Helium 10 Killed Review Insights: 5 Tested Alternatives

On December 3, 2025, Helium 10 removed Review Insights from its Chrome Extension. They cited Amazon's updated policies. A redesigned version was promised for early 2026. As of July 2026—seven months deep into the Review Insights Gap—nothing has shipped. If you relied on that feature to pull and filter Amazon reviews, you're stuck. And if you were on the $49/mo Starter plan? Helium 10 killed that in April. Cheapest option now is $99/mo. We stopped waiting for them to fix it. Here are the five tools sellers are actually using to close the Review Insights Gap—and which one matches what you actually need.

Why Helium 10 Review Insights is Not Working — and Is It Coming Back?

The December 3 removal

Helium 10 didn't choose this. Amazon changed its Chrome Extension policy (Manifest V3) and enforced stricter rules on how extensions can scrape data. Review Insights violated those rules, so Helium 10 had to shut it down.

The frustration isn't the removal. It's the silence. Helium 10 said a redesign was coming "early 2026." Nothing. Radio silence. Sellers built workflows around that feature. Now it's gone, and there's no clear path back.

The redesign that isn't shipping

Here's what we know: Helium 10's own knowledge base says "Temporarily Unavailable." But seven months in? "Temporarily" doesn't mean anything anymore.

You have two choices: Wait and hope, or find a tool that actually works today.

The Two Jobs Review Insights Did

Review Insights wasn't one thing. Most sellers used it for two very different jobs — and the right replacement depends on which job you actually need to fill.

Job #1: Scrape reviews — Get raw review data out of Amazon so you can filter and analyze it yourself with full control. Export to CSV. Filter by star rating or date range. Work with the data in your own way, for instance if you want to run a sentiment analysis or use ChatGPT to analyze your Amazon reviews.

Job #2: Analyze reviews — Have a tool automatically extract themes, complaints, and insights from reviews and tell you what they mean for your listing or product development.

These are not the same job. A tool that's great at raw extraction may be useless for analysis, and vice versa. Pick wrong and you'll spend more time in the tool than outside it.

How We Tested

We picked one real Amazon product (ASIN B01M3VVK7U), mid-tier traffic, 1,352 reviews, not category-sensitive. We ran each tool through it and scored them against two separate rubrics: one for scrapers, one for analyzers.

One important context: Amazon publicly shows ~10 reviews on a product page at a time. Some extension-based tools are limited to just those visible reviews, where you dont need a valid login. The real value is in the review detail page where one can read hundreds of reviews.

Let's go job by job.

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Job #1: Scraping Reviews — Get Your Raw Data

If you want raw reviews to filter and analyze yourself, these are your options.

SellerSprite

What it does: Pulls reviews into a filterable table, exportable to Excel/CSV. Browser extension that pages through Amazon review pages automatically.

How it works: Two separate tools in one product. The browser extension pages through Amazon's review pages and exports raw data to Excel — that's the scraping job. The web platform's AI Review Analysis runs independently (top 300 reviews, sentiment across 6 dimensions) — that doesn't require the extension.

The raw CSV export flow is different: that report requires the extension to collect reviews from the listing page first.

What we got on B01M3VVK7U: During the free trial, the extension exported 255 reviews (out of 1,352 total), spanning 2017–2026, with full rating distribution.

One important caveat: SellerSprite requires a logged-in Amazon session. If you scrape at high volume, Amazon may flag or block your account. This is a real risk for sellers running frequent bulk exports.

Pricing: 3-day free trial (no credit card). Paid plans start at ~$19/mo.

Scoring:

• Export format? ✅ Excel / CSV
• Date filter? ✅ Yes — date column included in export
• Star filter? ✅ Yes — rating included, filterable in Excel
• Simple to use? ✅ Install extension → visit product page → click "Download reviews"

Bottom line: The easiest dedicated review scraper. One click from the Amazon product page. Most recommended on Reddit for this job. Just be mindful of scraping volume — Amazon account risk is real.

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ExportComments

What it does: ExportComments.com is a web-based Amazon review exporter — no extension needed. Paste a product URL, download reviews to CSV, Excel, or JSON.

We couldn't test it: The export feature is not available on the free tier. A paid plan is required to actually download reviews. The free tier only lets you configure the export — then hits a paywall.

Scoring:

• Export format? ✅ CSV / Excel / JSON (paid)
• Date filter? ❌ Not available
• Star filter? ✅ Filter by star rating before export
• Needs extension? ❌ None — purely web-based

Cost: Free tier is configuration-only. Paid plan required to export.

Bottom line: No extension to install, which is the main appeal. But we couldn't verify the actual export quality since it's paywalled. If you need a web-based option without installing anything, it's worth paying for — just go in knowing the free tier doesn't actually export anything.

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Descripio API (Free)

What it does: Programmatic access to Amazon review data. One API call returns all cached reviews for any ASIN as JSON — no extension, no browser, no scraping from your machine.

Who it's for: Developers and technical sellers who want to pipe review data directly into spreadsheets, Python scripts, or ChatGPT workflows. Not a point-and-click tool — you need to be comfortable with curl or a fetch call.

Setup:

1. Create a free account at app.descripio.com/signup — no credit card required
2. Go to API Keys in the dashboard
3. Click Create Key — copy the key and store it securely

Making the call:

The endpoint is a simple GET request with your ASIN and API key:

curl "https://app.descripio.com/api/v1/reviews?asin=B01M3VVK7U" \
  -H "Authorization: Bearer YOUR_API_KEY"

Or in JavaScript:

const res = await fetch(
  "https://app.descripio.com/api/v1/reviews?asin=B01M3VVK7U",
  { headers: { Authorization: "Bearer YOUR_API_KEY" } }
);
const data = await res.json();
console.log(data.reviewCount, data.reviews.length);

One important note from the docs: fetching cached reviews doesn't count against your quota. Only triggering a new refresh job (POST /reviews/refresh) uses quota. On the free tier that means 100 refresh requests/month — reads are unlimited.

Response object:

The top-level response contains product metadata plus the review array:

Field	Type	Description
asin	string	Product ASIN
title	string	Product title
imageUrl	string	Product image URL
marketplace	string	Amazon marketplace (e.g. amazon.com)
reviewCount	number	Total reviews on Amazon
reviews	Review[]	Cached review array
lastScraped	string	ISO 8601 — when data was last refreshed
cached	boolean	true if served from cache

Each item in reviews contains:

Field	Type	Description
id	number	Internal review ID
amazonReviewId	string	Amazon's own review identifier
title	string	Review headline
content	string	Full review text
date	string	ISO 8601 review date
isTopReview	boolean	Amazon "top review" flag
country	string	Reviewer country code (e.g. US, DE)
scrapedAt	string	ISO 8601 — when this review was collected

Convert to CSV in one line: jq -r '.reviews[] | [.date, .country, .title, .content] | @csv' response.json > reviews.csv

Pricing: Free tier: 100 refresh requests/month. Paid plans from $29/mo (1,000 requests) to $299/mo (30,000 requests). Reads are always free regardless of plan.

Scoring:

• Export format? ✅ JSON (one jq command to CSV)
• Date filter? ✅ date field on every review
• Star filter? ⚠️ Not a query param — filter in code after fetching
• Simple to use? ⚠️ Requires API/CLI knowledge

Bottom line: The most flexible option and the only one with no per-review cost ceiling on reads. If you can run a curl command, this gives you structured JSON you can pipe anywhere. Not for sellers who need a click-and-download interface.

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Job #2: Analyzing Reviews — Get Actionable Insights

If you want a tool to extract themes, complaints, and listing recommendations from reviews automatically, these are your options.

Jungle Scout Review Analysis

What it does: Analyzes review trends, extracts positive and negative themes, and surfaces common product issues. Strong on pattern recognition across review sets.

The top-50 limit: Jungle Scout only analyzes the top 50 most helpful reviews for a product — not all reviews. For products with hundreds of reviews, you're getting a sample. This matters if you're working with high-volume ASINs.

Scoring:

• Positive analysis (what customers like)? ✅ Themes and highlights
• Negative analysis (quality issues)? ⚠️ Complaints surfaced, no issue timeline
• Review coverage? ⚠️ Top 50 most helpful only

Cost: $99/mo (7-day trial).

Bottom line: Best for sellers who want processed insights rather than raw data. The top-50 cap is a real limitation for high-review products.

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Descripio App (Free)

What it does: Analyzes your Amazon reviews against your product listing. Two separate jobs in one tool: it tells you what customers love that you're not mentioning (listing gaps), and what they're complaining about (product issues and quality alerts).

Be honest: Descripio is our tool. We're scoring it hard. It's not a raw review exporter — if you need CSV download, this won't replace Review Insights 1:1.

We ran it on the same ASIN (B01M3VVK7U, 107 reviews). Here's what came out.

The overview tells you immediately: 15 keyword topics from reviews aren't in the listing yet, and it prioritized the top three to fix. That's the starting point — two tabs do the real work below.

What Customers Like — Listing Gaps

The first tab shows you what customers are praising and checks whether those themes are already covered in your bullet points, A+ text, and product images.

"Safety Features" comes up 5x across reviews — customers care about the no-boil-dry protection. But the listing only partially covers it in bullet points, and it's completely missing from A+ Text and product pictures.

The missing topic is specific: the listing never mentions "good safety features" as a characteristic. The source review even tells you the exact language customers use. You copy that language into your bullet, click "Generate Content," done.

Improvement Opportunities — Quality Alerts

The second tab is where Descripio goes beyond listing optimization into product development intelligence. This is the part most tools skip entirely.

For this kettle: 72 quality issues identified from 107 reviews. The issue timeline shows complaints spiking in recent months — not a historic pattern. The 4 most recent alerts are all durability failures from February 2026.

The full issue list breaks down into 9 distinct failure modes with real review quotes, countries, and dates. "Rusted inside after two weeks," "leaks when pouring because the lid is not sealed well," "starting to mold." If you're the brand owner, this is a sourcing brief for your factory. If you're a private label seller evaluating this niche, this is a product improvement roadmap.

This is what Helium 10 Review Insights never did — it exported raw reviews. It didn't tell you which issues are spiking, when they started, or what's causing repeat complaints.

Scoring:

• Positive analysis (listing gaps)? ✅ Per-topic coverage across bullet points, A+ Text, images
• Negative analysis (quality alerts)? ✅ Issue timeline, distinct failure modes, source reviews
• Review coverage? ⚠️ Top 100 most recent + 100 most helpful

Free tier: Full analysis on the free plan. No credit card required.

Bottom line: If you want to improve your listing and understand what's actually breaking in your product, this is the fastest path. One click, results in two minutes. Not a data export tool — an action tool.

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Side-by-Side Comparison

Job #1: Scraping (Raw Review Export)

Feature	SellerSprite	ExportComments	Descripio API
Export format	Excel / CSV	CSV / Excel / JSON	JSON
Date filter	✅	❌	✅
Star filter	✅	✅ Filter before export	⚠️ Filter in code
Review limit (free trial)	255 on trial	❌ Export requires paid plan	None
Needs extension?	Yes	❌ No	❌ No
Ease of use	⭐⭐⭐⭐⭐	⭐⭐⭐⭐	⭐⭐ (requires API)
Price	Free trial / ~$19/mo	Paid plan required	Free

Job #2: Analysis (Automated Insights)

Feature	Jungle Scout	Descripio App
Positive analysis (listing gaps)	✅ Themes	✅ Per-topic, per-placement
Negative analysis (quality alerts)	⚠️ Complaints listed	✅ Issue timeline + failure modes
Review coverage	⚠️ Top 50 most helpful	Top 100 recent + 100 helpful
Price	$99/mo	Free

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Tools We Tested That Didn't Work

You'll see these names online. Here's the reality:

Apify — There is no official Amazon API for review data. Apify hosts unofficial Amazon review scrapers built by third-party developers. The most-used one for reviews is the Amazon Reviews Scraper by hypnotic_freedom. Some scrapers work; many break as Amazon updates its pages. We tested several and most failed on current Amazon layouts. Technical sellers may find one that holds up, but reliability is a genuine problem. Proceed with caution and expect maintenance.

Stackline — Vendor-grade analytics requiring brand registry. Overkill for most sellers.

Comet AI browser — Too early-stage. Not mature enough for production use.

EcomStal — Reddit OP tried it. "Wasn't reliable." We agree.

Tools You'll See Recommended That Don't Solve This Problem

These show up in every "Helium 10 alternatives" list online. They shouldn't be here.

Keepa — Price history tracker. Zero review analysis.

SmartScout — Keyword research + BSR tracking. Not review export.

AMZScout — Product research tool. Surface-level review feature. Not the same job.

Data Dive — Popular in Germany. Focused on product insights, not review extraction.

Good tools. Wrong job.

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Which Path: Scrape or Analyze?

The question isn't "which tool is best." It's "which job do I actually need?"

Choose scraping (Job #1) if:

• You have a VA, analyst, or strong ChatGPT workflow
• You want to filter reviews by star rating or date in bulk
• You're building your own tracking spreadsheet
• You want flexibility over speed

Choose analysis (Job #2) if:

• You want to improve your listing directly
• You don't have time to parse raw data
• You want to know what to change, not just what the reviews say
• Speed matters more than control

Most mid-size sellers (5–20 SKUs) end up using one of each: a scraper for bulk pulls, an analyzer for listing work.

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Which Tool for Which Seller Size

1–3 SKUs

ExportComments (paid, web-based) or SellerSprite (free trial). Manual is fine at this scale. Spend an hour a month. Don't pay $99 for Jungle Scout.

5–20 SKUs

SellerSprite ($29/mo) + Descripio App (free). Speed on both jobs. $30/mo pays for itself in saved time.

20+ SKUs

SellerSprite or Descripio API for scraping. Descripio App or Jungle Scout ($99/mo) for analysis. Automation is mandatory. Manual doesn't scale here.

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Is Helium 10 Better Than SellerSprite?

For pure review scraping, SellerSprite wins on price (40–60% cheaper). When Review Insights was live, Helium 10's interface was slightly smoother — but that doesn't matter when the feature is offline. With Review Insights gone since December 2025, SellerSprite is your default for scraping. For review analysis, it's a different comparison — Helium 10 never had strong analysis tools.

What Real Sellers Say

The original Reddit thread that kicked off this research? Here's what sellers are actually doing:

From the OP: "Export Amazon reviews to CSV/Excel. Filter by star rating range. Filter by date range. No duplicates, no 100-review limit."

@enzoshumanty confirmed the cause: "Amazon changed their TOS so they had to disable that feature."

@Interesting-Store-15 flagged SellerSprite: "SellerSprite has free review downloads." (True — we exported 255 reviews free on our test ASIN.)

@Dependent-Highway886 shared the pain: "Had to go through and manually do this. It kinda sucks because some competitors have thousands of reviews."

@rxr77 mentioned Apify: "There are scrapers on Apify, $5/mo free credit — but reliability varies if you're comfortable with command line."

Real sellers aren't looking for perfect. They're looking for what works today.

Once you've got your reviews into a tool that actually works, the next step is using them to optimize your listing. Review-based optimization beats keyword-stuffing — your customers told you exactly what to say. You're just listening.

FAQ

What's the cheapest Helium 10 Review Insights alternative? For scraping: SellerSprite (free trial, then ~$19/mo) or Descripio API (free, no cap). For analysis: Descripio App (free). For a web-based no-extension option: ExportComments (paid plan required to export).

Can I still use ChatGPT alone to analyze Amazon reviews? Yes. Copy reviews from the Amazon page. Paste into ChatGPT. Ask it to extract themes. It works — but doesn't scale past 2–3 ASINs before your time investment becomes ridiculous.

Will Helium 10 bring Review Insights back? Maybe. "Early 2026" was the promise. Seven months past that deadline and nothing has shipped. We're not betting on it. You shouldn't either.

What's the difference between review export and review analysis? Export = raw data (CSV, filter, then you decide what to do with it). Analysis = a tool that tells you what the data means (themes, complaints, sentiment). Both are useful. Different jobs.

Does Jungle Scout analyze all reviews? No — Jungle Scout's review analysis is limited to the top 50 most helpful reviews per product. For products with hundreds of reviews, that's a meaningful sample, not the full picture.

What if I have a tool you missed? The five above cover 95% of what sellers are actually using. If you've found something better, Reddit already knows about it.

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Stop Searching. Start Testing.

You've got five proven options split across two jobs. Pick the one that matches your workflow — not the one with the best marketing.

Try Descripio free — no credit card, no setup. Analyze your own reviews in two minutes and see what changes you should make to your listing. Analyze your first product free.

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