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Stop Blaming the Video: Diagnose Failing Ad Creatives

A practical skill for diagnosing low-converting ad creatives across e-commerce, short drama, and live commerce—without defaulting to 'the video is bad'.

OpenAgentSkillPublished:

Where this fits

A media buyer pulls up a campaign with a 0.3% CTR and a cost-per-purchase that's doubled week-over-week. The instinct is to blame the video and re-cut it. But the real problem could be the audience targeting, the landing page, or a platform mismatch. This skill gives the agent a structured workflow: it takes the failing creative, delivery data, user feedback, product facts, platform, and time window, and returns problem localization, evidence gaps, platform mismatches, fix priorities, and a new-version task list.

Why agents benefit

  • Separates root causes: It explicitly distinguishes creative, product, audience, landing page, and delivery factors—so the agent doesn't default to "re-cut the video" when the real issue is a weak offer or misaligned targeting.
  • Delivers actionable artifacts: Outputs a breakdown report, differentiated remake plan, shot-by-shot script, generation prompts, and an acceptance checklist—not vague advice.
  • Asks only what changes the outcome: When input is incomplete, it asks at most three targeted questions instead of dumping a long questionnaire on the user.
  • Integrates generation via AI-HIVE OpenAPI: Config queries, reference upload, price snapshots, COST_FIRST/SPEED_FIRST/SUCCESS_FIRST routing, async polling, and download—all handled programmatically.
  • Cost-aware by default: It outputs a reviewable plan first and only submits potentially billable image/video generation tasks after confirmation.

Practical scenarios

E-commerce product with declining ROAS

A DTC brand sees ROAS drop from 3.2 to 1.1 over three weeks. The agent takes the ads, product facts, and platform data, and identifies that the landing page load time and audience overlap—not the creative—are the primary culprits. It produces a fix priority list and a refreshed creative brief.

Short drama (短剧) episode with high views, low installs

A short-drama team has a teaser with high impressions but poor app-install conversion. The skill flags a platform mismatch: the teaser's hook works on one platform's feed but violates another's expectation for vertical, fast-paced storytelling. It generates a platform-specific variant script.

Live-commerce seeding content underperforming

A live-commerce operator's seeding video gets engagement but no cart clicks. The diagnosis separates product-fact issues (price positioning) from creative issues (missing urgency cues) and delivers a revised script with specific prompts for regenerating the creative.

Add it to your agent workflow

Install the skill:

npx skills add wubin1836/ai-hive-agent-skills --skill ad-creative-failure-diagnosis-ai-hive

Minimal input example:

Target: Improve conversion on our TikTok Spark ads for a $29 skincare serum.
Facts: FDA-compliant claims only; no before/after guarantees.
Materials: Three failing ad videos, CTR and CPC export, 12 user comments.
Channel: TikTok, 9:16, 15-30s, English.
Constraints: $500 budget, review by compliance lead, deliver in 48h.

The agent responds with a diagnosis plan, evidence gaps, and a new creative task list.

Compare before adopting

Before adopting, compare against: quality signals (does the diagnosis hold up in real campaigns?), maintenance freshness (the skill references AI-HIVE OpenAPI—check version alignment), alternatives (generic creative-analysis prompts vs. this structured workflow), and workflow fit (does your team already use AI-HIVE, or would they need to onboard?). The skill is explicit about its boundaries—no unauthorized replication, no fabricated claims—which is a good sign for production use.

Why it is worth tracking

The skill addresses a real pain point: most ad-failure analysis is either too generic or too siloed. Its open-source repo (2 stars at time of writing) is early, but the methodology—separating creative, product, audience, landing page, and delivery factors—is sound and transferable. Track it if you build tools for media buyers or content teams; revisit when the repo shows more community engagement or when the AI-HIVE API surface stabilizes. For a deeper look, see the skill profile at https://www.openagentskill.com/skills/wubin1836-ad-creative-failure-diagnosis-ai-hive.

Featured Skill

ad-creative-failure-diagnosis-ai-hive

Skill by wubin1836