Using AI to Standardize Taxonomy for Increased Ad Revenue

Project Overview

For this project we used the following tools/products: Google Ad Manager 360 (GAM360); GAM API (application programming interface) to automate any bulk action items; and Open AI (Artificial Intelligence tool) to analyze and map website content.

Results: Significant CPM Growth

The results confirmed our hypothesis: Using AI to categorize a website’s content into a secondary taxonomy focused on the advertising industry, did increase programmatic CPMs. See the final section of this article for the associated methods used in this experiment.

Publisher Provided Signals (PPS) are not sent from GAM to Google’s buy side platforms on every ad request. The graph below shows the percentage of the ad requests with PPS present, versus not present:

43% of ad requests included the taxonomy terms associated with the content the user had previously read (through Publisher Provided Signal), while 57% of requests did not include them. With that in mind, whenever PPS were present, there was a significant increase in eCPM:

The eCPM on ADx’s rose from $1.14 up to $1.88, a 65% increase, which translated to an overall 27% revenue increase in Google Adx over the past three months (January 1 to March 23, 2025).

What's next?

As we have shown that advertisement focused taxonomy helped to increase CPM on programmatic ads, we are excited to extend this implementation to more of our existing clients. We also believe the obvious next step is to apply the same methodology, but aimed at direct sold campaigns.

Using an advertisement taxonomy focused on a specific industry and/or an IAB taxonomy to classify the content consistently, will make it easier for ad sales teams to match their direct sold campaigns with the right audience on their websites.

Benefits for ad sales

By using the GAM forecasting tool, advertisers can determine the available ad inventory for each advertisement taxonomy item. This helps with campaign planning and future delivery. The inventory volume of each taxonomy item offers valuable insights into website audience interests and content, making it a crucial component for developing a comprehensive media kit.

Enhanced Ad Relevance

Ads that match to standardized content categories are more likely to resonate with users, improving engagement rates and overall campaign performance. The idea is to improve click-through-rates (CTRs) of direct sold campaigns, with properly targeted ads leading to higher conversion rates.

With better-targeted ads and improved engagement, publishers can achieve higher CPMs, boosting their advertising revenue.

Deeper Dive on Setup & Methods

This was a very detailed experiment that involved many team members and carefully planned out strategies and tactics. Below is a brief description of the overall steps taken to reach our outcomes:

• Each IAB taxonomy item needs to have a matching 1st Party Audience (1st PA) created in GAM
• Each 1st PA was assigned to the matching Publisher Provided Signal (PPS) in GAM. PPS lets publishers scale their first-party audience and contextual data to improve programmatic monetization. This helps publishers make the most of their first-party data for ads personalization in programmatic transactions, and helps buyers understand the inventory they're bidding into.
• Users were identified using Publisher Provided Identifier (PPID), which allows publishers to send Google Ad Manager an identifier unique to the user without using cookies.
• Each user's PPID was assigned to the appropriate first-party audiences based on the taxonomy terms associated with the articles they viewed.
• We implemented automations that trigger whenever an article is published. These automations send the article's headline and body, along with the IAB's audience taxonomy, to an AI service, requesting it to return the relevant taxonomy terms for the article. The identified terms are then stored in the article's data.
• That automation was manually triggered for all the existing articles so that all of them would have their matching IAB’s audience taxonomy terms.
• Each time a new user visits the website, a “profile” in the form of PPID will be created, which will track their interests and purchase intent information. Upon their return to the site, we will be able to recognize the user and target personalized ads accordingly. Additionally, relevant user data will be shared with programmatic buyers through PPS. If the user displays new interests or purchase intent, they will be included in updated 1st party audience segments based on their activity on the website.

Interested in getting started? Get in touch with us today.