content: audit modules 2-8, fix factual/arithmetic bugs and stale terms#32
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Add docs/CONTENT-AUDIT-MODULES-2-8.md: a full read of all 23 remaining lesson files (modules 2-8), cross-checked against PR #29's claimed fixes, the voice guide, and Module 1's rewritten terminology. Fix the P0 findings from that audit: - 8.2: remove two fabricated Amazon features (a "Bid Simulator" and an "Eligible Impressions" report, both Google Ads terminology that doesn't exist in Sponsored Products), unify three contradictory SOV threshold schemes into one, add the fact card PR #29's own commit message claimed already existed here. - 8.3: fix a Gap Analysis Matrix that contradicted its own scoring rule; four of six rows used labels outside the defined scale. - 3.1: fix a cascading ACoS error (stated 26%, actual ~17%) that threw off two derived comparison multipliers. - 5.1: fix a portfolio budget example that claimed to stay under a ₱2,000 cap while actually totaling ₱2,100. - 5.2: resolve a self-contradiction between "you only pay the daily budget" and a weekly total that included the uncapped over-delivery day; add a fact card, matching this file's own dayparting treatment. - 5.3: fix a Gross Profit table implying two different margins for the same product; state the assumed margin explicitly. - 4.2: fix a ROAS range that didn't invert its paired ACoS range. - 2.3: stop labeling $0/spend rows as "100% ACoS" (undefined, not 100). - 3.3: fix a mislabeled table column, a single month's savings mislabeled as an annual total, an inaccurate video-placement claim, and an unsourced conversion-lift stat. - 6.1, 6.2, 4.4: replace "break-even CPC/bid" with "maximum CPC at target ACoS" to match Module 1's rewritten terminology, and fix a 4.4 cross-reference that skipped Module 5 entirely. - Module 8's three files: fix frontmatter (lowercase xpreward, missing type/estimatedMinutes) that was silently defeating the importer's XP/type/duration values. Voice-guide cleanup (em-dashes, emoji, acronym definitions, missing quiz coverage in modules 2-3) is scoped as its own follow-up phase per the audit doc, given its size. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01QSfREMzPnGxjrUPSbz3PGp
…gress Adds quiz-questions.json coverage for modules 2 (Keyword Research) and 3 (Listing Optimization), which previously had zero quiz coverage. Also picks up the start of a broader em-dash/emoji/acronym cleanup pass across modules 2-8 that's still running. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01QSfREMzPnGxjrUPSbz3PGp
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📝 WalkthroughWalkthroughRevises curriculum lessons across Modules 2–8 with updated instructional content, calculations, terminology, formatting, frontmatter metadata, fact cards, quiz copy, and a new content-audit document. ChangesCurriculum content updates
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Completes the em-dash/emoji removal, per-file acronym definitions, and Quick check + What to read next sections for: all of module 2 (keyword research), all of module 4 (campaign architecture), all of module 6 (bidding lab), and 5.1 (campaign portfolios). Module 4.1 and the module 2/3 quiz additions landed in the prior commit. Modules 3, 5.2, 5.3, 7, and 8 still need this same pass, tracked separately, since this batch hit a session rate limit partway through. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01QSfREMzPnGxjrUPSbz3PGp
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content/curriculum/modules/2-keyword-research/2.1-match-types.mdx (1)
56-83: 🎯 Functional Correctness | 🟠 Major | ⚡ Quick winResolve the contradictory phrase-match example.
Line 71 says
"water bottles"does not match, while Line 81 says plurals are close variants that may match. Mark the table row as a close-variant match so learners receive one rule.🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@content/curriculum/modules/2-keyword-research/2.1-match-types.mdx` around lines 56 - 83, Update the “water bottles” row in the Phrase Match example table to identify it as a possible close-variant match, aligning it with the later explanation that phrase match includes plurals. Keep the other examples and their explanations unchanged.content/curriculum/modules/2-keyword-research/2.3-negative-keywords.mdx (1)
23-49: 🎯 Functional Correctness | 🟠 Major | ⚡ Quick winFix the spend denominator before scaling the waste.
The rows total $119.26, not $1,000. Therefore $44.89 is 37.64% waste—about $376.40 per $1,000 and ₱188,202 per ₱500,000, not ₱22,445. Either rescale the table to $1,000 or change the heading and downstream calculation.
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@content/curriculum/modules/2-keyword-research/2.3-negative-keywords.mdx` around lines 23 - 49, Correct the spend-scaling example in the “Before negatives, $1,000 spend” section: the displayed rows total $119.26, so update the heading and downstream waste calculations to use that denominator, including the per-$1,000 and ₱500,000 figures. Preserve the table values and the stated $44.89 wasted spend.
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Inline comments:
In `@content/curriculum/modules/2-keyword-research/2.1-match-types.mdx`:
- Around line 106-110: In the “When to use it” list, update the fourth bullet’s
heading from “Retargeting” to “Proven-term targeting” while preserving its
existing explanation about capturing best-performing search terms.
In
`@content/curriculum/modules/2-keyword-research/2.2-keyword-research-workflow.mdx`:
- Around line 67-77: Update the Brand Analytics guidance near “Source 2: Amazon
Brand Analytics” to describe Amazon’s Search Frequency Rank as a relative metric
rather than exact search volume. Replace any numeric search-count example with
rank-based examples, or direct readers to a separate source for volume
estimates, while preserving the existing workflow steps.
In `@content/curriculum/modules/3-listing-optimization/3.3-aplus-content.mdx`:
- Around line 138-145: Revise the table and accompanying month-12 explanation in
the A+ content section to clearly identify the 45% and 30% ACoS figures as
hypothetical worked-example assumptions. Reframe “avoidable ad spend” and the
savings claim as modeled potential savings, not guaranteed savings or Brand
Registry’s cost of delay, while preserving the enrollment-cost and Sponsored
Brands context.
In
`@content/curriculum/modules/4-campaign-architecture/4.1-sponsored-products.mdx`:
- Around line 23-27: Update step 2 of the Sponsored Products workflow to
describe choosing a targeting method rather than only choosing keywords, while
acknowledging automatic, keyword, and product targeting options. Keep the
remaining steps unchanged.
- Around line 37-44: Update the placement descriptions to use the official
Sponsored Products buckets: “Top of search,” “Rest of search,” and “Product
Pages.” Keep “Customers who bought this also bought” as an example of a
recommendation module appearing on product pages, not as a placement name.
- Around line 29-31: Keep
content/curriculum/modules/4-campaign-architecture/4.1-sponsored-products.mdx
lines 29-31 unchanged as the baseline explanation. In
content/curriculum/modules/2-keyword-research/2.4-keyword-grouping.mdx lines
17-73 and
content/curriculum/modules/2-keyword-research/2.2-keyword-research-workflow.mdx
lines 172-190, reword the “targeted ad copy” and “write one ad” examples to
reflect a single Sponsored Products model focused on shared search intent, bids,
and reporting rather than custom ad copy per ad group.
In
`@content/curriculum/modules/4-campaign-architecture/4.2-sponsored-brands-display.mdx`:
- Around line 53-67: Update the opening Sponsored Display definition to describe
both product/contextual targeting and audience/behavioral targeting, rather than
presenting it as people-only. Preserve the existing retargeting explanation
while clarifying that SD can target products, categories, and audience
behaviors.
In
`@content/curriculum/modules/4-campaign-architecture/4.3-campaign-structure.mdx`:
- Around line 30-32: Update the campaign-structure lesson and the quick-check
content around the keyword bidding explanation to consistently state that each
keyword can have its own bid, regardless of ad group membership. Clarify that ad
groups organize related keywords and support reporting and management, but do
not prevent keyword-level bid control; apply the same correction to the
referenced duplicate section.
In
`@content/curriculum/modules/4-campaign-architecture/4.4-campaign-architecture-practice.mdx`:
- Line 47: Update Question 4 and its corresponding answer to explicitly request
and use the three direct formula inputs—CVR, price, and target ACoS—for
calculating maximum CPC. Remove any implication that product margin is a direct
input, while retaining it only as contextual guidance for determining target
ACoS if needed; apply the same correction to the referenced answer section.
In `@content/curriculum/modules/5-portfolio-strategy/5.1-campaign-portfolios.mdx`:
- Around line 89-108: Rework the portfolio budget example in the “Portfolio
budget means campaigns inside share a pool” section to describe a period-based
group spending cap rather than a same-day shared daily pool. Remove or qualify
the claim that Campaign A can automatically use the remaining ₱100 in real time,
and separately identify any shared-unspent-budget beta behavior and its
eligibility limits if retained.
In `@content/curriculum/modules/5-portfolio-strategy/5.2-budget-pacing.mdx`:
- Around line 27-48: Update the budget pacing lesson’s “Daily budget, with
over-delivery” explanation and weekly example to teach Amazon’s documented
calendar-month averaging mechanic, including configurable 25% or 100%
overdelivery. Tell learners to verify which overdelivery setting their account
uses, and remove the unsupported uncertainty about reconciliation windows or
fixed caps.
In `@content/curriculum/modules/6-bidding-lab/6.1-bid-strategies.mdx`:
- Around line 132-138: Revise the Fixed Bids and Dynamic Down Only descriptions
to present lower or target ACoS as expected tendencies rather than guaranteed
outcomes: clarify that Fixed Bids cap CPC, while Dynamic Down Only may still
miss target when CVR or auction mix changes. Reframe the comparison as something
to measure during a controlled test, and retain the existing Dynamic Up and Down
tradeoff guidance.
- Line 58: Update the “What it does” explanation in the bidding strategies
module to distinguish Dynamic Up and Down bid changes from placement
adjustments. Describe the dynamic-bidding increase/decrease separately, and
attribute the 900% top-of-search figure only to placement adjustments rather
than presenting it as a dynamic-bid cap.
- Around line 43-50: The fixed-bid ceiling statements in
content/curriculum/modules/6-bidding-lab/6.1-bid-strategies.mdx lines 43-50 and
content/curriculum/modules/6-bidding-lab/6.3-bid-elevator-prep.mdx lines 42-47
must distinguish the base bid from the maximum CPC after placement adjustments.
Update both locations to qualify that the base bid is capped before modifiers,
and state the adjusted max-CPC ceiling separately rather than claiming realized
CPC can never exceed the set bid.
In `@content/curriculum/modules/6-bidding-lab/6.2-placement-adjustments.mdx`:
- Around line 27-29: Update the “Rest of Search” description in the placement
adjustments module to state that Sponsored Products bid adjustments are
supported. Remove the “No adjustment available” wording and revise the tip so it
no longer implies the base bid always applies when no adjustment is set.
- Around line 112-118: Update the top-of-search guidance in the
placement-adjustments content to remove the fixed “2–3x” CTR and CVR claim.
Instruct learners to evaluate Placement Report CTR, CVR, and ACoS for their own
product and campaign before judging performance or setting adjustments.
In
`@content/curriculum/modules/8-competitive-intelligence/8.2-share-of-voice.mdx`:
- Line 161: Revise the lesson statement about competitors “converting better” to
clarify that Amazon does not expose competitor CVR or relevance scores directly.
Frame the conclusion as an inference from your own account’s clicks,
impressions, conversions, and share/rank visibility data, rather than
attributing competitor metrics to your reports.
In `@content/curriculum/quiz-questions.json`:
- Around line 170-176: The quiz question currently recommends negating a
targeted keyword, but negative keywords apply to shopper search terms. Update
the question, answer option B, and explanation to identify the item as a search
term, or revise the recommended action to lowering or pausing the targeted
keyword while preserving the zero-sales and undefined-ACoS guidance.
In `@docs/CONTENT-AUDIT-MODULES-2-8.md`:
- Line 8: Update the Module 8 audit report and the referenced findings to
clearly identify each item as baseline, fixed, or still open. Label the report
explicitly as a pre-fix audit baseline, and mark the already-resolved Module 5
calculation findings accordingly so future work targets only active issues.
---
Outside diff comments:
In `@content/curriculum/modules/2-keyword-research/2.1-match-types.mdx`:
- Around line 56-83: Update the “water bottles” row in the Phrase Match example
table to identify it as a possible close-variant match, aligning it with the
later explanation that phrase match includes plurals. Keep the other examples
and their explanations unchanged.
In `@content/curriculum/modules/2-keyword-research/2.3-negative-keywords.mdx`:
- Around line 23-49: Correct the spend-scaling example in the “Before negatives,
$1,000 spend” section: the displayed rows total $119.26, so update the heading
and downstream waste calculations to use that denominator, including the
per-$1,000 and ₱500,000 figures. Preserve the table values and the stated $44.89
wasted spend.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
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📒 Files selected for processing (21)
content/curriculum/modules/2-keyword-research/2.1-match-types.mdxcontent/curriculum/modules/2-keyword-research/2.2-keyword-research-workflow.mdxcontent/curriculum/modules/2-keyword-research/2.3-negative-keywords.mdxcontent/curriculum/modules/2-keyword-research/2.4-keyword-grouping.mdxcontent/curriculum/modules/3-listing-optimization/3.1-listing-quality-score.mdxcontent/curriculum/modules/3-listing-optimization/3.3-aplus-content.mdxcontent/curriculum/modules/4-campaign-architecture/4.1-sponsored-products.mdxcontent/curriculum/modules/4-campaign-architecture/4.2-sponsored-brands-display.mdxcontent/curriculum/modules/4-campaign-architecture/4.3-campaign-structure.mdxcontent/curriculum/modules/4-campaign-architecture/4.4-campaign-architecture-practice.mdxcontent/curriculum/modules/5-portfolio-strategy/5.1-campaign-portfolios.mdxcontent/curriculum/modules/5-portfolio-strategy/5.2-budget-pacing.mdxcontent/curriculum/modules/5-portfolio-strategy/5.3-seasonal-strategy.mdxcontent/curriculum/modules/6-bidding-lab/6.1-bid-strategies.mdxcontent/curriculum/modules/6-bidding-lab/6.2-placement-adjustments.mdxcontent/curriculum/modules/6-bidding-lab/6.3-bid-elevator-prep.mdxcontent/curriculum/modules/8-competitive-intelligence/8.1-brand-analytics.mdxcontent/curriculum/modules/8-competitive-intelligence/8.2-share-of-voice.mdxcontent/curriculum/modules/8-competitive-intelligence/8.3-competitor-benchmarking.mdxcontent/curriculum/quiz-questions.jsondocs/CONTENT-AUDIT-MODULES-2-8.md
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| - Top-of-search is the most valuable placement: 2–3x higher CTR and CVR | ||
| - Placement adjustments are percentage increases that only raise bids for specific spots | ||
| - Combined with Dynamic Up and Down, adjustments create multiplicative effects (up to 20x) | ||
| - Always calculate your maximum possible CPC before setting adjustments | ||
| - Start conservative (+10–25%), gather data, then increase | ||
| - Monitor ACoS by placement, not just position | ||
|
|
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🎯 Functional Correctness | 🟠 Major | ⚡ Quick win
🧩 Analysis chain
🏁 Script executed:
#!/bin/bash
set -euo pipefail
file='content/curriculum/modules/6-bidding-lab/6.2-placement-adjustments.mdx'
echo '--- file outline ---'
ast-grep outline "$file" --view expanded || true
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echo '--- relevant lines ---'
sed -n '90,140p' "$file" | cat -nRepository: projectamazonph/amph-v2
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#!/bin/bash
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file='content/curriculum/modules/6-bidding-lab/6.2-placement-adjustments.mdx'
echo '--- search for placement uplift claims ---'
rg -n "2–3x|2-3x|placement|ACoS|CTR|CVR" "$file" || true
echo
echo '--- broader module context (first 220 lines) ---'
sed -n '1,220p' "$file" | cat -nRepository: projectamazonph/amph-v2
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🌐 Web query:
Amazon Ads placement report CTR CVR ACoS placement varies by product campaign top-of-search guidance
💡 Result:
The Amazon Ads placement report is a critical tool for analyzing how campaigns perform across distinct surface areas, primarily: Top of Search (ToS), Rest of Search (RoS), and Product Pages [1][2][3]. Because these placements function as separate ad products with varying shopper intent, they rarely share identical performance metrics [3][4]. Key performance indicators (KPIs) in the placement report—CTR, CVR, and ACoS—are analyzed to determine if a campaign is effectively allocating budget [5][6][7]. 1. Top of Search (ToS): Generally delivers the highest visibility and CTR, as it captures high-intent shoppers at the beginning of their buying journey [6][8][4]. While it often converts at a higher rate (CVR) than other placements, it is also the most competitive, typically resulting in the highest Cost-Per-Click (CPC) [3][4]. 2. Rest of Search (RoS): Often acts as a secondary placement with lower visibility [6]. Metrics here frequently show lower CTR and CVR compared to ToS, and if CPCs are not managed correctly, this placement can become a source of inefficient spend and high ACoS [3][4]. 3. Product Pages: Placements that appear on product detail pages. Performance here varies significantly based on product relevance and targeting strategy, often serving as a broader reach component compared to keyword-driven search placements [3][4]. Guidance for Optimization: Advertisers use the placement report to identify inefficient spend—such as high ACoS in Rest of Search—and reallocate budget toward better-performing placements [3][9]. Amazon allows for placement-based bid adjustments (multipliers) of up to 900% for Sponsored Products, enabling advertisers to increase bids specifically for high-performing surfaces like Top of Search [10][8][11]. Before applying significant bid adjustments, it is recommended to gather a statistically significant sample size, often cited as at least 100 clicks per placement, to avoid skewed data interpretations [10]. Integrating these insights allows for a strategy that moves beyond blended campaign ACoS to optimize profitability at the granular, placement-specific level [3].
Citations:
- 1: https://sellermetrics.app/amazon-advertising-reports/
- 2: https://www.sellerapp.com/blog/amazon-advertising-reports/
- 3: https://www.velocitysellers.com/2026/06/07/amazon-sponsored-products-placement-data-deep-dive-2026/
- 4: https://gobrandwoven.com/resources/articles/sponsored-product-ad-placements-amazon/
- 5: https://clearadsagency.com/amazon-reports/amazon-placement-report-purpose-and-how-to-use-them/
- 6: https://ceowebltd.com/blog/how-to-use-amazons-placement-reports-to-adjust-bids/
- 7: https://www.linkedin.com/pulse/sponsored-products-placement-report-muhammad-usman-xhp6f
- 8: https://igppc.com/amazon-top-of-search-placement/
- 9: https://lite14.net/blog/2024/09/21/how-to-use-amazons-placement-reports-to-adjust-bids/
- 10: https://emplicit.co/amazon-placement-bid-adjustments-explained/
- 11: https://amalyze.com/resources/sponsored-success/placement-bid-modifiers
Replace the fixed 2–3x uplift claim. Top-of-search performance varies by product and campaign, so teach learners to use Placement Report CTR, CVR, and ACoS instead of treating a single uplift as a rule.
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In `@content/curriculum/modules/6-bidding-lab/6.2-placement-adjustments.mdx`
around lines 112 - 118, Update the top-of-search guidance in the
placement-adjustments content to remove the fixed “2–3x” CTR and CVR claim.
Instruct learners to evaluate Placement Report CTR, CVR, and ACoS for their own
product and campaign before judging performance or setting adjustments.
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| "question": "A keyword gets 200 clicks and $150 in ad spend, with $0 in sales. What's the right read?", | ||
| "optionA": "Its ACoS (advertising cost of sales, ad spend divided by ad sales) is 100%, which is acceptable", | ||
| "optionB": "It's a strong candidate for a negative keyword. With zero sales, ACoS is undefined, not a fixed percentage, and this spend is pure waste", | ||
| "optionC": "It should be given a higher bid to try to generate a sale", | ||
| "optionD": "Nothing needs to change since spend is under $200", | ||
| "correctAnswer": "B", | ||
| "explanation": "ACoS is spend divided by sales, which is undefined at $0 in sales, not 100%. 200 clicks and $150 spent with zero orders is a clear signal to add this as a negative, not raise its bid." |
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🎯 Functional Correctness | 🟠 Major | ⚡ Quick win
🧩 Analysis chain
🏁 Script executed:
#!/bin/bash
set -euo pipefail
# Inspect the quiz item and nearby questions
sed -n '150,190p' content/curriculum/quiz-questions.json
# Check the curriculum guidance for the intended vocabulary/style
printf '\n--- docs/CURRICULUM-REDESIGN.md (relevant hits) ---\n'
rg -n "search term|keyword|negative" docs/CURRICULUM-REDESIGN.md docs/voice-guide.md content/curriculum -g '!**/node_modules/**' || trueRepository: projectamazonph/amph-v2
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Use “search term” here, or change the action. Negative keywords apply to shopper search terms, not to a bid keyword itself. If this is meant to be a targeted keyword, the right next step is to lower or pause it instead of negating it. content/curriculum/quiz-questions.json:170-176
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In `@content/curriculum/quiz-questions.json` around lines 170 - 176, The quiz
question currently recommends negating a targeted keyword, but negative keywords
apply to shopper search terms. Update the question, answer option B, and
explanation to identify the item as a search term, or revise the recommended
action to lowering or pausing the targeted keyword while preserving the
zero-sales and undefined-ACoS guidance.
Finishes the em-dash/emoji removal, per-file acronym definitions, and Quick check + What to read next sections across the remaining module 3, 5.2, 5.3, 7, and 8 files (modules 2, 4, 6, and 5.1 landed in the prior commit). Also fixes real issues CodeRabbit's live-research review surfaced on top of the already-committed batch: - 2.1: resolved a contradictory phrase-match example, renamed a "Retargeting" bullet that collided with Module 4's actual retargeting definition. - 2.2: replaced a fabricated exact Brand Analytics search-volume figure with the real Search Frequency Rank mechanic (Amazon doesn't expose raw counts), and stopped implying Sponsored Products ad groups carry custom ad copy. - 2.3: fixed a spend-heading/table mismatch that threw off a waste scaling calculation by roughly 3x. - 2.4: reworked the "one ad per group" framing to match how Sponsored Products actually works (no per-group creative). - 3.3: labeled a Brand Registry ACoS comparison as a hypothetical worked example instead of implying guaranteed savings. - 4.1: corrected the targeting-method step and the placement-bucket names to Amazon's actual three reporting buckets. - 4.2: broadened the Sponsored Display intro to cover both its targeting modes, not just audience retargeting. - 4.3: fixed a quick-check answer that contradicted the lesson's own (correct) statement that every keyword can carry its own bid. - 4.4: clarified that margin isn't a direct maximum-CPC input. - 5.1: reworked the portfolio budget example to match Amazon's actual period-cap mechanic instead of implying real-time same-day pooling. - 5.2: replaced a hedged, uncertain over-delivery explanation with Amazon's actual documented mechanic (monthly averaging, 25%/100% configurable over-delivery). - 6.1: separated Dynamic Up and Down's own bid cap from placement adjustments' separate 900% ceiling, and softened two "guaranteed" ACoS/bid-ceiling claims to account for placement adjustments and auction variance. - 6.2: updated Rest of Search, which gained bid adjustment support in 2024, and removed a fixed "2-3x" top-of-search uplift claim. - 8.2: reframed a competitor-CVR claim as an inference from the learner's own account data, since Amazon doesn't expose competitor conversion rates directly. - quiz-questions.json: fixed a question that recommended negating a "keyword" when negatives apply to search terms. - Marked docs/CONTENT-AUDIT-MODULES-2-8.md as a pre-fix baseline so it isn't read as a live list of open issues. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01QSfREMzPnGxjrUPSbz3PGp
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Actionable comments posted: 17
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content/curriculum/modules/5-portfolio-strategy/5.3-seasonal-strategy.mdx (1)
118-135: 🎯 Functional Correctness | 🟠 Major | ⚡ Quick winCorrect the profit metric terminology.
The formula subtracts ad spend, so ₱50,000 and ₱75,000 are profit after ad spend—not gross profit. At a 50% margin, pre-ad gross profit would be ₱100,000 and ₱375,000. Calling the result “Gross Profit” and “total profit” can teach the wrong metric.
Proposed fix
- Gross Profit = (Sales × 50%) − Ad Spend. + Profit After Ad Spend = (Sales × 50%) − Ad Spend. ... -│ Gross Profit │ ₱50,000 │ ₱75,000 │ +₱25,000 │ +│ Profit After │ ₱50,000 │ ₱75,000 │ +₱25,000 │ ... -Even though ACoS went from 25% to 40%, total profit increased by ₱25,000 +Even though ACoS went from 25% to 40%, profit after ad spend increased by ₱25,000🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@content/curriculum/modules/5-portfolio-strategy/5.3-seasonal-strategy.mdx` around lines 118 - 135, Correct the seasonal profit example’s terminology: rename the “Gross Profit” row and the surrounding “total profit” references to profit after ad spend, while preserving the existing formula and values. Clarify that pre-ad gross profit at the 50% margin would be ₱100,000 and ₱375,000, and retain the instruction to recalculate using the actual Q4 margin.content/curriculum/modules/2-keyword-research/2.3-negative-keywords.mdx (3)
158-163: 🎯 Functional Correctness | 🟡 Minor | ⚡ Quick winMake the negative-update schedule unambiguous.
“First 2 weeks” overlaps with “Weeks 2-6,” and “bi-weekly” can mean either twice a week or every two weeks. Use disjoint ranges and write “every two weeks” if that is intended.
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@content/curriculum/modules/2-keyword-research/2.3-negative-keywords.mdx` around lines 158 - 163, Update the negative-update schedule table to use non-overlapping phase ranges, clarifying the boundary between the initial period and Weeks 2–6. Replace “Bi-weekly” in the Mature campaign row with “Every two weeks” to remove ambiguity, while preserving the existing frequencies and time requirements.
13-15: 🎯 Functional Correctness | 🟠 Major | ⚡ Quick winSoften the absolute negative-keyword guidance.
The “never convert,” fixed “20-30” quota, and “single fastest way” language overstates what the examples support. Rephrase these as sample-based underperformance or obvious irrelevance, and remove the hard quota so the lesson doesn’t encourage over-blocking.🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@content/curriculum/modules/2-keyword-research/2.3-negative-keywords.mdx` around lines 13 - 15, Soften the claims in the negative-keyword introduction around “what to block,” “single fastest way,” and any absolute conversion language: describe negatives as terms that underperform in the provided examples or are clearly irrelevant, rather than universally failing. Remove the fixed 20–30 negative-keyword quota wherever it appears in this lesson, preserving guidance to make decisions from observed performance and relevance.
182-182: 🎯 Functional Correctness | 🟠 Major | ⚡ Quick winClarify negative exact behavior Negative exact doesn’t block only the literal query; Amazon also applies close variations. Update the explanation and example so learners don’t treat exact negatives as byte-for-byte only.
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@content/curriculum/modules/2-keyword-research/2.3-negative-keywords.mdx` at line 182, Update the answer’s negative exact explanation to state that it blocks the target keyword and Amazon-applied close variations, not only a byte-for-byte literal query. Revise the “cutting board oil” example to distinguish exact matching plus close variations from negative phrase matching, while preserving the phrase-match examples and remaining answers.content/curriculum/modules/4-campaign-architecture/4.3-campaign-structure.mdx (1)
63-65: 🎯 Functional Correctness | 🟡 Minor | ⚡ Quick winLabel the competitor ASIN example as product targets.
Keywordsis the wrong bucket for competitor ASINs here; rename it toTargetsor split the example into keyword and product-targeting sections.🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@content/curriculum/modules/4-campaign-architecture/4.3-campaign-structure.mdx` around lines 63 - 65, Update the “YB-PAT-Competitors” example so competitor ASINs appear under a “Targets” label rather than “Keywords,” while preserving the existing product-targeting context.content/curriculum/modules/2-keyword-research/2.4-keyword-grouping.mdx (1)
160-165: 🎯 Functional Correctness | 🟡 Minor | ⚡ Quick winChoose one maximum keyword count.
Line 185 recommends 5-15 keywords, while the mistakes table and answer specify a maximum of 15-20. Align all three so the quick check has one unambiguous answer.
Also applies to: 182-197
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@content/curriculum/modules/2-keyword-research/2.4-keyword-grouping.mdx` around lines 160 - 165, Align the keyword-count guidance across the “Common Keyword Grouping Mistakes” table, the quick-check answer, and the recommendation around the keyword grouping section by choosing one maximum range. Update all three references to use the same limit, preserving the surrounding guidance and ensuring the quick check has a single unambiguous answer.content/curriculum/modules/3-listing-optimization/3.1-listing-quality-score.mdx (2)
23-32: 🎯 Functional Correctness | 🟠 Major | ⚡ Quick winDo not assign undocumented signal weights.
The introduction says Amazon publishes no formula, but the table labels each factor High, Medium, or Low. Present these as diagnostic factors without invented weighting, or cite a documented source.
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@content/curriculum/modules/3-listing-optimization/3.1-listing-quality-score.mdx` around lines 23 - 32, Remove the undocumented High, Medium, and Low labels from the factor table in the listing quality score section, or replace them with an explicitly sourced weighting scheme. Keep the factors and their observable impact descriptions intact, and ensure the introduction does not imply unsupported relative importance.
38-79: 🎯 Functional Correctness | 🟠 Major | ⚡ Quick winTreat lower CPC as a possible outcome, not a documented Amazon reward.
Both lessons turn an inferred relationship into a guaranteed pricing mechanism:
content/curriculum/modules/3-listing-optimization/3.1-listing-quality-score.mdx#L38-L79: replace “Amazon rewards/charges” and “listings get cheaper” with qualified efficiency language.content/curriculum/modules/3-listing-optimization/3.3-aplus-content.mdx#L63-L63: describe improved conversion and ACoS without promising Amazon will lower CPC.🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@content/curriculum/modules/3-listing-optimization/3.1-listing-quality-score.mdx` around lines 38 - 79, Qualify the CPC claims rather than presenting lower CPC as a guaranteed Amazon reward: in content/curriculum/modules/3-listing-optimization/3.1-listing-quality-score.mdx lines 38-79, replace the “Amazon rewards/charges” and “listings get cheaper” language with possible efficiency outcomes; in content/curriculum/modules/3-listing-optimization/3.3-aplus-content.mdx line 63, describe improved conversion and ACoS without promising Amazon will lower CPC.content/curriculum/modules/3-listing-optimization/3.2-listing-anatomy.mdx (1)
42-58: 🎯 Functional Correctness | 🟠 Major | ⚡ Quick winUpdate the title guidance for Amazon’s July 27, 2026 limit. The “first 80 characters” rule, 180-character example, and “readability second” tip will be wrong once non-media titles are capped at 75 characters; replace them with concise, natural titles and move extra details into Item Highlights. Also update the takeaway callout at lines 182-197.
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@content/curriculum/modules/3-listing-optimization/3.2-listing-anatomy.mdx` around lines 42 - 58, Update the title guidance in the listing-anatomy module for Amazon’s July 27, 2026 non-media 75-character limit: replace the first-80-characters rule and overlong PPC example with a concise, natural title of 75 characters or fewer, and revise the “readability second” tip to prioritize natural readability. In the takeaway callout, update the corresponding title-length guidance and direct extra details into Item Highlights.content/curriculum/modules/8-competitive-intelligence/8.3-competitor-benchmarking.mdx (1)
64-80: 🎯 Functional Correctness | 🟡 Minor | ⚡ Quick winKeep scored cells limited to the four rubric values.
Line 70 says cells use only
Strong,Medium,Weak, orNot using, but lines 77-78 contain values such asWeak (flat bids)andStrong (scheduled bid rules). Keep the scored value exact and move explanatory text into theReadingcolumn.🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the rest with a brief reason, keep changes minimal, and validate. In `@content/curriculum/modules/8-competitive-intelligence/8.3-competitor-benchmarking.mdx` around lines 64 - 80, Keep every scored matrix cell in the exact four-value rubric: Strong, Medium, Weak, or Not using. Update the Weekend bid adjustments and Sponsored Display rows to remove parenthetical explanations from Competitor A, Competitor B, and Us, and move those details into the corresponding Reading cells.
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
Inline comments:
In `@content/curriculum/modules/2-keyword-research/2.4-keyword-grouping.mdx`:
- Line 17: Update the keyword-grouping lesson’s references across the sections
around the shared-intent guidance and lines 182–197 to consistently use the
shared-shopper-intent test, replacing language about whether “one ad” fits every
keyword. Preserve the existing explanation that Sponsored Products use the
product listing rather than custom ad copy, and align all affected guidance with
the AMPH v2 terminology already established in the lesson.
In
`@content/curriculum/modules/3-listing-optimization/3.1-listing-quality-score.mdx`:
- Line 38: Revise the CPC explanation around the “general dynamic” passage and
the corresponding text at the later referenced location to avoid stating that
Amazon directly rewards listings with lower CPC. Describe stronger CTR and CVR
as potentially improving advertising efficiency in an auction-based system,
without presenting lower CPC as deterministic or guaranteed.
In `@content/curriculum/modules/3-listing-optimization/3.2-listing-anatomy.mdx`:
- Around line 141-149: Align the fifth feature heading with the coverage
described in the warranty text by renaming “LIFETIME WARRANTY” to “5-YEAR
WARRANTY” in the listing content. Keep the existing five-year replacement terms
unchanged.
- Around line 92-97: Update the performance claims in the listing anatomy
content, including the bullet-impact table, the “15-30% higher” zoom conversion
claim, and the “pays back 10x” statement. Either remove these unsupported
numerical promises or explicitly label them as estimates/illustrative data and
provide an appropriate source.
- Line 160: Update the Sponsored Products tip in the listing optimization module
to retain the recommendation to target the product’s own ASIN for defensive
placement, but remove the unsupported claim that winning the ad spot reinforces
CTR and CVR data with Amazon. Keep the remaining explanation focused on reaching
searchers viewing the product.
In `@content/curriculum/modules/3-listing-optimization/3.3-aplus-content.mdx`:
- Around line 158-162: Update the Key Takeaways in the A+ Content module to
preserve the earlier qualifications: present the 5–17% conversion improvement as
an estimate rather than a direct promise, and qualify the comparison-chart
performance claim instead of stating it as universally highest-converting. Keep
the remaining takeaways unchanged.
- Around line 121-132: The Brand Analytics example and Tip overstate available
capabilities by claiming product prices and advertiser-competition data. Update
the “Real example” and the Tip to reference only query volume/frequency, shares,
and top-clicked products; remove price and “few advertisers bidding” claims, and
instruct learners to combine Brand Analytics findings with Advertising Console
data for competition and bidding insights.
- Around line 23-31: Update the A+ Content and Video in gallery PPC Impact cells
in the comparison table to use source-backed, non-guaranteed language instead of
“+15-25%” conversion or CTR claims. Reflect Amazon’s framing of potential sales
lifts of up to 8% for Basic A+ and 20% for Premium A+, without asserting a
direct CTR increase.
In `@content/curriculum/modules/5-portfolio-strategy/5.3-seasonal-strategy.mdx`:
- Line 30: Update the seasonal strategy table row labeled “Post-Q4” so its
timing is no longer “Late Dec”: either rename the phase to “Post-peak” while
retaining the timing, or keep “Post-Q4” and move its timing to January.
- Line 146: Update the “PORTFOLIO: Q4 2026 Holiday” template name in the
seasonal strategy content to use a year-neutral placeholder, such as a variable
year, while preserving the Q4 Holiday naming structure and consistency with the
surrounding Q4 2027 instructions.
- Around line 23-27: Update the Prime Day row in the seasonal strategy table to
replace the fixed “Jul” month with “Varies by year; check Amazon’s announced
dates.” Keep the remaining Prime Day traffic, ACoS pattern, and action guidance
unchanged.
- Line 137: Revise the Tip in the seasonal strategy module to qualify the
recommendation to spend more when ACoS rises. Instruct readers to increase
budgets only after comparing incremental profit after ad spend and validating
margin, inventory availability, and marginal sales; replace the blanket
“optimize for profit” guidance with this conditional decision framework.
In
`@content/curriculum/modules/8-competitive-intelligence/8.1-brand-analytics.mdx`:
- Around line 102-104: Revise the guidance in the brand analytics section around
“Higher acceptable ACoS” so it does not infer conversion or profitability from
income alone. State that ACoS ceilings should be based on margin and measured
segment performance, while demographics remain only a targeting hypothesis.
- Line 24: Update the Amazon Brand Analytics sentence to state that access
requires both a Professional selling account and Brand Representative access for
a brand enrolled in Amazon Brand Registry. Make clear that Brand Registry
enrollment alone is insufficient, while preserving the existing description of
the reports and insights.
- Around line 26-34: Update the Key Reports table to use the current Brand
Analytics terminology for the Click Share & Conversion Share row, aligning it
with Top Search Terms/Search Query Performance. Locate and rename or remove all
later Item Comparison references in this curriculum module, while preserving the
surrounding report descriptions and PPC use cases.
In
`@content/curriculum/modules/8-competitive-intelligence/8.3-competitor-benchmarking.mdx`:
- Around line 173-180: Update the second item in the “Key Takeaways” list to
clarify that daily deep competitive analysis is unnecessary while daily
impression-share alert monitoring remains expected. Keep the existing weekly
review recommendation and other takeaways unchanged.
- Around line 46-51: Update the competitor-filtering guidance in the “Same
placement”/SOV list to remove the unconditional “Share of Voice > 5%” cutoff and
its dismissal of lower-SOV sellers. Replace it with guidance to assess current
SOV alongside relevance, growth, placement, and product overlap.
---
Outside diff comments:
In `@content/curriculum/modules/2-keyword-research/2.3-negative-keywords.mdx`:
- Around line 158-163: Update the negative-update schedule table to use
non-overlapping phase ranges, clarifying the boundary between the initial period
and Weeks 2–6. Replace “Bi-weekly” in the Mature campaign row with “Every two
weeks” to remove ambiguity, while preserving the existing frequencies and time
requirements.
- Around line 13-15: Soften the claims in the negative-keyword introduction
around “what to block,” “single fastest way,” and any absolute conversion
language: describe negatives as terms that underperform in the provided examples
or are clearly irrelevant, rather than universally failing. Remove the fixed
20–30 negative-keyword quota wherever it appears in this lesson, preserving
guidance to make decisions from observed performance and relevance.
- Line 182: Update the answer’s negative exact explanation to state that it
blocks the target keyword and Amazon-applied close variations, not only a
byte-for-byte literal query. Revise the “cutting board oil” example to
distinguish exact matching plus close variations from negative phrase matching,
while preserving the phrase-match examples and remaining answers.
In `@content/curriculum/modules/2-keyword-research/2.4-keyword-grouping.mdx`:
- Around line 160-165: Align the keyword-count guidance across the “Common
Keyword Grouping Mistakes” table, the quick-check answer, and the recommendation
around the keyword grouping section by choosing one maximum range. Update all
three references to use the same limit, preserving the surrounding guidance and
ensuring the quick check has a single unambiguous answer.
In
`@content/curriculum/modules/3-listing-optimization/3.1-listing-quality-score.mdx`:
- Around line 23-32: Remove the undocumented High, Medium, and Low labels from
the factor table in the listing quality score section, or replace them with an
explicitly sourced weighting scheme. Keep the factors and their observable
impact descriptions intact, and ensure the introduction does not imply
unsupported relative importance.
- Around line 38-79: Qualify the CPC claims rather than presenting lower CPC as
a guaranteed Amazon reward: in
content/curriculum/modules/3-listing-optimization/3.1-listing-quality-score.mdx
lines 38-79, replace the “Amazon rewards/charges” and “listings get cheaper”
language with possible efficiency outcomes; in
content/curriculum/modules/3-listing-optimization/3.3-aplus-content.mdx line 63,
describe improved conversion and ACoS without promising Amazon will lower CPC.
In `@content/curriculum/modules/3-listing-optimization/3.2-listing-anatomy.mdx`:
- Around line 42-58: Update the title guidance in the listing-anatomy module for
Amazon’s July 27, 2026 non-media 75-character limit: replace the
first-80-characters rule and overlong PPC example with a concise, natural title
of 75 characters or fewer, and revise the “readability second” tip to prioritize
natural readability. In the takeaway callout, update the corresponding
title-length guidance and direct extra details into Item Highlights.
In
`@content/curriculum/modules/4-campaign-architecture/4.3-campaign-structure.mdx`:
- Around line 63-65: Update the “YB-PAT-Competitors” example so competitor ASINs
appear under a “Targets” label rather than “Keywords,” while preserving the
existing product-targeting context.
In `@content/curriculum/modules/5-portfolio-strategy/5.3-seasonal-strategy.mdx`:
- Around line 118-135: Correct the seasonal profit example’s terminology: rename
the “Gross Profit” row and the surrounding “total profit” references to profit
after ad spend, while preserving the existing formula and values. Clarify that
pre-ad gross profit at the 50% margin would be ₱100,000 and ₱375,000, and retain
the instruction to recalculate using the actual Q4 margin.
In
`@content/curriculum/modules/8-competitive-intelligence/8.3-competitor-benchmarking.mdx`:
- Around line 64-80: Keep every scored matrix cell in the exact four-value
rubric: Strong, Medium, Weak, or Not using. Update the Weekend bid adjustments
and Sponsored Display rows to remove parenthetical explanations from Competitor
A, Competitor B, and Us, and move those details into the corresponding Reading
cells.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
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Review profile: CHILL
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📒 Files selected for processing (24)
content/curriculum/modules/2-keyword-research/2.1-match-types.mdxcontent/curriculum/modules/2-keyword-research/2.2-keyword-research-workflow.mdxcontent/curriculum/modules/2-keyword-research/2.3-negative-keywords.mdxcontent/curriculum/modules/2-keyword-research/2.4-keyword-grouping.mdxcontent/curriculum/modules/3-listing-optimization/3.1-listing-quality-score.mdxcontent/curriculum/modules/3-listing-optimization/3.2-listing-anatomy.mdxcontent/curriculum/modules/3-listing-optimization/3.3-aplus-content.mdxcontent/curriculum/modules/4-campaign-architecture/4.1-sponsored-products.mdxcontent/curriculum/modules/4-campaign-architecture/4.2-sponsored-brands-display.mdxcontent/curriculum/modules/4-campaign-architecture/4.3-campaign-structure.mdxcontent/curriculum/modules/4-campaign-architecture/4.4-campaign-architecture-practice.mdxcontent/curriculum/modules/5-portfolio-strategy/5.1-campaign-portfolios.mdxcontent/curriculum/modules/5-portfolio-strategy/5.2-budget-pacing.mdxcontent/curriculum/modules/5-portfolio-strategy/5.3-seasonal-strategy.mdxcontent/curriculum/modules/6-bidding-lab/6.1-bid-strategies.mdxcontent/curriculum/modules/6-bidding-lab/6.2-placement-adjustments.mdxcontent/curriculum/modules/7-search-term-triage/7.1-search-term-analysis.mdxcontent/curriculum/modules/7-search-term-triage/7.2-negative-keywords.mdxcontent/curriculum/modules/7-search-term-triage/7.3-str-triage-prep.mdxcontent/curriculum/modules/8-competitive-intelligence/8.1-brand-analytics.mdxcontent/curriculum/modules/8-competitive-intelligence/8.2-share-of-voice.mdxcontent/curriculum/modules/8-competitive-intelligence/8.3-competitor-benchmarking.mdxcontent/curriculum/quiz-questions.jsondocs/CONTENT-AUDIT-MODULES-2-8.md
🚧 Files skipped from review as they are similar to previous changes (11)
- docs/CONTENT-AUDIT-MODULES-2-8.md
- content/curriculum/quiz-questions.json
- content/curriculum/modules/4-campaign-architecture/4.1-sponsored-products.mdx
- content/curriculum/modules/4-campaign-architecture/4.4-campaign-architecture-practice.mdx
- content/curriculum/modules/5-portfolio-strategy/5.2-budget-pacing.mdx
- content/curriculum/modules/4-campaign-architecture/4.2-sponsored-brands-display.mdx
- content/curriculum/modules/6-bidding-lab/6.1-bid-strategies.mdx
- content/curriculum/modules/2-keyword-research/2.2-keyword-research-workflow.mdx
- content/curriculum/modules/5-portfolio-strategy/5.1-campaign-portfolios.mdx
- content/curriculum/modules/2-keyword-research/2.1-match-types.mdx
- content/curriculum/modules/8-competitive-intelligence/8.2-share-of-voice.mdx
| This is where most sellers make their biggest mistake: **dumping all keywords into one ad group**. It works, briefly. But as you scale, it becomes a mess of conflicting data, vague optimization, and missed opportunities. | ||
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| The solution is **keyword grouping**: organizing keywords into tightly themed clusters that each get their own ad group with targeted ad copy and appropriate bids. | ||
| The solution is **keyword grouping**: organizing keywords into tightly themed clusters that each get their own ad group with an appropriate bid and a clean read on performance. Sponsored Products ads don't use custom ad copy the way Sponsored Brands do (the ad is your product listing), so grouping isn't about writing different ads per theme. It's about bid control and reporting clarity. |
There was a problem hiding this comment.
🎯 Functional Correctness | 🟡 Minor | ⚡ Quick win
Use the shared-intent test consistently.
Line 17 correctly says Sponsored Products have no custom ad copy, but Lines 186 and 197 still tell learners to test whether “one ad” fits every keyword. Replace those references with the shared-shopper-intent test from Lines 54 and 73.
As per coding guidelines, “Rewrite legacy curriculum content to match the AMPH v2 product before shipping the next content release.”
Also applies to: 54-73, 182-197
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In `@content/curriculum/modules/2-keyword-research/2.4-keyword-grouping.mdx` at
line 17, Update the keyword-grouping lesson’s references across the sections
around the shared-intent guidance and lines 182–197 to consistently use the
shared-shopper-intent test, replacing language about whether “one ad” fits every
keyword. Preserve the existing explanation that Sponsored Products use the
product listing rather than custom ad copy, and align all affected guidance with
the AMPH v2 terminology already established in the lesson.
Source: Coding guidelines
| ## The Relevance Feedback Loop | ||
|
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||
| Here's the general dynamic — and why it compounds over time: | ||
| Here's the general dynamic, and why it compounds over time. Watch what happens to CPC (cost per click) as CTR and CVR move together: |
There was a problem hiding this comment.
🎯 Functional Correctness | 🟠 Major | ⚡ Quick win
Avoid claiming Amazon directly rewards listings with lower CPC.
These lines turn an acknowledged inference into a deterministic pricing rule. CPC is auction-based; describe stronger CTR and CVR as potentially improving efficiency rather than making ads inherently cheaper. (advertising.amazon.com)
Also applies to: 79-79
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In
`@content/curriculum/modules/3-listing-optimization/3.1-listing-quality-score.mdx`
at line 38, Revise the CPC explanation around the “general dynamic” passage and
the corresponding text at the later referenced location to avoid stating that
Amazon directly rewards listings with lower CPC. Describe stronger CTR and CVR
as potentially improving advertising efficiency in an auction-based system,
without presenting lower CPC as deterministic or guaranteed.
Comment on lines
92
to
97
| Here's how bullet quality moves the metrics that matter: CTR, CVR (conversion rate, orders divided by clicks), and ACoS (advertising cost of sales). | ||
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| | Bullet Quality | CTR Impact | CVR Impact | ACoS Impact | | ||
| |----------------|------------|------------|-------------| | ||
| | Good bullets | +10-20% | +15-30% | -10-25% | | ||
| | Weak bullets | -10% | -20-40% | +15-35% | |
There was a problem hiding this comment.
🎯 Functional Correctness | 🟠 Major | ⚡ Quick win
Qualify or remove the performance promises.
The bullet-impact percentages, “15-30% higher” zoom conversion claim, and “pays back 10x” statement are presented without a source or illustrative-data label. Remove the numbers or explicitly frame and source them as estimates.
Also applies to: 109-115, 182-187
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In `@content/curriculum/modules/3-listing-optimization/3.2-listing-anatomy.mdx`
around lines 92 - 97, Update the performance claims in the listing anatomy
content, including the bullet-impact table, the “15-30% higher” zoom conversion
claim, and the “pays back 10x” statement. Either remove these unsupported
numerical promises or explicitly label them as estimates/illustrative data and
provide an appropriate source.
Comment on lines
+141
to
+149
| > **1. FAMILY-SIZED PREP SPACE.** 18x12 inches of natural bamboo surface. Big enough for a whole lechon prep, compact enough for daily use. Fits standard kitchen counters. | ||
| > | ||
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| > **2. ORGANIC BAMBOO CONSTRUCTION.** Harder than maple, gentler on knives. Naturally antimicrobial, no chemicals, no treatments. Just pure organic bamboo that's better for your kitchen and your health. | ||
| > | ||
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| > **3. DEEP JUICE GROOVE CATCHES MESSES.** Surrounding channel catches juices from meat, fruits, and vegetables. No more cleaning countertops after every slice. Perfect for BBQ and meal prep. | ||
| > | ||
| > **4. VERSATILE ENOUGH FOR EVERY KITCHEN** — Use it for chopping vegetables, slicing meat, serving cheese, or as a BBQ prep station. Built for Filipino kitchens where one board does everything. | ||
| > **4. VERSATILE ENOUGH FOR EVERY KITCHEN.** Use it for chopping vegetables, slicing meat, serving cheese, or as a BBQ prep station. Built for Filipino kitchens where one board does everything. | ||
| > | ||
| > **5. EASY CARE, LIFETIME WARRANTY** — Hand wash, dry, and apply mineral oil monthly. It lasts for years. If it warps or cracks within 5 years, we replace it free. No questions asked. | ||
| > **5. EASY CARE, LIFETIME WARRANTY.** Hand wash, dry, and apply mineral oil monthly. It lasts for years. If it warps or cracks within 5 years, we replace it free. No questions asked. |
There was a problem hiding this comment.
🎯 Functional Correctness | 🟡 Minor | ⚡ Quick win
Match the warranty heading to the actual term.
The heading promises a lifetime warranty, but the proof limits replacement to five years. Rename it “5-YEAR WARRANTY” or make the described coverage genuinely lifetime.
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In `@content/curriculum/modules/3-listing-optimization/3.2-listing-anatomy.mdx`
around lines 141 - 149, Align the fifth feature heading with the coverage
described in the warranty text by renaming “LIFETIME WARRANTY” to “5-YEAR
WARRANTY” in the listing content. Keep the existing five-year replacement terms
unchanged.
| > - Position 7: 5-year warranty graphic | ||
|
|
||
| > 💡 **Tip**: After you optimize your listing, run a **Sponsored Products campaign** targeting your product's own ASIN. If you win that ad spot and your listing is now optimized, you'll convert searchers who are already looking at your product — reinforcing your CTR and CVR data to Amazon. | ||
| > **Tip**: After you optimize your listing, run a **Sponsored Products campaign** targeting your product's own ASIN (Amazon's product ID). If you win that ad spot and your listing is now optimized, you'll convert searchers who are already looking at your product, reinforcing your CTR and CVR data to Amazon. |
There was a problem hiding this comment.
🎯 Functional Correctness | 🟡 Minor | ⚡ Quick win
Remove the unsupported self-targeting signal claim.
Product targeting can place an ad on a targeted ASIN’s detail page, but the cited mechanism does not establish that targeting your own ASIN “reinforces” CTR and CVR data. Keep the defensive-placement strategy, but remove that causal explanation. (advertising.amazon.com)
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In `@content/curriculum/modules/3-listing-optimization/3.2-listing-anatomy.mdx` at
line 160, Update the Sponsored Products tip in the listing optimization module
to retain the recommendation to target the product’s own ASIN for defensive
placement, but remove the unsupported claim that winning the ad spot reinforces
CTR and CVR data with Amazon. Keep the remaining explanation focused on reaching
searchers viewing the product.
| ## What Is Brand Analytics? | ||
|
|
||
| Amazon Brand Analytics (ABA) is a set of reports available to Brand Registered sellers. It gives you direct insight into customer search behavior, shopping patterns, and the competitive landscape — data that non-brand-registered sellers can't see. | ||
| Amazon Brand Analytics (ABA) is a set of reports available to Brand Registered sellers. It gives you direct insight into customer search behavior, shopping patterns, and the competitive landscape, data that non-brand-registered sellers can't see. |
There was a problem hiding this comment.
🎯 Functional Correctness | 🟡 Minor | ⚡ Quick win
🧩 Analysis chain
🏁 Script executed:
#!/bin/bash
set -euo pipefail
file='content/curriculum/modules/8-competitive-intelligence/8.1-brand-analytics.mdx'
wc -l "$file"
sed -n '1,80p' "$file"Repository: projectamazonph/amph-v2
Length of output: 4154
🌐 Web query:
Amazon Brand Analytics access requirements Professional selling account Brand Registry Brand Representative access Amazon documents
💡 Result:
To access Amazon Brand Analytics, a seller must meet two primary requirements: maintaining an active Professional selling account and having the correct Brand Registry role assigned to their account [1][2][3]. Specifically, the requirements are: Professional Selling Account: You must have an active Professional selling plan [1][2][4]. This is a subscription-based account, which currently costs $39.99 per month plus applicable selling fees [1][2]. Brand Registry Enrollment and Role: Your brand must be enrolled in the Amazon Brand Registry, typically requiring an active or pending trademark [2][4][3]. Additionally, the specific user account must be assigned the Brand Representative role [1][5]. This role is intended for internal, first-party sellers directly employed by the brand [5]. If you are the Rights Owner who enrolled the brand, this role is often assigned automatically [5]. If you are an additional user or employee, a Brand Administrator must manually assign the Brand Representative role to your account [1][5]. Please note that other roles, such as Reseller, do not grant access to Brand Analytics [5]. Once these requirements are met, you can access the tool in Seller Central by navigating to the Brands menu and selecting Brand Analytics [1][2][6]. If you meet the criteria but still cannot access the tool, check your user permissions in Seller Central or contact Selling Partner Support [7][6].
Citations:
- 1: https://sell.amazon.com/tools/amazon-brand-analytics
- 2: https://sell.amazon.com/blog/brand-analytics
- 3: https://thunderbit.com/blog/how-to-leverage-amazon-brand-registry-data
- 4: https://myamazonguy.com/brand-registry/amazon-brand-analytics-tool/
- 5: https://sell.amazon.com/blog/brand-registry-roles
- 6: https://www.zonguru.com/blog/amazon-brand-analytics
- 7: https://sellercentral.amazon.com/help/hub/reference/external/PHCEMH5FFH32KG8?ref=efph_PHCEMH5FFH32KG8_cont_H2Z5B4HMF5ZXCG2&locale=en-US
Clarify Brand Analytics access requirements. It requires a Professional selling account plus Brand Representative access for a brand enrolled in Brand Registry; Brand Registry alone isn’t enough. Update this sentence so learners don’t expect access with insufficient permissions.
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In
`@content/curriculum/modules/8-competitive-intelligence/8.1-brand-analytics.mdx`
at line 24, Update the Amazon Brand Analytics sentence to state that access
requires both a Professional selling account and Brand Representative access for
a brand enrolled in Amazon Brand Registry. Make clear that Brand Registry
enrollment alone is insufficient, while preserving the existing description of
the reports and insights.
Source: MCP tools
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| ### Key Reports | ||
|
|
||
| | Report | What It Shows | PPC Use Case | | ||
| |--------|--------------|--------------| | ||
| | **Search Frequency** | Top search terms ranked by frequency | Benchmark your keyword targeting against actual customer demand | | ||
| | **Click Share & Conversion Share** | Your brand's CTR and CVR vs top 3 competitors per ASIN | Identify where competitors are outperforming you | | ||
| | **Click Share & Conversion Share** | Your brand's CTR (click-through rate) and CVR (conversion rate) vs top 3 competitors per ASIN (Amazon's product ID) | Identify where competitors are outperforming you | | ||
| | **Market Basket Analysis** | Products frequently bought together with yours | Cross-sell targeting and product placement strategy | | ||
| | **Item Comparison** | Which products customers compare yours against | Direct competitor identification for product targeting | | ||
| | **Demographics** | Age, income, education of your customers | Audience targeting refinement | |
There was a problem hiding this comment.
🎯 Functional Correctness | 🟠 Major | ⚡ Quick win
🧩 Analysis chain
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sed -n '1,180p' content/curriculum/modules/8-competitive-intelligence/8.1-brand-analytics.mdxRepository: projectamazonph/amph-v2
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git ls-files | rg '8\.1-brand-analytics\.mdx$|brand-analytics'Repository: projectamazonph/amph-v2
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git ls-files 'content/curriculum/**/*brand*' 'content/curriculum/**/*analytics*' 'content/curriculum/**/*.mdx' | sed -n '1,200p'Repository: projectamazonph/amph-v2
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fd -a '8\.1-brand-analytics\.mdx|brand-analytics|analytics' content/curriculumRepository: projectamazonph/amph-v2
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git ls-files content/curriculum | rg 'brand|analytics|8\.1|8-competitive-intelligence'Repository: projectamazonph/amph-v2
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git ls-files content/curriculum | sed -n '1,200p'Repository: projectamazonph/amph-v2
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find . -path '*/content/curriculum/*' -type f | sed -n '1,200p'Repository: projectamazonph/amph-v2
Length of output: 2533
🏁 Script executed:
sed -n '1,180p' content/curriculum/modules/8-competitive-intelligence/8.1-brand-analytics.mdx && printf '\n--- SEARCH ---\n' && rg -n 'Click Share|Conversion Share|Item Comparison|Search Frequency|Market Basket|Demographics' content/curriculum/modules/8-competitive-intelligence/8.1-brand-analytics.mdx content/curriculum/modules/8-competitive-intelligenceRepository: projectamazonph/amph-v2
Length of output: 13766
🌐 Web query:
Amazon Brand Analytics click share conversion share item comparison current report top clicked products search term
💡 Result:
Amazon Brand Analytics (ABA) is a suite of tools available to brands enrolled in Amazon Brand Registry that provides aggregated data on customer shopping behavior and performance [1][2]. As of July 2026, the status of the requested reports is as follows: Click Share and Conversion Share These metrics are primarily featured in the Search Query Performance and Top Search Terms dashboards [3][4]. - Click Share: Represents the percentage of total clicks for a specific search query that were attributed to a specific brand or ASIN [3][4]. It measures listing discoverability and the effectiveness of elements like titles, images, and ad placements [3]. - Conversion Share: Represents the percentage of total conversions (purchases) for a specific search query that were attributed to a specific brand or ASIN [4][5]. Top Search Terms Report This dashboard displays the most popular marketplace queries ranked by Search Frequency Rank (SFR) [3][4]. For each search term, it provides the top three clicked products (ASINs), along with their respective click share and conversion share [2][4]. It covers marketplace-wide data, allowing brands to research category-level demand and planning [3]. Item Comparison Report The Item Comparison and Alternate Purchase Behavior report was discontinued by Amazon and is no longer available as of June 30, 2022 [1]. Previously, this report helped brands identify which competing products customers viewed or purchased in the same 24-hour session as their own items [6][7][8]. Current Primary Dashboards While the landscape of ABA has evolved, brands currently utilize several primary dashboards to analyze performance, including: - Search Query Performance: Provides a detailed view of the search-to-purchase funnel (impressions, clicks, cart adds, and purchases) for top queries relevant to a brand, including market share metrics [3][2][4]. - Search Catalog Performance: Offers product-level insights into the sales funnel to help identify conversion issues or customer drop-off points [1]. - Top Search Terms: (Described above) [2]. - Other dashboards include Market Basket Analysis, Repeat Purchase Behavior, and Demographics [1][2]. Data in these reports is generally updated and available within 72 hours of the close of a given period [1].
Citations:
- 1: https://m.media-amazon.com/images/G/01/BX_Marketing/2023/ABA_1-Pager_-_V06b-3-10-2023.pdf
- 2: https://sell.amazon.com/blog/brand-analytics
- 3: https://www.amplisell.com/blog-post/best-amazon-brand-analytics-reports-that-inform-strategy
- 4: https://ensobrands.com/amazon-brand-analytics-guide/
- 5: https://help.sarasanalytics.com/en_US/amazon-vendor-central/amazon-brand-analytics-search-terms-report
- 6: https://www.amalytix.com/en/knowledge/controlling/aba-item-comparison/
- 7: https://capitoldataanalytics.com/amazon-brand-analytics-item-comparison-and-alternate-purchase/
- 8: https://profitwhales.com/articles/how-use-amazon-brand-analytics/
🌐 Web query:
site:sell.amazon.com Brand Analytics Item Comparison report current standalone dashboard
💡 Result:
As of July 17, 2026, there is no standalone "Item Comparison" dashboard within Amazon Brand Analytics [1][2]. While Amazon Brand Analytics offers a comprehensive suite of dashboards—such as Search Query Performance, Search Catalog Performance, Top Search Terms, Market Basket Analysis, Repeat Purchase Behavior, Demographics, and Customer Loyalty Analytics—the specific "Item Comparison" report is not currently listed as a standalone dashboard [1][2]. It is possible that the term "Item Comparison" may be confused with other features, such as: 1. Market Basket Analysis: This dashboard identifies products that customers frequently purchase together, which provides some comparative insight into product relationships [1][2]. 2. A+ Content Comparison Charts: Sellers can use A+ Content on product detail pages to create comparison charts to display alongside their products, though this is a marketing feature, not an analytics dashboard [3][4]. 3. Product Opportunity Explorer or Marketplace Product Guidance: These tools offer competitive and demand-based insights that allow for comparisons, though they are distinct from Brand Analytics [5]. For the most up-to-date access to available analytics, you can navigate to the Brand Analytics section directly via the Seller Central main menu by selecting Brands, then Brand Analytics [1].
Citations:
- 1: https://sell.amazon.com/tools/amazon-brand-analytics
- 2: https://sell.amazon.com/blog/brand-analytics
- 3: https://sell.amazon.com/blog/amazon-brand-management
- 4: https://sell.amazon.com/brand-registry
- 5: https://sell.amazon.com/tools/seller-central
🏁 Script executed:
sed -n '1,140p' content/curriculum/modules/8-competitive-intelligence/8.2-share-of-voice.mdxRepository: projectamazonph/amph-v2
Length of output: 5782
Update the Brand Analytics report names and remove legacy Item Comparison references. Click Share & Conversion Share should match the current Top Search Terms/Search Query Performance terminology, and the later Item Comparison references should be renamed or dropped.
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In
`@content/curriculum/modules/8-competitive-intelligence/8.1-brand-analytics.mdx`
around lines 26 - 34, Update the Key Reports table to use the current Brand
Analytics terminology for the Click Share & Conversion Share row, aligning it
with Top Search Terms/Search Query Performance. Locate and rename or remove all
later Item Comparison references in this curriculum module, while preserving the
surrounding report descriptions and PPC use cases.
Source: MCP tools
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| → Higher acceptable ACoS (advertising cost of sales); they convert well | ||
| → Test Sponsored Brands (brand-focused) | ||
| ``` |
There was a problem hiding this comment.
🎯 Functional Correctness | 🟠 Major | ⚡ Quick win
Do not infer a higher acceptable ACoS from income alone.
Demographics can form a targeting hypothesis, but income does not prove stronger conversion or profitability. Tie the ACoS ceiling to margin and measured segment performance instead of assuming high-income shoppers “convert well.”
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In
`@content/curriculum/modules/8-competitive-intelligence/8.1-brand-analytics.mdx`
around lines 102 - 104, Revise the guidance in the brand analytics section
around “Higher acceptable ACoS” so it does not infer conversion or profitability
from income alone. State that ACoS ceilings should be based on margin and
measured segment performance, while demographics remain only a targeting
hypothesis.
Comment on lines
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| Not every seller in your category is a competitor. Filter by: | ||
|
|
||
| 1. **Same price band** — A ₱300 product doesn't compete with a ₱3,000 product | ||
| 2. **Same target customer** — Premium vs. value buyers | ||
| 3. **Same placement** — Top of Search competitors vs. Rest of Search competitors | ||
| 4. **Share of Voice > 5%** — Below 5%, they're not worth your attention | ||
| 1. **Same price band.** A ₱300 product doesn't compete with a ₱3,000 product | ||
| 2. **Same target customer.** Premium vs. value buyers | ||
| 3. **Same placement.** Top of Search competitors vs. Rest of Search competitors | ||
| 4. **Share of Voice > 5%.** Below 5%, they're not worth your attention |
There was a problem hiding this comment.
🎯 Functional Correctness | 🟠 Major | ⚡ Quick win
Remove the unconditional 5% SOV cutoff.
“Below 5%, they’re not worth your attention” is an unsupported hard boundary that can exclude emerging or strategically relevant competitors. Use relevance, growth, placement, and product overlap alongside current SOV instead.
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In
`@content/curriculum/modules/8-competitive-intelligence/8.3-competitor-benchmarking.mdx`
around lines 46 - 51, Update the competitor-filtering guidance in the “Same
placement”/SOV list to remove the unconditional “Share of Voice > 5%” cutoff and
its dismissal of lower-SOV sellers. Replace it with guidance to assess current
SOV alongside relevance, growth, placement, and product overlap.
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| ## Key Takeaways | ||
|
|
||
| 1. A 30-minute weekly competitive review is enough — daily analysis is overkill | ||
| 1. A 30-minute weekly competitive review is enough. Daily analysis is overkill | ||
| 2. Focus on competitors in your price band and customer segment, not every seller | ||
| 3. Gap analysis reveals where competitors are weak and you can win | ||
| 4. Every insight should produce a specific, measurable campaign action | ||
| 5. Track the same 5 competitive metrics weekly for consistent trend data | ||
| 6. Don't over-react — confirm trends before adjusting campaigns | ||
|
|
||
| --- | ||
| 6. Don't over-react. Confirm trends before adjusting campaigns |
There was a problem hiding this comment.
🎯 Functional Correctness | 🟡 Minor | ⚡ Quick win
Clarify daily monitoring versus daily analysis.
The cadence table requires a daily impression-share alert check, while this takeaway says daily analysis is overkill. Change the wording to say that daily deep analysis is unnecessary, while daily alert monitoring remains expected.
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.
In
`@content/curriculum/modules/8-competitive-intelligence/8.3-competitor-benchmarking.mdx`
around lines 173 - 180, Update the second item in the “Key Takeaways” list to
clarify that daily deep competitive analysis is unnecessary while daily
impression-share alert monitoring remains expected. Keep the existing weekly
review recommendation and other takeaways unchanged.
…k check Quick check Q4/A4 still asked for "two numbers" and answered "target ACoS and product margin" for the maximum CPC formula, even though the body text was already corrected. Formula only takes CVR, price, and target ACoS; margin's role is upstream, informing what target ACoS to set.
Fixes across 10 files:
- 5.3: rename mislabeled "Gross Profit" to "Profit After Ad Spend"
(formula subtracts ad spend, so it isn't gross profit); fix
overlapping Post-Q4/Q4 date ranges; make Prime Day's month
year-agnostic; year-neutral portfolio template name; qualify the
"spend more when ACoS rises" tip with margin/inventory/incremental
profit conditions.
- 2.3: soften absolute negative-keyword claims ("single fastest way",
"will NEVER convert", fixed 20-30 quota); fix overlapping negative-
update schedule ranges and ambiguous "bi-weekly"; clarify negative
exact also blocks Amazon's close variations, not just the literal
query.
- 2.4: align keyword-count guidance to one range (15-20) across the
mistakes table, takeaways, and quiz; replace "one ad fits every
keyword" test with the shared-shopper-intent test already used
elsewhere in the lesson, since Sponsored Products has no per-group
ad copy.
- 4.3: relabel competitor ASINs under "Targets" instead of "Keywords"
in the product-targeting campaign example.
- 3.1: remove undocumented High/Medium/Low signal weights; soften
"Amazon rewards/charges" language to reflect an auction-based
tendency, not a guaranteed price effect.
- 3.2: replace the stale "first 80 characters" title rule and
180-character example with concise, natural-title guidance plus a
fact card (Amazon's non-media title limits vary by category and
change over time); fix "LIFETIME WARRANTY" heading to match the
5-year replacement terms in the body; remove the unsupported
self-targeting "reinforces CTR/CVR data" claim; qualify bullet and
zoom performance percentages and the "pays back 10x" claim as
directional estimates.
- 3.3: replace "+15-25%" A+/video PPC-impact claims with Amazon's own
framing (up to 8%/20% sales lift); fix Brand Analytics example and
tip to stop implying it exposes competitor prices or bid competition;
preserve earlier hedges in Key Takeaways instead of re-flattening
them; remove stale Item Comparison/Alternate Purchase Behavior report
references (discontinued 2022).
- 8.1: clarify Brand Analytics access needs a Professional account
plus Brand Representative role, not Brand Registry alone; remove
Item Comparison report references and replace with Top Search Terms'
top-clicked-product data; stop inferring higher acceptable ACoS from
income alone.
- 8.2: replace a stale Item Comparison report reference with Top
Search Terms.
- 8.3: remove the unconditional "SOV > 5%" competitor cutoff; keep
Gap Analysis Matrix cells to the defined four-value rubric, moving
explanatory detail into the Reading column; distinguish daily alert
monitoring (still expected) from daily deep analysis (overkill).
This was referenced Jul 17, 2026
projectamazonph
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Module 2's four files (match types, keyword research workflow, negative keywords, keyword grouping) had the factual and voice-guide fixes from PR #32 but were still missing the "What you can do after this lesson", "The decision in one sentence", "Your turn", and "Client language" blocks that the lesson-production standard in docs/CURRICULUM-REDESIGN.md requires (Modules 0-1 already had these). Adds them without touching existing body content, tables, Key Takeaways, Quick check, or What to read next.
projectamazonph
pushed a commit
that referenced
this pull request
Jul 17, 2026
Modules 3-8 (19 files) had the factual and voice-guide fixes from PR #32 but were still missing the "What you can do after this lesson", "The decision in one sentence", "Your turn", and "Client language" blocks the lesson-production standard in docs/CURRICULUM-REDESIGN.md requires (Modules 0-1 already had these, Module 2 got them in the previous commit). Adds them without touching existing body content, tables, Key Takeaways, Quick check, Fact cards, or What to read next. Every new scenario is original (not a duplicate of an existing in-file example), math in worked "Your turn" scenarios was verified, and none of the debunked claims already corrected elsewhere in these files (break-even CPC framing, discontinued Item Comparison report, Bid Simulator, income-implies- profitability) were reintroduced. This closes out the "Rewrite foundation + campaign-building lessons using the lesson-production standard" item from issue #24's Release 2 checklist for all of Modules 0-8.
4 tasks
projectamazonph
added a commit
that referenced
this pull request
Jul 17, 2026
) * content: add lesson-production-standard blocks to Module 2 Module 2's four files (match types, keyword research workflow, negative keywords, keyword grouping) had the factual and voice-guide fixes from PR #32 but were still missing the "What you can do after this lesson", "The decision in one sentence", "Your turn", and "Client language" blocks that the lesson-production standard in docs/CURRICULUM-REDESIGN.md requires (Modules 0-1 already had these). Adds them without touching existing body content, tables, Key Takeaways, Quick check, or What to read next. * content: add lesson-production-standard blocks to Modules 3-8 Modules 3-8 (19 files) had the factual and voice-guide fixes from PR #32 but were still missing the "What you can do after this lesson", "The decision in one sentence", "Your turn", and "Client language" blocks the lesson-production standard in docs/CURRICULUM-REDESIGN.md requires (Modules 0-1 already had these, Module 2 got them in the previous commit). Adds them without touching existing body content, tables, Key Takeaways, Quick check, Fact cards, or What to read next. Every new scenario is original (not a duplicate of an existing in-file example), math in worked "Your turn" scenarios was verified, and none of the debunked claims already corrected elsewhere in these files (break-even CPC framing, discontinued Item Comparison report, Bid Simulator, income-implies- profitability) were reintroduced. This closes out the "Rewrite foundation + campaign-building lessons using the lesson-production standard" item from issue #24's Release 2 checklist for all of Modules 0-8. * content: address CodeRabbit review pass on PR #36 Fixes across 14 files: - 3.1: fixed the "Your turn" scenario's ACoS arithmetic (stated 61%, actual math gives ~101% at the given CPC/CVR/price); reduced the Client language quote from three sentences to two. - 3.2: removed invented product claims (leakproof, tested lid, "brand-level" naming) not supported by the brief, framing them as assumptions to confirm instead; reworded the title-rewrite explanation so it doesn't imply a title change alone expands ad eligibility, since reach still depends on campaign targeting and match type. - 3.3: made the "decision in one sentence" and worked scenario conditional on Brand Registry eligibility and the seller's own conversion data, instead of presenting A+ Content's ACoS improvement as a guaranteed outcome; the scenario now checks eligibility (e.g. IP Accelerator or non-US pending-trademark paths) before assuming the full trademark spend is required. - 4.1, 4.4: replaced budget ranges that only summed to 75-100% with one explicit split (55/30/15) that sums to exactly the stated daily budget in each scenario. - 4.2: softened the brand-defense guidance so Sponsored Products isn't described as unable to defend a branded search at all, and Sponsored Brands "puts" a product back at the top became "can compete for a top placement"; qualified Sponsored Display retargeting with its own Brand Registry/eligibility requirement. - 5.1: labeled the 60/25/15 portfolio split as a three-product-line adaptation of the lesson's own 60/20/10/10 framework, instead of reading as an unexplained mismatch. - 5.2: reframed the 20-30% budget increase as a starting point tied to the actual 8PM-12AM PHT peak window, with bid cuts or pausing low performers as the fallback if it still exhausts early. - 6.1: scoped the "never raise above what we set" client-language claim to the base bid, since placement adjustments can still lift the effective CPC above it. - 7.1: made the "Winner" classification and aggressive-bid recommendation conditional on a stated 20% target ACoS, instead of presenting a bare 14% ACoS as sufficient evidence on its own. - 7.3: replaced a "Monitor" classification that isn't one of the lesson's five named actions with "Keep for now," matching the precedent this lesson's own quick-practice section already uses for low-click terms. - 8.2: replaced a bid-ceiling-test suggestion (which measures bid elasticity, not SOV) with a reference to Amazon's actual Search Term Impression Share report for term-level share and rank. - 2.1, 2.2: tightened Client language quotes to two clean sentences. --------- Co-authored-by: Claude <noreply@anthropic.com>
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Summary
Follow-up to PR #31. That PR fully rebuilt Modules 0-1; this one is a full read-through audit of the remaining 23 lesson files (Modules 2-8), written up in
docs/CONTENT-AUDIT-MODULES-2-8.md, with the P0 findings fixed.docs/CONTENT-AUDIT-MODULES-2-8.md— every file in Modules 2-8 read in full, cross-checked against PR Content: Release 1 trust-and-safety pass (legacy refs, factual corrections, course split) #29's claimed fixes (verified against the actual PR Content: Release 1 trust-and-safety pass (legacy refs, factual corrections, course split) #29 diff, not assumed), the voice guide, and Module 1's rewritten terminology.8.2-share-of-voice.mdxtold learners to use a "Bid Simulator" and an "Eligible Impressions" report, both Google Ads terminology that doesn't exist in Sponsored Products. Reframed, and unified three contradictory SOV threshold schemes into one. Added the fact card PR Content: Release 1 trust-and-safety pass (legacy refs, factual corrections, course split) #29's own commit message claimed already existed here (it didn't).8.3's Gap Analysis Matrix contradicted its own scoring rule (four of six rows used labels outside the defined scale);3.1's worked ACoS comparison had a cascading error (stated 26%, actual ~17%, which threw off two derived multipliers);5.1's portfolio budget example summed to ₱2,100 while claiming a ₱2,000 cap was never exceeded;5.2claimed "you only pay the daily budget" in the same breath as a weekly total that included the uncapped over-delivery day;5.3's Gross Profit table implied two different margins for the same product;4.2's ROAS range didn't invert its paired ACoS range;2.3labeled $0-sales rows as "100% ACoS" (undefined, not 100);3.3had a mislabeled table column, a single month's savings mislabeled as an annual total, an inaccurate video-placement claim, and an unsourced conversion-lift stat.6.1,6.2,4.4still said "break-even CPC/bid" after Module 1's rewrite retired that term in favor of "maximum CPC at target ACoS" (they're only the same number if the target equals the real margin). Also fixed a4.4cross-reference that skipped Module 5 entirely.xprewardand omittedtype/estimatedMinutes, silently defeatingscripts/import-amph-content.ts's frontmatter parser (case-sensitive) and importing every Module 8 lesson with default values instead of its intended ones.Voice-guide cleanup (em-dashes, emoji, acronym definitions, missing Quick-check/What's-next sections, and the fact that Modules 2-3 have zero quiz coverage) is scoped as its own follow-up phase in the audit doc, given it's the same size of work as the Module 0-1 rewrite in PR #31.
Test plan
quiz-questions.jsonis still well-formed JSONtype,estimatedMinutes, camelCasexpReward)Generated by Claude Code
Summary by CodeRabbit