Display \& Video 360 Description of Methodology](https://support.google.com/displayvideo/answer/6343606) (Including Active View Methodology)

Google dynamically optimizes ad placement position to meet advertising goals and
user interaction / consumption patterns.

## Filtration methodology

Ads Data Hub provides a privacy-centric way for Advertisers and Agencies to
query event level data and get aggregated results. Ads Data Hub utilizes the
same AdSpam logs as upstream products such as Google Ads and Display \& Video
360. Refer to the "Filtration" sections within the Description of Methodology
for each of the upstream products.

The filtration methodology reporting is performed with two separate processes,
one that occurs at log-processing time and one that occurs at post-processing
time.

- When processing ad events from ad logs initially, real time joining is performed with joined spam logs to annotate events as spam.
  - Empirically tested methods confirm that this real time joining operation captures about 98% of spam events.
- The post-processing pipeline further performs corrections on processed ad event data. The post processor pipeline looks back a sufficient number of days to ensure that sufficient spam events are captured. This post processor correction pipeline is running daily. This is because there may be situations in which discrepancies may arise in the levels of AdSpam reflected within Ads Data Hub in comparison to upstream platforms due to timing differences. However, internal analyses conducted estimate on average an immaterial level of discrepancy (\<1%) at an event level.
  - Empirically tested methods confirm that this post processor pipeline captures virtually 100% of all available spam event corrections within 7 days time.
- When an event is marked as spam, it is excluded from the official reporting stats query results.

Additionally, when taking all spam processing as a whole, the
impact of ongoing spam revision to MRC metrics is minimal. Empirically tested
methods show sampling despammed impressions one day after the ad events changes
by less than 1% when resampling the same event day on subsequent reporting days.
And again, revision typically ceases in a few days and virtually 100% ceases
within 7 days.

Google monitors spam processing accuracy and impact on a regular cadence.

Google upstream products such as Google Ads and Display \& Video 360 have a
decision rate of 100% (based on the reviewed sampled data). Since Ads Data Hub
utilizes the same AdSpam logs as upstream products, the decision rate for Ads
Data Hub Google first-party traffic is 100%.

### Privacy check filtration

Ads Data Hub's privacy checks apply to the collection of MRC-accredited metrics.
Rows that aren't aggregated enough to protect end-user privacy (must contain
data on 50 or more users), or don't meet Ads Data Hub's other privacy checks,
will be dropped. This applies to filtered row summaries within the query and API
results.

However, the immutable queries that produce MRC-accredited metrics are less
likely to be filtered than custom queries. This is due to the queries using only
a few key slicing dimensions, such as full days or device-type, such that
re-running the queries with variations in parameters is unlikely to accidentally
isolate small groups of users.

The likelihood of the MRC-accredited metrics being filtered from your results
may increase if:

- The campaigns you're measuring have a low number of events, such as in the case of campaigns with low budgets or narrow targeting.
- Custom queries are run and re-run prior to running an MRC query over the same events.

## Changes to the methodology

In the event of changes to the measurement methodology, Ads Data Hub will notify
customers using the
[release notes](https://developers.google.com/ads-data-hub/resources/release-notes), in addition
to Account Manager and Support communications.

## Ads Data Hub reporting

For general information regarding how Ads Data Hub reports data, refer to the
[overview](https://developers.google.com/ads-data-hub/guides/intro).

Find instructions on retrieving viewability and IVT data using the Ads Data Hub
API or UI for various buying frontends in the
[viewability and invalid traffic guide](https://developers.google.com/ads-data-hub/guides/query_viewability_metrics).

*** ** * ** ***

1. Source events will be revised for up to 7 days as part of invalid
   traffic filtration (Google Ad Traffic Quality). While both Ads Data Hub
   and upstream Google platforms use the same primary sources to revise
   invalid traffic over a period of days, until revision has settled the
   exact amount of invalid traffic observed at a given moment may differ. [↩](https://developers.google.com/ads-data-hub/resources/description-of-methodology#fnref1)

2. Third-party Ad Tracking or Ad Serving Vendors are included in the scope of
   this audit, whereas Third-Party Brand Measurement vendors are not. [↩](https://developers.google.com/ads-data-hub/resources/description-of-methodology#fnref2)