Google’s Ads Data Hub is expected to be a future-proof solution for measurement, campaign insights and audience activation, for Google owned and operated properties, like Google.com and YouTube. But many are unaware of the opportunities, and the limitations, of the platform. Here we take a deeper dive into Ads Data Hub.
An introduction to Ads Data Hub
As recently as 2018 Google provided advertisers and agencies with granular DoubleClick media data linked to user IDs, to facilitate deeper campaign analysis than what was available directly from the ad platforms. This was known as Google’s Data Transfer product, which allowed any advertiser with access to their ad platform, and some knowledge of BigQuery, to analyse granular user-level data on their advertising campaigns. In May 2018, following the introduction of the General Data Protection Regulation (GDPR), these user IDs were redacted, meaning Data Transfer as a product had limited use.
Along came Ads Data Hub, a solution that can replace Data Transfer for deeper campaign analysis (originally developed as a YouTube measurement solution). The main difference with Ads Data Hub is that nobody can access these user IDs from Google, retaining the increased level of privacy required by new regulations coming into force. Instead of accessing user IDs directly, we would “query” Google’s database to bring back cohorts of users, at least 50 at a time, without disclosing any personally identifiable information on any of the individuals within that cohort. Essentially this gave advertisers and agencies the ability to conduct deeper analysis on their advertising campaigns, without compromising on user privacy.
Here’s how Geoff Samek, Senior Product Manager, Ads Data and Privacy at Google, describes it: “Ads Data Hub gives advertisers access to detailed, impression-level data about their media campaigns across devices in a secure, privacy-safe environment.”
How it works
On one side, Google houses event-level data from the following ad platforms: Display & Video 360 (DV360), Campaign Manager 360 (CM360), YouTube, and Google Ads. This data is stored in a Google owned cloud database, or “BigQuery project”, and is accessed through queries written in structured query language (SQL). Each platform has its own data table, and can only be joined using a resettable device ID (RDID), and, in the case of DV360 and CM360, an identifier captured as a custom variable. There are some limitations on the data available, such as Google Ads only providing Google Display Network and YouTube data, and DV360 providing non-reserved YouTube data.
On the other side, the advertiser or agency creates their own BigQuery project, which contains advertiser-provided marketing and business data. This will provide an opportunity to join first-party datasets for use cases like linking offline sales to online activity, or provide more insight into in-app impressions and conversions.
Ads Data Hub allows us to join personal, first-party data to Google ad platform data; to query the combined dataset based on both first-party and Google data features; and then return privacy-safe cohorts, as mentioned above. The output of these queries are then made available, either through a data download, used within visualisation tools such as Data Studio, or plugged back into the ad platform for activation.
What Ads Data Hub can do
There are multiple use cases for Ads Data Hub. Broadly speaking these can be split into three areas: Audience, Measurement and Business Data.
Audience focuses on our ability to learn more about the profile of our customer, and use this insight in our campaigns. For example:
- Audience Activation – allows you to create custom audiences from analyses performed using Ads Data Hub, through a combination of DV360, CM360, click, Floodlight or conversion data from Google Ads, along with advertiser first-party data. These audiences can then be used in ad platforms for direct targeting.
- Affinity Propensity to Convert – through existing platform reporting you’re only able to view performance of the affinity or in-market audiences you target. With Ads Data Hub we’re able to view all affinity and in-market segments into which your exposed audiences are bucketed. This can also be viewed by geo, giving us a greater understanding of your customers’ interests.
- Targeted Audience with Retailer Point of Sale (POS) – Ads Data Hub allows you to determine how your digital ads affect offline sales, down to which creative had a greater influence on these sales. You will need to have access to the sales data, the ability to correctly format the data for upload into BigQuery, and an ID that can be matched with your Campaign Manager 360 data.
Measurement provides us with a deeper analysis of our campaigns. For example:
- Aggregated analysis across business units – this analysis provides insights into how conversion rates change when a user is exposed to both branding and direct response marketing, or multiple brands within the same group. This allows for more effective campaign optimisation. Here’s an example of how we helped Paysafe Group learn more about how multi-brand marketing affected performance.
- Viewable impressions to conversion – using Ads Data Hub we’re able to count the number of impressions that led to conversions while filtering for only viewable impressions. This provides a new metric akin to viewable conversion rate.
- Post-campaign impact analysis – the data available in Ads Data Hub provides a granular view of attributes associated with your ads. Using this you can segment customers into groups that help determine effectiveness without the normal requirements of setting up tests in advance of campaign activation.
- Cross-screen YouTube campaign reporting – evaluating cross-screen behaviour can be challenging as customers move between screens in an unpredictable way. Ads Data Hub is uniquely positioned as the only platform to accurately measure this behaviour. Understanding how content is consumed across multiple screens can help optimise your strategy and improve performance.
Business data offers us the chance to maximise our first-party data assets. For example:
- Offline conversion analysis – linking an online Quote ID with an offline converted sale, using a first-party data join, allows you to see which part of your campaign delivered these conversions. For example, we can look at a list of publishers to learn which drove quotes and how many of those quotes turned into conversions, giving us a more valuable view of our marketing activity.
- Profitability analysis – taking the order ID and order value for each online conversion, matching this up with the profit generated on each order, using the order ID as the join, you’re able to identify which media buys drive the highest, or lowest, profit across the sales they contributed to.
Key considerations when using Ads Data Hub
The development of Ads Data Hub is a strong step in the right direction when it comes to offering deeper data analysis, while preserving user privacy. While there are some useful use cases available today, it’s important we take into consideration a few key points:
- Ads Data Hub isn’t for everyone, it’s most effective when running multiple Google platforms, and you’re unable to answer specific business questions using the available in-platform reporting options.
- There is a requirement for specialist resource, such as working with SQL and cloud-based architecture, and a collaborative mindset as you work through problem-solving and solution builds.
- The majority of Ads Data Hub use cases still rely on third-party cookies, which has limitations today in regard to browser and operating system support, as well as long-term viability as third-party cookies are phased out. This is something we’re working closely with Google on to ensure the long-term success of the Ads Data Hub product.