Custom solution / Publisher × AI
Managing monetization with AI agents
Epicflare designs and develops specialist AI agents to combine monetization analysis, explain performance gaps and coordinate action tracking. The solution produces documented findings and priorities for publisher teams to review and act on.
AI monetization management
Custom solution · English · PDF · 1 page
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Watch the demo
A publisher asks their AI assistant to audit a Google Ad Manager setup after a drop in programmatic revenue. Specialist agents review performance, configuration, ad requests and consent signals, then deliver an audit report that separates findings from points still to confirm, with a prioritized action plan.
Read the transcript
Revenue drops or technical issues. Investigating problems in Google Ad Manager takes time away from AdOps teams. Specialized agents, such as Epicflare’s, can handle these investigations, bringing together the expertise needed to diagnose a wide range of issues.
These agents can be accessed through Claude or ChatGPT. Simply describe the problem in the chat. They then autonomously analyze the key components of your advertising stack, including configuration, performance, ad requests, and more.
Once the audit is complete, the results are delivered directly in the chat. The run summary shows that nearly 70 agents were deployed across more than 150 tasks, with the entire audit taking almost four hours. The detailed breakdown below provides a comprehensive view of the tasks performed.
Then there’s the full audit report, starting with an overview of the findings. The individual tabs provide a detailed breakdown of each analysis. These cover yield, the overall Google Ad Manager configuration, key monetization settings, and a technical review of ad requests and their parameters.
One particularly useful output is the condensed action plan. It sets out the key actions to take, step by step, along with their expected impact.
Work that would normally take several days and require multiple areas of highly specialized expertise can now be completed in a few hours at a lower cost and with a high level of analytical depth.
The challenge
Monetization decisions draw on performance data, ad delivery settings and demand conditions. A useful diagnosis must connect these views, show the supporting evidence and distinguish findings from hypotheses that still need checking.
Solution scope
The approach combines three areas of expertise around a Google Ad Manager connection through MCP, using the reporting, configuration and data available for the project.
Analyst
Examine CPM, fill rate and revenue across sources and segments, alongside viewability and video completion.
AdOps
Review configuration, delivery and ad requests, including technical signals related to consent and ID tracking.
Yield manager
Assess inventory value, demand sources and revenue opportunities.
The analyses are consolidated into findings, hypotheses and recommendations, then prioritized for review.
Sources
Google Ad Manager connection through MCP
- Reporting
- Configuration
- Data
Additional sources included as needed
Specialist AI agents
Analyst
CPM, fill rate and revenue, alongside viewability and video completion
AdOps
Configuration, delivery and ad requests, including consent and ID tracking signals
Yield manager
Inventory value, demand sources and revenue opportunities
Findings
Analyses consolidated into findings, hypotheses and recommendations
Priorities
Prioritized action plan
Teams validate priorities
Tracking
Progress, blockers and observed effects on performance metrics
Deliverables
Documented diagnosis
Performance gaps, relevant segments, supporting data and hypotheses to verify.
Prioritized action plan
Corrections, dependencies and metrics, with a roadmap covering owners, deadlines and milestones.
Improvement tracking
Progress, blockers and observed effects on performance metrics.
Scope and control
This is a custom design and development offering. Its scope depends on available data and access, with additional sources included as needed. Consent and identification analysis concerns technical signals. Teams validate priorities, implement actions and track the results.
The scope, deliverables and success criteria are defined for each engagement before work begins.
What would help your team make better monetization decisions?
Discuss your current reporting, the questions it leaves open and the tools and data available. We can assess a suitable solution scope.