Helps put ads at most relevant content using ai to match ads with the right content
Ai powered solution for smarter Ad placement
Date
January 2025 - May 2025
Company
BuzzFeed
Scenario
To target Ad campaigns, our team have to manually identify, tag and categorize groups of people. Then it's locked and they cant refresh that pool, making for a exhausting and non scalable process.
Roles
Internal discovery
Benchmark
Interface creation
Internal validations
Handoff
Metrics and continuous improvement
Challenge
Manual campaign setup of the audiences, lack of scalability and expensive third-party targeting tools despite already having the necessary data internally.
Results
+500k/year
in cost reduction
2.5X CTR
on Ad increase
Revenue increase
at Ad campaigns
Before (And why it wasn’t working)
Permutive
Before Reverb, Ad Ops teams had to:
manually define user's demographic attributes.
tag or categorize content to proper atribute them with themes.
create multi-condition logic queries.
iterate multiple times to double-check and produce a usable segment.
constantly update campaigns as new articles were published.
relies on an expensive third-party tool.
In practice, creating a segment required navigating complex data models, taxonomies, and event configurations before even defining the audience.
The result was a workflow that was slow, highly technical, difficult to scale, and expensive to maintain.
Project Goals
Generate contextual audiences quickly
Remove complexity from the process
Scale targeting across all BuzzFeed’s brands
Support privacy-safe advertising.
Reduce reliance on third-party tools
Maintain legacy segments available
The Solution: Reverb
Main table
Create segment with AI
First option will allow you to do a simple prompt. AI will analyse and select matching articles to be your seed articles.
Users can simply describe the audience they want to reach in natural language.
Example: “People interested in home organization and interior design.”The AI analyzes the prompt and correlates it with existing content themes, article embeddings, and audience signals across BuzzFeed’s content ecosystem.
The system then generates a contextual cluster of relevant articles and audiences.
After selecting Seed articles, pick a relevancy score. This will filter how similar the segment must be. Also, this will affect its size; the stricter you are, the smaller the segment pool will be.
Manually input seed articles
Second option will demand a manual selection of the 3 seed articles.
For cases when Ad ops team wants to be specific or already have an idea of articles that are working good in campaigns.
View mode
UX Key Decisions
Start from intent, not data
Users don’t think in signals, taxonomies, or attributes — they think in audiences.
Support multiple mental models
Some users think in concepts, others in examples. We support both.
Balance simplicity with control
Works with minimal input, but allows refinement.
Make the system understandable
Rather than exposing model logic, we make outputs visible.
Enable discovery
Previous tools required knowing what to target.
Shift from setup to iteration
Instant outputs, refine from there.
Make segments dynamic
Continuously updates as new content is published.
Results achieved
Cost reduction of
+500k/year
in third party segment tool cost
Increase on
2.5X CTR
cause smarter targeting means better content relevancy
Revenue increase
better results make for more valuable Ad slots
Platform unification
create segment and manage campaigns at the same tool
Time saving
to go from ad concept to live audience
Simple flow
Easy like Sunday moooorning
