01 / Monitor
Keep a live watchlist of competitors
Add a competitor once. AdHunter uses structured web data to keep the record useful as their public ad library changes.
COMPETITOR INTELLIGENCE / LIVE WORKSPACE
AdHunter turns public ad data into a working intelligence layer for teams that need to move from “what are they running?” to “what should we learn from it?”
Built for practical research. No invented benchmarks or vanity metrics.
Less tab-switching. More context around the ads shaping your category.
The intelligence layer
AdHunter keeps the workflow close to the evidence: collect public data, search it, notice change, save the useful parts, and ask better questions.
01 / Monitor
Add a competitor once. AdHunter uses structured web data to keep the record useful as their public ad library changes.
02 / Search
Filter by brand, format, country, status, and creative details so the right reference is never buried in a feed.
03 / Spot signals
Separate newly discovered ads from the rest, then use winner signals as a prompt for deeper review—not a promise of performance.
04 / Save
Save useful ads into one working collection with the context you need when briefing your next creative direction.
A calmer research loop
Designed for the moment between noticing a competitor and deciding what deserves a creative brief.
Track public competitor libraries with structured, queryable records.
Search by the dimensions that matter to the question in front of you.
Save the reference, read the current AI analysis, and move with context.
Current AI ad analysis
When an ad needs more than a glance, AdHunter can analyze its visible creative and copy to surface themes, angles, and questions for your team to validate.
Explore the workspaceVisible angle
Generated analysis is a starting point for review, not a performance claim.
Clear by design
AdHunter monitors public competitor ad data from the Meta Ad Library and organizes the results into a searchable workspace.
No. Winner signals are directional context for research. They are not a promise of spend, conversion, or future performance.
Yes. Search the library, inspect newly discovered ads, save references, and use the current AI analysis on an ad when you need a faster read.
Start with the evidence