About AdRiseLab

Our Story

AdRiseLab was founded by Caner Moral in Ankara, Turkey — built from firsthand experience with the research, production, and review bottlenecks that Meta advertisers face.

After years of managing Meta ad campaigns across e-commerce, SaaS, and agency clients — and watching ROAS tank not because of targeting mistakes but because of creative stagnation — the problem became clear: the algorithm changed, but the tools didn't. Agencies and brands were still using the same slow brief-to-design-to-publish workflow in an era that rewards creative velocity above all else.

AdRiseLab is the platform we wished existed — a workspace that turns product inputs into Meta-ready creative drafts, monitors connected-account performance for fatigue signals, and turns public competitor-ad research into creative hypotheses teams can review and test.

What We Believe

• 01

  Creative is a delivery input.

  Meta's delivery systems use many signals. Creative is one of the inputs teams can directly research, test, and improve.

• 02

  Speed wins.

  Shorter research-to-publish cycles let teams test more hypotheses and respond to performance changes sooner.

• 03

  Tools should be built for how the algorithm actually works.

  Not how it worked two years ago.

What We're Building

The short version: an AI performance marketer for Meta ads. Not a template library and not a design tool — a workspace that closes the loop from research to live campaign.

Today that loop has four working parts, and each one exists because it was a bottleneck we hit ourselves:

• →

  Research. Public competitor-ad data turned into creative hypotheses you can actually test, instead of a swipe file you never open again.

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  Production. A product URL becomes Meta-ready creative drafts — static, video and UGC-style — in the formats and ratios the placements actually need.

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  Launch. Guided campaign setup that publishes to Meta in Paused status, so nothing goes live without a human looking at it first.

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  Monitoring. Connected-account performance watched for fatigue signals, so you refresh creative before delivery drops rather than after.

Where this is going: an operator that can run the loop continuously and propose the next move on its own — while every change that touches spend still waits for an explicit approval. We are building an assistant that earns trust, not an autopilot that spends your budget quietly.

How We Handle Numbers

This industry has a habit of dressing estimates up as measured results. We would rather be useful than impressive, so we label things plainly:

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  Our published benchmarks are modeled planning estimates, not observed medians pulled from customer accounts. Every dataset page says so on the page itself.

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  Our workflow examples are labeled illustrative modeled scenarios. They are not customer case studies and we do not present them as verified results.

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  We do not publish performance guarantees. Nobody can promise a ROAS number for an account they have never seen.

The Team

What We Publish for Free

Most of what we know is public and does not require an account. If you never become a customer, these are still yours to use:

Contact

For partnerships, press, or questions: support@adriselab.com