Full Beginner Amazon Ads Tutorial for Amazon KDP (Step-by-Step Guide)

About this video

A complete beginner Amazon Ads tutorial for KDP. His premise: ads do not sell books, they only show books to more people — a bad cover, title or niche fails under any setup, so first ensure demand, an attractive cover/title, a solid description and A+ content, and at least ~15 reviews. The structure is four campaigns per format: manual keyword and manual product campaigns at launch, an automatic campaign after about two weeks (once manual sales have taught Amazon what the book is about), and later a scale campaign for winners. Keyword targets are harvested free from Amazon autocomplete (AMZ Suggestion Expander) or Publisher Rocket; product targets are page-one ASINs. Settings: broad match for prospecting, max ~30 targets per campaign, dynamic bids ‘down only’, starting bids around $0.30 for low/medium content and $0.65 for high content, $5–$10/day, starting in the US then UK and Canada. Optimization: only judge targets with 1,000+ impressions and 10+ clicks, move targets with 3+ orders into an exact-match scale campaign at higher bids, and treat ~40% ACoS as paperback break-even — lower bids below CPC when above it, raise 3–5 cents when below, twice weekly. He ends with a troubleshooting matrix and outsourcing options above $500/month.

Key takeaways

• Fix the book first: ads amplify a good listing, they cannot rescue a bad one
• Launch manual keyword + product campaigns first; add auto after ~2 weeks of sales data
• Keep campaigns to 15–30 targets, broad match for discovery, exact match for proven winners
• Use ~40% ACoS as the paperback break-even guide; adjust bids relative to CPC twice a week
• Diagnose by funnel stage: impressions = bids/targets, clicks = cover/title, sales = page/reviews/price

Episode details: published November 6, 2023 · 25:27 long. Summary written by Self Growth Videos from the episode itself. Business results and any income figures mentioned are Sean Dollwet’s own claims, shared for education — they are not typical or guaranteed.

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