القائمة
Whether to kill or scale a campaign / ad set / creative. Covers kill thresholds with minimum-data guardrails and platform-specific scaling budget-step limits.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
Add conversion measurement to a live ChatGPT Ads campaign - choose between the OpenAI Conversions API (server-side) and the JavaScript Pixel (client-side), define the events that matter, and roll out without delaying launch. Use when setting up ChatGPT Ads tracking, CAPI vs pixel decisions, measuring leads/signups/purchases from ChatGPT Ads, or moving from CTR optimization to conversion-based optimization.
Build, review, and scale a ChatGPT Ads campaign from your existing Google/Meta/Microsoft text ads and website. Use when launching ChatGPT Ads, building a ChatGPT Ads campaign workbook, repurposing existing search/social ads for ChatGPT, writing context hints (not keywords), or scaling to 100+ upload-ready ads. Covers the full 9-step golden-path workflow with copy-paste prompts.
Comparing ad-platform performance with CRM; attribution gaps; 'ad platform shows conversions but CRM shows zero'; UTM/pixel issues; last-click vs data-driven. Covers data-source hierarchy and gap diagnosis.
Defining GTM metrics, pipeline efficiency, AI cost metrics, TTFV, CAC/LTV/NRR, magic number, attribution models, weekly review cadence.
Multi-platform product launches: Product Hunt, Hacker News, BetaList, AppSumo, waitlist, launch day, multi-channel rollout — pre-launch through post-launch.
SPEAR loop for any non-trivial agent task — Scope, Plan, Execute, Assess, Resolve. Prevents the strong-start-weak-finish failure mode by forcing an explicit MECE rubric and a Plan→Execute→Assess inner loop until the rubric passes.
استنادا إلى تصنيف SOC المهني
| name | kill-scale-rules |
| description | Whether to kill or scale a campaign / ad set / creative. Covers kill thresholds with minimum-data guardrails and platform-specific scaling budget-step limits. |
Most teams kill too early (acting on noise) or scale too aggressively (the algorithm can't keep up). These thresholds are calibrated so you act on signal, not noise.
| Timeframe | Kill if | Min data |
|---|---|---|
| 24 hours | Hook rate < 15% | 5K+ impressions |
| 48 hours | CTR < 0.5% | 2K+ impressions |
| 3 days | CPA > 2x target | $50+ spend or 1K+ clicks |
| 5 days | No conversions | 3x target CPA in spend |
| 7 days | CPA trending up 3 consecutive days | Statistically significant data |
| 14 days | CPA 1.5x above target with no improvement | Full test cycle complete |
Never kill before minimum data. Bad decisions from small samples cost more than the extra test spend. If a creative has 800 impressions and 2 clicks, you don't have enough signal to conclude anything — wait.
| Condition | Action | Frequency |
|---|---|---|
| CPA < target for 48h | Increase budget 20% | Every 2-3 days |
| CPA < 50% of target for 72h | Increase budget 30-50% | Every 2 days |
| Winner holds after 3 increases | Duplicate to new audience | Once per winner |
| Creative at 100K impressions | Commission 3 variations | Immediately |
| CPA rises after budget increase | Revert to previous budget, wait 48h | As needed |
If CPA rises >25% within 48h of a budget increase, revert to the previous budget and wait 48h before trying again. The algorithm may need to re-stabilize. Repeated failed scaling attempts on the same creative usually mean the audience is saturated — duplicate to a new audience instead of pushing harder.
Part of the Synter free skills collection — open-source agent skills for advertising, PPC, and marketing automation.
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