amazon search rank growth engine
by nowrich
A systematic framework for Amazon SEO, keyword prioritization, and conversion-optimized listing architecture.
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Works with the AI tools you already use
See it in action
You say
Optimize my ASIN for a 'silicone baking mat'. Competitors focus on 'non-stick' and 'eco-friendly'. I have data for 50 keywords. Generate the title, bullets, and backend terms.
Your agent does
Optimized Title
Silicone Baking Mat Non-Stick - Reusable Sheet for Pastry and Cookie Baking - Heat Resistant Professional Grade (Set of 2, Red)
Backend Keywords (248 bytes)
half sheet liner oven safe parchment paper alternative macaron supplies kitchen accessories reusable...
What you get
About this skill
The problem
Amazon listings often stall on page three because they lack keyword density or fail to trigger the A9 algorithm's relevancy signals. Developers and sellers struggle to balance human-readable copy with the technical constraints of backend search terms and indexing requirements.
What it does
- Identifies and categorizes head, body, and long-tail keywords using a weighted scoring matrix for search volume and conversion potential.
- Generates optimized product titles, five-bullet sequences, and A+ content structures following Amazon style guides.
- Drafts backend search term blocks optimized for the 250-byte limit without keyword duplication.
- Provides a concrete image direction plan, specifying layout and content for all eight thumbnail slots to maximize CTR.
- Outlines a structured ranking workflow for daily position tracking and indexing verification.
Why this beats prompting it yourself
Generic prompts often ignore Amazon's specific byte limits for backend keywords or include prohibited promotional language. This skill enforces strict structural rules, such as primary keyword placement in the first 100 characters and specific review velocity strategies, ensuring the output is immediately compliant and competitive.
Use cases
- Re-optimizing stagnant ASINs that have lost organic ranking to newer competitors.
- Building a launch-ready SEO foundation for new private label product entries.
- Auditing existing listings to identify gaps in backend search terms and mobile visibility.
- Standardizing listing creation workflows across a multi-brand Amazon portfolio.
Known limitations
Requires manual input of keyword data from external tools like Helium 10 or Amazon Search Query Performance. Does not manage PPC bids or inventory logistics.
How to install
Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.
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