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#

bash

npx skills add nexscope-ai/Amazon-Skills --skill amazon-ppc -g

Two Modes#

ModeWhen to UseInputOutputA — BuildLaunching PPC for a new productProduct info + keywords + marginsComplete campaign blueprint + keyword groupings + initial bidsB — OptimizeImproving existing campaignsCampaign data + search term reports + current ACoSOptimization 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#

text

I'm launching a portable blender on Amazon US. Price: $39.99. Product cost: $8, shipping: $3, Amazon fees: $7.50. Here are my keywords: portable blender, personal blender, smoothie maker. Build me a PPC campaign structure.

text

Use amazon-keyword-research to find keywords for "bamboo cutting board", then build a PPC campaign structure. Product costs $6, sells for $29.99. Brand new product launch.

text

I want to advertise my dog t-shirt (ASIN B0D72TSM62, price $5.99, cost $2). Look at competitors B0CMD17929 and B0B76519ZG, extract their keywords, and build my PPC campaigns.

Mode B — Optimize Existing Campaigns#

text

My PPC ACoS is 58% and my target is 30%. I have 3 campaigns: Auto ($800/month, ACoS 67%), Manual Broad ($1,100, ACoS 48%), Manual Exact ($500, ACoS 33%). Product margin is 54%. Help me optimize.

text

Here's my search term report [paste CSV data]. Break-even ACoS is 40%. Find wasted spend, tell me what to negate and what to migrate.

text

Weekly PPC check: here are this week's search terms with clicks and sales [data]. Add negatives for 10+ clicks with no sales, move 2+ orders to Exact.

Short Prompts Work Too#

text

Help me set up PPC for my product B0D72TSM62

text

My ACoS is too high, help me fix it

text

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:

text

Mode A example:
"I found your product — Paiaite Dog T-Shirt, $5.99 on Amazon. To build your
campaigns, I need three things:
  1. Your product cost per unit (so I can calculate your break-even ACoS)
  2. Your monthly ad budget (so I can size the campaigns right)
  3. Any target keywords or competitor ASINs? (Or I can research for you)"

Mode B example:
"Got it — ACoS is too high. To give you specific actions, can you share:
  1. Your profit margin (or product cost, I'll calculate it)
  2. Which campaigns are running and their rough ACoS?
Search term report data is a bonus but not required to start."

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):

text

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.

DetailHow to Get ItCritical?ASINFrom user's promptHelpfulProduct name and categoryFetch from ASIN or askHelpfulSelling priceFetch from ASIN or ask✅ YesProduct cost (landed)Must ask user✅ YesMonthly ad budgetMust ask user✅ YesAmazon fees (referral + FBA)Estimate ~15% referral + FBA by sizeCan estimateLaunch vs mature productAsk or infer from contextHelpful

Step A2: Calculate ACoS Targets#

Using the formulas from Key Concepts, compute the financial framework that governs all bid decisions:

text

📊 PPC FINANCIAL FRAMEWORK

Selling Price:           $39.99
Total Costs:             $18.50 (product $8 + shipping $3 + Amazon fees $7.50)
Profit Before Ads:       $21.49
Profit Margin:           53.7%

Break-even ACoS:         53.7% (spending ALL profit on ads)
Target ACoS (Mature):    30.0% (keeps ~24% profit margin)
Target ACoS (Launch):    50.0% (aggressive — acceptable for first 4-8 weeks)

Max CPC at Target ACoS:  $1.20 (at 10% conversion rate)
Formula: Max CPC = Selling Price × Target ACoS × Conversion Rate

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.
2. 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.
3. 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: curl -s "https://completion.amazon.com/api/2017/suggestions?mid=ATVPDKIKX0DER&alias=aps&prefix=<URL-ENCODED-KEYWORD>" | python3 -c "import sys,json; [print(s['value']) for s in json.load(sys.stdin).get('suggestions',[])]"

Step A4: Build Campaign Structure and Group Keywords#

Default: 4 campaigns. This is the standard structure for a new product launch:

PriorityCampaignWhat It DoesAlways Include?1Auto DiscoveryAmazon auto-matches your ad to search terms — collects data on what shoppers actually search✅ Yes2Manual ExactYour top 10-15 proven keywords with exact match — highest control, lowest ACoS✅ Yes3Manual BroadAll research keywords with broad match — discovers variations and long-tail terms✅ Yes4Product TargetingShows 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)
2. 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
3. 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 TypeStarting BidAdjust AfterManual ExactAmazon suggested bid or Max CPC (whichever is lower)7 days with 20+ clicksManual Broad70-80% of Exact bid7 daysAuto50-70% of Exact bid7 daysProduct Targeting50-70% of Exact bid7 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).

2. 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).

DetailCritical?NotesCampaign names and types✅ YesAuto/Manual/Broad/ExactOverall ACoS✅ YesAnd per-campaign if availableMonthly ad spend and ad sales✅ YesFor budget efficiency analysisProduct profit margin✅ YesTo calculate break-even ACoSTop spending keywords + their ACoSHelpfulEnables specific bid adjustmentsSearch term report (CSV)BonusEnables keyword funnel analysisCTR and conversion ratesBonusDeeper 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#

text

# ✅ PPC Campaign Blueprint — Ready to Implement

## Financial Framework
Selling Price: $XX.XX | Profit Before Ads: $XX.XX | Break-even ACoS: XX%
Target ACoS (Launch): XX% | Target ACoS (Mature): XX%
Max CPC: $X.XX (at XX% conversion rate)

## How These Campaigns Work Together

Standard: 4 campaigns. If budget is tight, start P1+P2, add the rest later.

  Auto (P1) → finds new search terms        ↓ terms with 2+ orders
  Broad (P3) → tests keywords at wider match ↓ terms with 2+ sales
  Exact (P2) → best keywords, lowest ACoS
  Product Targeting (P4) → ads on competitor pages

Separate campaigns prevent internal competition (bidding against yourself).

## Campaign Setup — Follow This in Seller Central

For each campaign below, create it in Seller Central with these exact settings.
Bids marked "use suggested" mean: use Amazon's suggested bid shown during setup.
If suggested bid > your Max CPC, that keyword may not be profitable — see the
⚠️ flag in the Financial Framework for guidance.

### Campaign 1: [Product] - Auto Discovery (Priority 1)
CAMPAIGN SETTINGS:
  Campaign Name:    [Product] - Auto
  Daily Budget:     $XX
  Start Date:       [today]
  End Date:         No end date
  Bid Strategy:     Dynamic Bids - Down Only

AD GROUP:
  Ad Group Name:    Auto - Discovery
  Default Bid:      $X.XX (use suggested bid × 0.5-0.7)
  ASIN:             [your ASIN]

KEYWORDS:           None — Amazon auto-selects based on your listing

NEGATIVE KEYWORDS:
  [keyword] | Negative Exact
  [keyword] | Negative Exact
  (add all Exact campaign keywords here — prevents Auto from
   competing with Exact on the same terms)

### Campaign 2: [Product] - Manual Exact (Priority 2)
CAMPAIGN SETTINGS:
  Campaign Name:    [Product] - Exact
  Daily Budget:     $XX
  Start Date:       [today]
  End Date:         No end date
  Bid Strategy:     Fixed Bids

AD GROUP:
  Ad Group Name:    Exact - Primary
  Default Bid:      $X.XX (use suggested bid, or Max CPC if lower)
  ASIN:             [your ASIN]

KEYWORDS:
  [keyword] | Exact | $X.XX (use suggested bid)
  [keyword] | Exact | $X.XX
  [10-15 keywords, each with match type and bid]

NEGATIVE KEYWORDS:  None needed (exact match is already precise)

### Campaign 3: [Product] - Manual Broad (Priority 3)
CAMPAIGN SETTINGS:
  Campaign Name:    [Product] - Broad
  Daily Budget:     $XX
  Start Date:       [today or Week 2]
  End Date:         No end date
  Bid Strategy:     Dynamic Bids - Down Only

AD GROUP:
  Ad Group Name:    Broad - Discovery
  Default Bid:      $X.XX (use suggested bid × 0.7-0.8)
  ASIN:             [your ASIN]

KEYWORDS:
  [keyword] | Broad | $X.XX
  [keyword] | Broad | $X.XX
  [15-20 keywords]

NEGATIVE KEYWORDS:
  [keyword] | Negative Exact
  (add all Exact campaign keywords — prevents Broad from competing)

### Campaign 4: [Product] - Product Targeting (Priority 4)
CAMPAIGN SETTINGS:
  Campaign Name:    [Product] - ASIN Targeting
  Daily Budget:     $XX
  Start Date:       [today or Week 2]
  End Date:         No end date
  Bid Strategy:     Fixed Bids

AD GROUP:
  Ad Group Name:    Competitor ASINs
  Default Bid:      $X.XX (use suggested bid × 0.5-0.7)
  ASIN:             [your ASIN]

TARGETS:
  B0XXXXXXXX | [competitor name, price, reviews] | $X.XX
  B0XXXXXXXX | [competitor name, price, reviews] | $X.XX

NEGATIVE KEYWORDS:
  [your own ASIN] | Negative Exact (prevent ads on your own page)

## Negative Keyword Master List (apply to Auto + Broad + Product Targeting)
  [term] | Negative Exact     (irrelevant terms)
  [term] | Negative Phrase     (waste modifiers: free, cheap, used, DIY, etc.)

## Budget Summary
| Campaign | Priority | Daily | Monthly | Role |
|----------|:--------:|-------|---------|------|
| Auto     | P1 | $XX | $XXX | Discover search terms |
| Exact    | P2 | $XX | $XXX | Scale best keywords |
| Broad    | P3 | $XX | $XXX | Test variations |
| Product  | P4 | $XX | $XXX | Competitor pages |
| TOTAL    |    | $XX | $XXX | |

## Launch Schedule
Day 1:  Create P1 (Auto) + P2 (Exact). Check that ads are active.
Day 3:  Check impressions. If very low, your bids are below competitive
        range — increase toward Amazon's suggested bid.
Day 7:  Add P3 (Broad) + P4 (Product Targeting). Review Auto search
        terms — add obvious negatives.
Day 14: Full analysis — migrate winners (2+ orders) from Auto/Broad → Exact.
Day 21: Bid optimization — adjust bids for keywords with 20+ clicks.

---

# 📊 Campaign Design Rationale

## Keyword Sources
[How keywords were discovered — fetch-competitor.sh, autocomplete, etc.]

## Bid Notes
Max CPC (profitability ceiling): $X.XX
Amazon suggested bids for this category typically range $X.XX - $X.XX.
[Flag any keywords where suggested bid > Max CPC and explain the tradeoff]

Mode B Output — Optimization Report#

text

# ✅ PPC Optimization Actions — Ready to Implement

## Priority 1: Immediate Negative Keywords (Do Today)
Add these as Negative Exact in their respective campaigns:
  Campaign "[name]": "term1", "term2", "term3"
  Campaign "[name]": "term4", "term5"
Expected savings: $XXX/month

## Priority 2: Keyword Migrations (This Week)
Move to Manual Exact (and add as negative in source):
  "[keyword]" from Auto → Exact, bid: $X.XX
  "[keyword]" from Broad → Exact, bid: $X.XX

## Priority 3: Bid Adjustments (This Week)
  "[keyword]": $X.XX → $X.XX (ACoS XX% → target XX%)
  "[keyword]": $X.XX → $X.XX (increase — profitable at XX%)
  "[keyword]": PAUSE (XX clicks, 0 sales)

## Priority 4: Budget Reallocation (Next Week)
  Auto: $XX/day → $XX/day (reduce — low efficiency)
  Exact: $XX/day → $XX/day (increase — best ACoS)

---

# 📊 Full Audit Report

## Performance Summary
| Metric | Current | Target | Status |
|--------|---------|--------|--------|
| Overall ACoS | XX% | XX% | 🔴🟡🟢 |
| TACoS | XX% | <XX% | 🔴🟡🟢 |
| Monthly Ad Profit | $XXX | $XXX | 🔴🟡🟢 |
| Budget Utilization | XX% | >90% | 🔴🟡🟢 |

## Keyword Funnel Analysis
[Full table from Step B3]

## Bid Adjustment Details
[Full table from Step B4]

## Week-by-Week Action Plan
Week 1: [specific tasks with expected outcomes]
Week 2: [specific tasks]
Week 3: [specific tasks]
Week 4: [review and next cycle planning]

## Expected Results After 4 Weeks
ACoS: XX% → XX%
Monthly savings: $XXX
Sales increase: +XX% (from better targeting)

---

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.