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@clawic · 收录于 昨天 · 上游提交 2 天前

Paid acquisition strategy, budget allocation, and avoiding common advertising mistakes across platforms

适合你,如果需要在多平台管理广告支出并提高回报率

/ 通过 npx 安装 校验哈希
npx oh-my-skill add clawic/skills/ads
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- clawic/skills/ads
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify clawic/skills/ads
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
14GitHub stars
~1K最小装载
~1K含声明引用
~1K文本包总量
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怎么用

商店整理自技能原文 · 版本 f825206 · 表述以原文为准
它做什么

Claude 会提供付费广告策略指导,包括预算分配、创意优化、常见错误避免,并针对 Meta、Google 等平台给出具体建议。

什么时候触发

当你询问如何投放广告、预算分配或广告优化时触发。

装好后可以这样说
Claude 会解释预算分配原则及保留备用金的必要性。
Claude 会诊断可能的指标陷阱并给出调整建议。
Claude 会按平台给出针对性注意事项。
技能原文 SKILL.md作者撰写 · MIT · f825206
Budget Mistakes
  • Starting with daily budgets too low to exit learning phase — platforms need 50+ conversions/week per ad set to optimize properly
  • Spreading budget across too many campaigns early — concentrate spend to gather statistically significant data faster
  • Killing ads before statistical significance — minimum 100 clicks or 1000 impressions before judging creative performance
  • No contingency for scaling — reserve 20-30% of budget for doubling down on winners mid-month
  • Treating ad spend as expense, not investment — track payback period, not just immediate ROAS
Metric Traps
  • Optimizing for CTR instead of conversion — high CTR with low conversion = curiosity clicks that waste budget
  • Trusting platform-reported conversions — attribution windows vary (7-day click, 1-day view), always cross-reference with actual revenue
  • Ignoring frequency — above 3-4 frequency per week, performance degrades and audience burns out
  • CPA tunnel vision — a $50 CPA is better than $30 CPA if LTV is 3x higher for the $50 cohort
  • Vanity reach metrics — 1M impressions mean nothing if 0 target customers saw the ad
Creative Rules
  • One variable per test — changing image AND copy simultaneously teaches nothing about what works
  • Winning ads fatigue in 2-4 weeks — have next creative batch ready before performance drops
  • Static images often outperform video on cost-per-conversion — test both, don't assume video is better
  • Headlines matter more than body copy — 80% of viewers read only the headline
  • User-generated content style outperforms polished brand creative in most direct response contexts
Audience Strategy
  • Broad targeting often wins at scale — platform algorithms find converters better than manual interest stacking
  • Lookalike audiences need minimum 1000 source users — smaller seeds create unstable lookalikes
  • Retargeting pools need 7-14 day recency caps — beyond that, intent has faded
  • Exclude converters from prospecting campaigns — paying to show ads to existing customers wastes budget
  • Test 1% vs 3% vs 5% lookalikes — tighter isn't always better, depends on market size
Platform-Specific Patterns
  • Meta: Learning phase resets with significant edits — avoid editing during first 50 conversions
  • Google: Search intent beats display reach for direct response — display is for awareness, search is for capture
  • TikTok: First 3 seconds determine everything — hook must be instant, no slow brand intros
  • LinkedIn: CPMs are 5-10x higher — only viable for high-LTV B2B where one customer justifies $200+ CPA
  • YouTube: Skippable ads teach you what hooks work — if they don't skip, your hook is strong
Scaling Pitfalls
  • Increasing budget more than 20-30% per day destabilizes campaigns — gradual scaling preserves algorithm learning
  • Duplicating winning ad sets fragments the audience and causes self-competition
  • Scaling spend without scaling creative — same ads to larger audience = faster fatigue
  • Ignoring incrementality — some conversions would have happened organically, true ROAS is lower than reported
  • Geographic expansion without localization — same ad in new market often fails
Landing Page Impact
  • Ads are only half the equation — a 2x better landing page beats 2x more ad spend
  • Message match: ad promise must appear above the fold on landing page — disconnect kills conversion
  • Page load time over 3 seconds loses 50%+ of paid clicks — optimize speed before scaling spend
  • One landing page per audience segment — generic pages convert worse than specific ones
  • Track micro-conversions (scroll depth, time on page) when sample size is too small for macro-conversions
Attribution Reality
  • Last-click attribution undervalues awareness campaigns — multi-touch attribution or holdout tests reveal true impact
  • iOS 14.5+ broke tracking for ~40% of users — model conversions, don't rely on pixel data alone
  • Offline conversions (calls, in-store) need manual import or integration — otherwise CPA looks inflated
  • View-through conversions are real but overvalued by platforms — weight click-through higher
  • 7-day attribution windows miss longer B2B sales cycles — extend windows or use CRM-based attribution
Testing Framework
  • Always run one control ad — without baseline, you don't know if new creative is better or platform just performed differently
  • Minimum 2 weeks per test — weekday/weekend patterns affect results
  • Document every test with hypothesis, result, and learning — institutional memory prevents repeat mistakes
  • Test audiences before creatives — wrong audience can't be saved by good creative
  • Negative results are valuable — knowing what doesn't work prevents future waste
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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