Amazon PPC Campaign Optimization 📢
Build profitable PPC campaign structures from scratch, or audit and optimize existing campaigns with data-driven bid adjustments. No API key — works out of the box.
Installation
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Two Modes
| Mode | When to Use | Input | Output |
|---|
| A — Build | Launching PPC for a new product | Product info + keywords + margins | Complete campaign blueprint + keyword groupings + initial bids |
| B — Optimize |
Improving existing campaigns | Campaign data + search term reports + current ACoS | Optimization plan + bid adjustments + negative keyword list |
Capabilities
- - ACoS financial framework: Calculate break-even ACoS, target ACoS, and Max CPC from product margins — the foundation for every bid decision
- Campaign architecture design: Build a structured Auto → Broad → Exact funnel with proper negative keyword isolation between campaigns
- Keyword grouping: Organize keywords into campaign buckets with match types and initial bids based on confidence level
- Bid optimization: Apply ACoS-based bid adjustment rules using industry-standard formulas (cut/increase by percentage based on ACoS range)
- Keyword funnel analysis: Identify migration opportunities (Auto→Broad→Exact) and wasted spend (high-click zero-sale terms)
- Negative keyword management: Generate seed lists (cross-campaign, irrelevant terms, generic waste modifiers) and ongoing additions from search term data
- Search term report analysis: Parse user-provided campaign data to find profitable terms, wasteful terms, and optimization gaps
- Competitor ASIN targeting: Build product targeting campaigns aimed at competitor product pages
- Integration chain: Works with amazon-keyword-research for keyword input and amazon-listing-optimization for pre-launch listing quality checks
Usage Examples
Mode A — Build New Campaigns
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Mode B — Optimize Existing Campaigns
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Short Prompts Work Too
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My ACoS is too high, help me fix it
I want to start advertising on Amazon
How This Skill Collects Information
Users rarely provide everything upfront — and they don't need to. This skill follows a progressive information gathering approach:
Step 1: Extract from the prompt. Parse whatever the user already provided — ASIN, price, ACoS numbers, campaign names, keywords, etc.
Step 2: Auto-discover. If an ASIN is given, run the bundled scripts/fetch-competitor.sh <ASIN> to get price, category, BSR, and competitor context. This script handles Amazon's anti-bot protections. If the user mentions a product type without an ASIN, use web_search to understand the market.
Step 3: Identify gaps. Compare what you have against what's needed (see the Required Information tables in Mode A Step A1 and Mode B Step B1 below). Focus on what's critical to proceed:
- - Mode A critical: product costs (to calculate ACoS) + monthly ad budget (to size campaigns) + keywords or competitor ASINs (to build campaigns)
- Mode B critical: current ACoS + profit margin (to know the gap and set targets)
Step 4: One consolidated follow-up. Ask only for missing critical items — in one conversational message, not a questionnaire:
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Step 5: Use estimates when stuck. If the user can't provide something (e.g., doesn't know exact fees), use reasonable category-based estimates and clearly note the assumption. Never block progress waiting for perfect data.
Key Concepts
Three formulas drive every recommendation in this skill. They're introduced here and applied in Step A2 (for Mode A) and Step B2 (for Mode B).
Break-even ACoS = Profit margin before ad spend. If your product sells for $40 with $15 in costs after Amazon fees, your margin is $25/$40 = 62.5%. At 62.5% ACoS you spend all profit on ads — break even.
Target ACoS = Break-even ACoS − Desired profit margin. Want 25% profit after ads? Target ACoS = 62.5% − 25% = 37.5%.
Keyword Funnel = The core PPC optimization loop, applied in Steps A4/A6 (building) and B3 (optimizing):
Auto Campaign (discover new terms)
↓ terms with 2+ orders
Manual Broad (test at broader match)
↓ terms with 2+ sales
Manual Exact (scale winners with precision)
At each step: add the migrated term as NEGATIVE in the source campaign to prevent duplicate spend.
Mode A Workflow — Build Campaign Structure
Step A1: Collect Product Info
The following details are needed. Many can be extracted automatically (see "How This Skill Collects Information" above) — only ask for what's truly missing.
| Detail | How to Get It | Critical? |
|---|
| ASIN | From user's prompt | Helpful |
| Product name and category |
Fetch from ASIN or ask | Helpful |
| Selling price | Fetch from ASIN or ask | ✅ Yes |
| Product cost (landed) | Must ask user | ✅ Yes |
| Monthly ad budget | Must ask user | ✅ Yes |
| Amazon fees (referral + FBA) | Estimate ~15% referral + FBA by size | Can estimate |
| Launch vs mature product | Ask or infer from context | Helpful |
Step A2: Calculate ACoS Targets
Using the formulas from Key Concepts, compute the financial framework that governs all bid decisions:
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If user doesn't know their conversion rate, use category benchmarks: 10-15% is average.
Step A3: Collect Keywords
Keywords can come from three sources (use one or combine):
- 1. From amazon-keyword-research skill (recommended): Run keyword research first, then feed the ranked keyword list into this skill.
- From competitor ASINs: User provides 1-3 competitor ASINs → run
scripts/fetch-competitor.sh <ASIN> for each → extract keywords from their titles and bullet points. The script returns title, brand, bullets, price, category, BSR, and review count. - From user's list: User provides their own keywords (e.g., from Helium 10, search term reports, or manual research).
Additionally, expand keywords using Amazon autocomplete: INLINECODE3
Step A4: Build Campaign Structure and Group Keywords
Default: 4 campaigns. This is the standard structure for a new product launch:
| Priority | Campaign | What It Does | Always Include? |
|---|
| 1 | Auto Discovery | Amazon auto-matches your ad to search terms — collects data on what shoppers actually search | ✅ Yes |
| 2 |
Manual Exact | Your top 10-15 proven keywords with exact match — highest control, lowest ACoS | ✅ Yes |
| 3 |
Manual Broad | All research keywords with broad match — discovers variations and long-tail terms | ✅ Yes |
| 4 |
Product Targeting | Shows your ad on competitor product pages — steals their traffic | ✅ If competitor ASINs available |
If budget is tight: Launch Priority 1+2 first (Auto + Exact). Add Priority 3 after one week of data. Add Priority 4 when you have competitor ASINs identified.
Organize keywords into these campaign buckets:
See the Mode A Output template below for the exact format of keyword groupings per campaign.
Step A5: Set Initial Bids
Max CPC (from Step A2) is your profitability ceiling — not your actual bid. Actual competitive bids depend on the category and keyword competition.
How to recommend bids:
- 1. Calculate Max CPC as the financial guardrail (what you can afford)
- For actual starting bids, tell the user to check Amazon's suggested bid range when creating the campaign in Seller Central — this reflects real auction data
- If Amazon's suggested bid > Max CPC, flag the gap and explain: either accept a loss (ranking launch), raise product price, or skip that keyword
When you don't have suggested bid data, use these category-relative starting points:
| Campaign Type | Starting Bid | Adjust After |
|---|
| Manual Exact | Amazon suggested bid or Max CPC (whichever is lower) | 7 days with 20+ clicks |
| Manual Broad |
70-80% of Exact bid | 7 days |
| Auto | 50-70% of Exact bid | 7 days |
| Product Targeting | 50-70% of Exact bid | 7 days |
Important: These are starting points. The real optimization happens after 1-2 weeks of data — adjust based on actual ACoS per keyword.
Step A6: Build Negative Keyword Seed List
Generate an initial negative keyword list before launch. Three types:
- 1. Cross-campaign negatives: Add all Exact campaign keywords as negatives in Broad and Auto campaigns (prevents internal competition — this is the Keyword Funnel isolation from Key Concepts).
- Irrelevant term negatives: Terms that share words with your product but are wrong category/intent. Example for "bamboo cutting board":
- Wrong material: "plastic cutting board", "glass cutting board"
- Wrong product: "cutting board oil", "cutting board stand"
- Wrong intent: "how to clean cutting board", "cutting board DIY"
- 3. Generic waste negatives: Common low-intent modifiers: "free", "cheap", "used", "DIY", "review", "reddit", "how to"
Step A7: Generate Campaign Blueprint
Compile everything from Steps A1-A6 into the final deliverable. Follow the Mode A Output template in the Output Formats section below.
Mode B Workflow — Optimize Existing Campaigns
Step B1: Collect Campaign Data
The following details are needed. Follow the same progressive gathering approach — extract from the user's prompt first, then ask for missing critical items in one follow-up (see "How This Skill Collects Information" above).
| Detail | Critical? | Notes |
|---|
| Campaign names and types | ✅ Yes | Auto/Manual/Broad/Exact |
| Overall ACoS |
✅ Yes | And per-campaign if available |
| Monthly ad spend and ad sales | ✅ Yes | For budget efficiency analysis |
| Product profit margin | ✅ Yes | To calculate break-even ACoS |
| Top spending keywords + their ACoS | Helpful | Enables specific bid adjustments |
| Search term report (CSV) | Bonus | Enables keyword funnel analysis |
| CTR and conversion rates | Bonus | Deeper performance insights |
Step B2: Performance Audit
Using the ACoS formulas from Key Concepts, analyze across five dimensions: (1) Financial Health — break-even vs current ACoS, monthly profit/loss; (2) Campaign Efficiency — per-campaign ACoS with 🔴🟡🟢 status; (3) Keyword Performance — group keywords by profitable/marginal/unprofitable/zero-sales; (4) Budget Allocation — is spend proportional to revenue? recommend shifts; (5) Missed Opportunities — converting terms not in Manual, high-spend zero-sale terms without negatives, underfunded winners.
Step B3: Keyword Funnel Analysis
Apply the Keyword Funnel from Key Concepts to the user's actual data. Three actions:
- - Migrate up (2+ orders): Auto → Exact or Broad → Exact. Add as negative in source campaign.
- Add negatives (10+ clicks, 0 sales): Add as negative exact or phrase in the source campaign.
- Watch list (<20 clicks): Not enough data yet — flag for next review cycle.
Step B4: Bid Adjustments
Apply ACoS-based bid adjustments to keywords with 20+ clicks (minimum for statistical significance):
- - ACoS > 200%: cut bid 30-50%
- ACoS 100-199%: cut bid 20%
- ACoS target+10% to 99%: cut bid 10-15%
- ACoS at target (±10%): no change
- ACoS below target: increase bid 10-20%
- 10+ clicks with 0 sales: pause keyword
Output a table: Keyword | Current Bid | Current ACoS | New Bid | Reason
Step B5: Generate Optimization Action Plan
Compile everything from Steps B1-B4 into a prioritized action plan. Follow the Mode B Output template in the Output Formats section below.
Output Formats
The primary deliverable is always an actionable campaign plan the seller can implement directly in Seller Central.
Mode A Output — New Campaign Blueprint
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Mode B Output — Optimization Report
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Ongoing Management & Integration
After setup, offer weekly reminders (cron/heartbeat): search term analysis + bid adjustments + monthly full audit. Recommended skill chain: amazon-keyword-research → amazon-listing-optimization → amazon-ppc. Always check listing quality before spending on ads. More skills: Amazon-Skills | eCommerce-Skills
Limitations
This skill uses publicly available data and user-provided campaign reports. It cannot access Seller Central directly, pull real-time bid landscapes, or automate campaign changes via API. For deeper PPC analytics with automated bid management, check out Nexscope — Your AI Assistant for smarter E-commerce decisions.
Built by Nexscope — research, validate, and act on e-commerce opportunities with AI.
Amazon PPC 广告活动优化 📢
从零开始构建盈利的PPC广告活动结构,或通过数据驱动的竞价调整来审计和优化现有广告活动。无需API密钥——开箱即用。
安装
bash
npx skills add nexscope-ai/Amazon-Skills --skill amazon-ppc -g
两种模式
| 模式 | 使用时机 | 输入 | 输出 |
|---|
| A — 构建 | 为新产品的PPC广告活动启动 | 产品信息 + 关键词 + 利润率 | 完整的广告活动蓝图 + 关键词分组 + 初始竞价 |
| B — 优化 |
改进现有广告活动 | 广告活动数据 + 搜索词报告 + 当前ACoS | 优化方案 + 竞价调整 + 否定关键词列表 |
功能
- - ACoS财务框架:根据产品利润率计算盈亏平衡ACoS、目标ACoS和最高CPC——这是所有竞价决策的基础
- 广告活动架构设计:构建结构化的自动→广泛→精准漏斗,并在广告活动之间设置适当的否定关键词隔离
- 关键词分组:将关键词按广告活动分组,并根据置信度设置匹配类型和初始竞价
- 竞价优化:使用行业标准公式(根据ACoS范围按百分比降低/提高)应用基于ACoS的竞价调整规则
- 关键词漏斗分析:识别迁移机会(自动→广泛→精准)和浪费的支出(高点击零销售词)
- 否定关键词管理:生成初始列表(跨广告活动、不相关词、通用浪费修饰词)并根据搜索词数据持续添加
- 搜索词报告分析:解析用户提供的广告活动数据,找出盈利词、浪费词和优化缺口
- 竞争对手ASIN定位:构建针对竞争对手产品页面的产品定位广告活动
- 集成链:与amazon-keyword-research配合获取关键词输入,与amazon-listing-optimization配合进行发布前的Listing质量检查
使用示例
模式A — 构建新广告活动
我正在亚马逊美国站推出一款便携式搅拌机。价格:39.99美元。产品成本:8美元,运费:3美元,亚马逊费用:7.50美元。以下是我的关键词:便携式搅拌机、个人搅拌机、奶昔机。请为我构建一个PPC广告活动结构。
使用amazon-keyword-research为竹制砧板查找关键词,然后构建PPC广告活动结构。产品成本6美元,售价29.99美元。全新产品发布。
我想为我的狗狗T恤做广告(ASIN B0D72TSM62,价格5.99美元,成本2美元)。查看竞争对手B0CMD17929和B0B76519ZG,提取它们的关键词,并构建我的PPC广告活动。
模式B — 优化现有广告活动
我的PPC ACoS是58%,目标是30%。我有3个广告活动:自动(800美元/月,ACoS 67%)、手动广泛(1,100美元,ACoS 48%)、手动精准(500美元,ACoS 33%)。产品利润率是54%。请帮我优化。
这是我的搜索词报告[粘贴CSV数据]。盈亏平衡ACoS是40%。找出浪费的支出,告诉我哪些词需要否定,哪些需要迁移。
每周PPC检查:以下是本周的搜索词及其点击和销售数据[数据]。为10次以上点击无销售的关键词添加否定,将2个以上订单的关键词迁移到精准匹配。
简短提示同样有效
帮我为我的产品B0D72TSM62设置PPC
我的ACoS太高了,帮我解决
我想开始在亚马逊上做广告
本技能如何收集信息
用户很少一次性提供所有信息——他们也不需要这样做。本技能遵循渐进式信息收集方法:
第1步:从提示中提取。 解析用户已经提供的任何信息——ASIN、价格、ACoS数字、广告活动名称、关键词等。
第2步:自动发现。 如果提供了ASIN,运行捆绑的scripts/fetch-competitor.sh 脚本获取价格、类别、BSR和竞争对手背景。该脚本处理亚马逊的反爬虫保护。如果用户只提到产品类型而没有ASIN,使用web_search了解市场。
第3步:识别缺口。 将已有的信息与所需信息进行对比(参见下方模式A步骤A1和模式B步骤B1中的必填信息表)。重点关注关键信息:
- - 模式A关键信息:产品成本(用于计算ACoS)+ 月度广告预算(用于确定广告活动规模)+ 关键词或竞争对手ASIN(用于构建广告活动)
- 模式B关键信息:当前ACoS + 利润率(用于了解差距并设定目标)
第4步:一次性跟进询问。 只询问缺失的关键信息——以一次对话消息的形式,而不是问卷:
模式A示例:
我找到了你的产品——Paiaite狗狗T恤,亚马逊售价5.99美元。要构建你的
广告活动,我需要三样东西:
1. 你的每件产品成本(这样我才能计算你的盈亏平衡ACoS)
2. 你的月度广告预算(这样我才能正确确定广告活动规模)
3. 有任何目标关键词或竞争对手ASIN吗?(或者我可以为你研究)
模式B示例:
明白了——ACoS太高了。要给你具体的操作建议,你能分享:
1. 你的利润率(或产品成本,我来计算)
2. 正在运行的广告活动及其大致ACoS?
搜索词报告数据是加分项,但不是必需的。
第5步:遇到困难时使用估算。 如果用户无法提供某些信息(例如,不知道确切费用),使用合理的基于类别的估算,并明确标注假设条件。永远不要因为等待完美数据而阻碍进展。
关键概念
三个公式驱动本技能中的每项建议。在此介绍,并在步骤A2(模式A)和步骤B2(模式B)中应用。
盈亏平衡ACoS = 广告支出前的利润率。如果产品售价40美元,扣除亚马逊费用后成本为15美元,则利润率为25美元/40美元 = 62.5%。在62.5%的ACoS下,你将所有利润都花在了广告上——盈亏平衡。
目标ACoS = 盈亏平衡ACoS − 期望利润率。希望在广告后获得25%的利润?目标ACoS = 62.5% − 25% = 37.5%。
关键词漏斗 = 核心PPC优化循环,应用于步骤A4/A6(构建)和B3(优化):
自动广告活动(发现新词)
↓ 有2个以上订单的词
手动广泛(以更广泛的匹配进行测试)
↓ 有2个以上销售的词
手动精准(精准扩展赢家)
在每个步骤中:将迁移的词作为否定词添加到源广告活动中,防止重复支出。
模式A工作流程 — 构建广告活动结构
步骤A1:收集产品信息
需要以下详细信息。许多信息可以自动提取(参见上面的本技能如何收集信息)——只询问真正缺失的信息。
| 详细信息 | 获取方式 | 关键? |
|---|
| ASIN | 从用户提示中获取 | 有帮助 |
| 产品名称和类别 |
从ASIN获取或询问 | 有帮助 |
| 售价 | 从ASIN获取或询问 | ✅ 是 |
| 产品成本(到岸成本) | 必须询问用户 | ✅ 是 |
| 月度广告预算 | 必须询问用户 | ✅ 是 |
| 亚马逊费用(推荐费 + FBA) | 估算约15%推荐费 + 按尺寸FBA费用 | 可估算 |
| 新品发布 vs 成熟产品 | 询问或从上下文推断 | 有帮助 |
步骤A2:计算ACoS目标
使用关键概念中的公式,计算控制所有竞价决策的财务框架:
📊 PPC 财务框架
售价: 39.99美元
总成本: 18.50美元(产品8美元 + 运费3美元 + 亚马逊费用7.50美元)
广告前利润: 21.49美元
利润率: 53.7%
盈亏平衡ACoS: 53.7%(将所有利润花在广告上)
目标ACoS(成熟期): 30.0%(保留约24%的利润率)
目标ACoS(发布期): 50.0%(激进——发布前4-8周可接受)
目标ACoS下的最高CPC: 1.20美元(转化率10%)
公式:最高CPC = 售价 × 目标ACoS × 转化率
如果用户不知道转化率,使用类别基准:10-15%是平均水平。
步骤A3