Overview

Helium 10’s Listing Analyzer bridges the gap between product discovery and a fully optimized Amazon listing. By scoring each element of a live ASIN against Amazon’s ranking criteria, the tool helps sellers avoid the common pitfall of launching a great product with a weak, hard‑to‑find listing.

Key Points

• Data‑driven audit — The Analyzer pulls the current Amazon page for a chosen ASIN, evaluates the title, five bullet points, description, backend keywords and image count, then assigns a numeric score (0‑100) to each component, instantly highlighting gaps such as low keyword density or missing lifestyle images.
• Competitive benchmark — It automatically extracts the top three ranking competitors in the same category, compares their keyword usage, formatting and A+ content, and flags any features the target listing lacks, like “hand‑crafted” in the title or enhanced brand content blocks.
• Actionable recommendations — For every element that falls below the optimal threshold, the system provides concrete edit suggestions, for example “add ‘dishwasher safe’ to bullet 2” or “include three long‑tail keywords in backend search terms.”
• Real‑time alerts — Sellers can set a minimum acceptable score; if the listing’s overall rating drops beneath that level, an instant notification is sent, prompting a quick review before the dip hurts organic traffic.
• Seamless integration — Suggested copy can be pushed directly into Helium 10’s Scribbles or Frankenstein tools, allowing keyword refinement and bulk export without leaving the platform.
• Performance tracking — After implementing changes, the Analyzer re‑scans the listing and displays the new scores, giving sellers a clear before‑and‑after view of the impact on visibility factors.

How Listing Analyzer Works

1. Enter ASIN or keyword — The seller types an existing ASIN or a product phrase such as “organic bamboo cutting board.” The tool retrieves the live listing data for that exact product, ensuring the analysis reflects what shoppers currently see.
2. — Helium 10 parses the title, five bullet points, product description, backend search terms and the total number of images. Each section receives a score from 0 to 100; for instance, a title that includes “bamboo cutting board” and “eco‑friendly” might earn an 85, while the same title missing the phrase “dishwasher safe” could drop to 60.