Amazon Listing Audit
TurboAgents Amazon Listing Audit is an AI tool that reads your live Amazon listing and up to two competitors — pages and customer reviews alike — scores your listing out of 100 across seven areas using our own code, and ranks the fixes that will move the needle, so you stop guessing why the seller above you converts better.
See exactly why your Amazon listing loses the sale — then fix it, line by line.
Paste your Amazon product URL and one or two rivals. The engine fetches all three listings and their reviews, computes a Listing Health Score across seven areas, mines what buyers actually complain about, and hands you an ordered list of fixes. One button then rewrites the listing — title, bullets, description, search terms and FAQs — shown before and after.
Watch the 2-minute demo
The one asset that decides your revenue, and nobody audits it.
An Amazon listing audit is a structured read of the page that actually takes the money — title, bullets, description, images, search terms, pricing signals and review sentiment — measured against the listings you lose to. Most sellers have never had one done, because the tools that exist either sell keyword data or sell copywriting, and neither tells you where you currently stand.
The scoring here is deliberately unglamorous: it is computed from the scraped facts in our own code, never asked of a model. That is what makes the number repeatable — run it twice on an unchanged listing and it will not drift, which no chat window can promise. The model’s job is to explain the findings and write the fix. These are the areas it scores:
- Listing Health Score
- A 0–100 score across seven areas — title, bullets, description, images, search terms, pricing signals and review sentiment — calculated deterministically from the scraped page.
- Backend search terms
- The keyword field buyers never see and Amazon indexes anyway. Almost always underused, and one of the cheapest fixes available.
- Review mining
- Reading the actual review text for recurring complaints and the words customers use, so the listing answers objections before they cost you the sale.
- Content policy check
- Amazon rejects listings for things like promotional language and prohibited claims. Every rewrite is checked against those rules before you copy anything.
You can see your rank and your conversion rate, but not why. So sellers rewrite bullets on instinct, add a keyword tool subscription, and change things that were never the problem — while the listing above them wins on an image count and three sentences of review-answering copy nobody thought to write.
How It Works
This is the page that ends the argument.
| Metric | You | Competitor A | Competitor B |
|---|---|---|---|
| Listing Health Score | 58 / 100 | 84 / 100 | 71 / 100 |
| Title characters used | 71 / 200 | 186 / 200 | 142 / 200 |
| Bullets | 5, avg 84 chars | 5, avg 218 chars | 5, avg 165 chars |
| Images | 3 | 9 | 7 |
| Backend search terms | Empty | Full | Partial |
- ▸Your title uses 71 of 200 available characters. Competitor A uses 186 — that is indexable space you are giving away for free.
- ▸Backend search terms are empty. Highest impact, lowest effort fix on the list; buyers never see the field and Amazon indexes it anyway.
- ▸Three images against nine. Two of yours are the same angle.
- ▸Reviews mention “leaks when pouring” eleven times across the category, and your listing never addresses it. Competitor A answers it in bullet three.
Illustrative figures. Real audits report only what was read on the live pages.
What You Get
- A Listing Health Score out of 100 — Across seven weighted areas, computed from the scraped page in our own code so it never drifts.
- A head-to-head against your rivals — Your listing beside one or two competitors on the numbers that decide conversion.
- A ranked fix list — Ordered by impact against effort, so the cheapest wins are at the top rather than buried.
- The objections costing you sales — Mined from the actual review text on your listing and theirs, matched against what your page answers.
- Character-count analysis — Title and bullets measured against Amazon’s real limits, showing exactly how much indexable space you are leaving unused.
- A backend search term audit — The field buyers never see and Amazon indexes anyway — usually the single cheapest fix available.
- An image coverage comparison — How many images you run, how many they run, and which angles you are missing.
- A full rewrite — Title, bullets, description, backend search terms and FAQs, driven by the findings this audit produced.
- Before and after, side by side — Every rewritten field shown against the original so nothing changes without you seeing it.
- A content policy check — Run against Amazon’s rules before you paste, so the copy you publish is copy that survives.
Where other market research tools stop, this keeps going.
Most tools hand you a PDF and walk away. TurboAgents gives you two things a static report can’t: charts you can actually use, and an analyst you can actually talk to.
A score that does not move when you are not looking
Ask a chat window to rate your listing twice and you get two different numbers. Ours is arithmetic — computed from the scraped page in our own code, with every component visible. You can disagree with a weighting, but you cannot be quietly told something different tomorrow.
The objections costing you the sale
Your reviews and your competitors’ reviews contain the actual reasons people hesitate, written in the words they use. We read that text rather than the star rating, pull out what recurs, and tell you which objections your listing currently leaves unanswered — which is usually the cheapest conversion fix on the page.
A rewrite that will not get you suppressed
Amazon rejects listings for promotional language, unsupported claims and formatting nobody warned you about. Every rewrite is checked against those content rules before it reaches you, so the copy you paste in is copy that survives. And the rewrite is fed the audit’s own findings — it fixes what was flagged, not generic best practice.
AI vs. an Amazon agency vs. fixing it yourself.
| Criteria | TurboAgents | Amazon agency | Doing it yourself |
|---|---|---|---|
| Turnaround | ~2 minutes | 1–2 weeks | A weekend |
| Cost | From $29/mo | $500–3,000 | Free, and slow |
| Repeatable score | Yes — same page, same number | Opinion | None |
| Reads competitor listings | 1–2, live | Yes | Manually, in tabs |
| Reads customer reviews | Yes, the text | Sometimes | If you have the time |
| Rewrite driven by the findings | Yes | Yes | Usually generic |
| Content policy checked | Before you paste | Yes | You find out later |
| Run it on a stranger’s listing | Yes | No | No |
Use Cases
- →
Seller losing to one specific competitor — Put both listings side by side and get the actual differences scored, instead of staring at their page wondering what they know.
- →
Brand with a catalogue on Amazon — Run every SKU and fix the ones scoring worst first, rather than rewriting the listings you happen to look at.
- →
Agency pitching an Amazon client — Audit a prospect’s live listing before the meeting — it works on any public URL, so you arrive with findings rather than questions.
- →
Seller who just got a conversion drop — Check what changed against rivals and see whether the problem is the page or the price, before rewriting anything.
- →
New seller launching a first product — Score the listing before you drive traffic to it, when a fix still costs nothing but ten minutes.
- →
Anyone who has never filled in search terms — Find out in two minutes whether the cheapest indexing win on Amazon is sitting empty on your page.
Frequently Asked Questions
Your live Amazon product URL and at least one competitor URL. A second competitor is optional but makes the comparison more reliable. Nothing needs connecting — no seller account, no API access.
All of them — India, US, UK, Germany, UAE and the rest. Amazon only, though. Flipkart, Myntra, Etsy and your own store are deliberately out of scope; the Product Description & SEO Pack covers other marketplaces.
In our own code, from the facts scraped off the page — character counts, image counts, field completeness, pricing signals and review sentiment across seven weighted areas. The model never returns the number. That is why the same unchanged listing scores identically every time.
Yes, the text rather than the star rating. Reviews on your listing and your competitors’ are mined for recurring objections and the exact language buyers use, then matched against what your page currently addresses.
Yes — title, bullets, description, backend search terms and FAQs, shown before and after side by side. It is driven by the specific findings the audit produced, so it fixes what was flagged rather than applying generic best practice. The rewrite is charged separately, so you can run the audit alone.
It is checked against Amazon’s content rules first — promotional language, unsupported claims, character caps and duplicate search terms — and anything flagged is rewritten before it reaches you.
Yes. It works on any public Amazon URL, which is why it is the one tool here you can run live in a sales meeting on a prospect’s own product.
Because without one the audit degrades into a generic checklist. Almost every meaningful finding is comparative — your title is short compared with what, your image count is low against whom. The rival is what turns advice into evidence.
That area is dropped and its weight redistributed across the areas we could read — never scored as a zero, which would quietly punish you for our fetch failing. If the run itself fails, your tokens are returned automatically.
After any material change to the listing or the price, and whenever a competitor overtakes you. It takes about two minutes, so there is no reason to work from a stale audit.
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