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<meta name="description" content="Practical guides for Amazon product research: turn reviews into product requirements, deduplicate parent ASINs, pre-screen design patent risk, and build an auditable Go/No-Go decision.">
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<div class="eyebrow">PDBen-Auto / practical guides</div>
<h1>Four product-research questions that reports alone do not answer</h1>
<p>Use the guide that matches the evidence you already have. Each workflow keeps the source boundary visible, distinguishes facts from estimates, and ends with an artifact a product team can review.</p>
<div class="tags"><span class="tag">Amazon product research</span><span class="tag">Voice of Customer</span><span class="tag">SellerSprite BI</span><span class="tag">Design patent risk</span><span class="tag">Go / No-Go decision</span></div>
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<section class="grid">
<article class="card"><h2>How do I turn Amazon reviews into product requirements?</h2><p>Start from written reviews, not only sentiment scores. Preserve review IDs, dates, variants, ratings, original text, and evidence limits before grouping recurring friction.</p><ul><li>Separate negative issues from positive purchase drivers.</li><li>Link every theme to supporting review records.</li><li>Translate the signal into product, packaging, fit, listing, and validation actions.</li></ul><a class="cta" href="cases/review-intelligence.html">Read the worked review case →</a></article>
<article class="card"><h2>How do I avoid inflating an Amazon market with duplicate ASINs?</h2><p>Keyword results are discovery evidence, not an automatic TAM. Define the market boundary, retain excluded candidates, require detailed-data coverage, and aggregate sibling listings at the parent ASIN level.</p><ul><li>Classify direct, adjacent, excluded, and review candidates.</li><li>Keep the denominator tied to the accepted scope.</li><li>Label SellerSprite values as third-party estimates.</li></ul><a class="cta" href="cases/sellersprite-bi.html">Read the SellerSprite BI case →</a></article>
<article class="card"><h2>How do I pre-screen design patent risk before tooling?</h2><p>A product name or image-similarity result is not enough. Read the complete drawing set, compare high-salience visual relationships, separate risk types, and make redesign directions testable.</p><ul><li>Explain what solid and broken lines appear to protect.</li><li>Change structure, silhouette, proportion, and component relationships.</li><li>Re-search the preferred concept before tooling.</li></ul><a class="cta" href="cases/design-patent.html">Read the design-around case →</a></article>
<article class="card"><h2>How do I build an auditable Amazon product Go/No-Go?</h2><p>Market demand, customer pain, supplier feasibility, unit economics, and cash constraints often arrive with different definitions. A typed evidence contract makes the handoff reviewable before a private decision engine is asked to score it.</p><ul><li>Validate required fields and reject sensitive data locally.</li><li>Bind the evidence bundle to a request hash.</li><li>Return a bounded handoff when the private engine is unavailable.</li></ul><a class="cta" href="cases/decision-gateway.html">Read the Gateway case →</a></article>
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<div class="method"><strong>Shared method</strong> The public Skills are designed to compose: market scope → customer evidence → design/IP pre-screen → supplier and financial validation → signed decision handoff. Public examples are synthetic or redacted; the workflows do not include hidden telemetry, covert tracking, or backdoor behavior.</div>
<footer><a href="index.html">Back to the PDBen-Auto Skill collection</a> · <a href="https://github.com/PDBen-Auto/amazon-product-decision-suite">Open the Decision Gateway repository</a></footer>
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