TikTok Ads MENA Creative Decay & Fatigue Benchmark
An illustrative creative-fatigue planning worksheet for TikTok Ads. The included figures are synthetic examples, not measured MENA benchmarks.
Problem it addresses
Provide a planning toolkit with illustrative creative-decay scenarios, a production pipeline planner, and a fatigue-monitoring SOP. The included example values are synthetic and must not be used as regional benchmarks or client forecasts.
Who it is for
PRO operating in high-growth e-commerce, digital publishing, and direct-response marketing across Saudi Arabia, UAE, and Egypt.
What is inside
Key files listed in the README repository architecture:
data/benchmarks_by_country.csvdata/benchmarks_by_industry.csvdata/creative_decay_benchmarks.jsondata/tiktok_mena_benchmarks.jsondocs/methodology-and-sources.mddocs/methodology.mdLICENSEREADME.mdSOURCES.mdtemplates/creative-production-pipeline.mdtests/test_data_integrity.py
How to evaluate and use it
- Read the README first and confirm that the documented problem matches your use case.
- Inspect the listed files to find the data, tools, templates, and tests relevant to your task.
- Follow the repository’s Quick Start and check prerequisites before running commands.
- Compare outputs with documented examples and review limitations before using them in a decision or client workflow.
Quick Start from the README: python -m unittest discover -s tests
Scope and limitations
- Decay Monitoring: Track each campaign against its own spend, audience, and creative baseline; the included scenario values are not evidence of a standard MENA fatigue window.
- Hook Drop-Off Telemetry: Creative decay manifests first in 2-second and 6-second video view completion rates before impacting CPA.
- Dialectal Sound Fatigue: Native Gulf audio trends burn out faster than generic commercial music tracks; rotator tracks sound fatigue separately.
This page summarizes the available documentation; it does not establish performance or business results. Verify data and prerequisites before use.