REVIEWS & RATINGS INTELLIGENCE

Catch the ratings dip
before the quarter does.

"Ratings dipped in one region and nobody noticed for a month."

// THE SHORT ANSWER

Reviews and ratings intelligence collects customer reviews, star ratings and Q&A for your products (and competitors') across every platform and region, then scores them for sentiment and recurring themes. iWeb Data Scraping surfaces quality issues, delivery complaints and competitor weaknesses weekly — so a ratings dip in one region is caught in days, not discovered in a quarterly review. Reviews are PII-scrubbed at collection, keeping the text and rating without the reviewer's identity.

Get free sample in 48h How it works
99%+field accuracy, QA-verified
48hfree sample turnaround
24/7pipeline monitoring
ISO 27001+ 9001 certified

Key facts

  • 100% — of platforms & regions in one view
  • Weekly — sentiment & theme tracking
  • PII-free — reviewer identities scrubbed at source

Reviews are the highest-signal, lowest-latency feedback your customers give — and most brands read them one platform at a time, too late to act. A product-quality problem, a courier failing in one city, a competitor's recurring complaint: all visible in reviews weeks before they show in sales. Reviews intelligence makes that signal systematic.

We collect reviews, ratings and Q&A across every platform and region you sell in, score sentiment and cluster themes, and deliver a weekly read on what's rising and falling — for your products and your rivals'. Personal identifiers are scrubbed at collection, so you get the content and the signal, compliantly. It runs on the same pipeline as our managed scraping.

THE POINT

The gap isn’t knowing this matters — it’s seeing it in time to act. That’s what the feed is for.

100%of platforms & regions in one view
Weeklysentiment & theme tracking
PII-freereviewer identities scrubbed at source
WHAT YOU GET

Every review, scored
and clustered.

Cross-platform collection

Reviews, ratings and Q&A gathered across every marketplace, app and region you operate in — one view.

Sentiment scoring

Each review scored for sentiment, so trends are quantifiable — a dip is a number, not a hunch.

Theme clustering

Recurring topics surfaced automatically — 'leaking cap', 'late delivery', 'wrong size' — ranked by volume.

Regional breakdown

Ratings and themes by city and platform, so a localized problem doesn't hide in the national average.

Competitor review mining

Rivals' recurring complaints and praise — their weaknesses are your positioning.

PII scrubbed at source

Reviewer names and identifiers removed in collection — content and rating retained, identity dropped.

SEE THE DATA FIRST

What you'll actually receive.

Real sample structure from this feed. Your free 48-hour sample comes in your category, in this shape — CSV, JSON or straight to your warehouse.

Review intelligence — sentiment scored, themes clustered.
platform rating sentiment themes region date
Amazon 2 -0.7 leaking cap; packaging West 2026-07-06
Blinkit 5 +0.9 value; fast delivery North 2026-07-06
Amazon 3 -0.1 late delivery South 2026-07-05
Flipkart 1 -0.8 wrong item; courier West 2026-07-04
↑ Sample structure — illustrative values. Your data reflects your platforms and category. Get this for your data →
HOW IT WORKS

From question to answer.

STEP 1

Set products & platforms

We define your SKUs, competitors and the platforms and regions to monitor.

STEP 2

Collect & score

Reviews gathered, sentiment scored, themes clustered — for you and named rivals.

STEP 3

Deliver the weekly read

Rising issues, regional dips and competitor patterns surfaced where your team sees them.

WHY BUY VS BUILD

The details in the feed.

FIELDS Rating, review text, sentiment score, theme tags, platform, region, date
ENRICHMENT Sentiment scoring + automatic theme clustering
COVERAGE All platforms & regions for your SKUs and named competitors
PII POLICY Reviewer identifiers scrubbed at collection
DELIVERY Weekly scored report or BI feed; CSV/API/warehouse
RELATED:Digital Shelf Analytics →Social Media Scraping →Product Reviews Dataset →
FAQ

Before the first call.

It collects customer reviews, star ratings and Q&A across every platform and region you sell in, scores each for sentiment, and clusters recurring themes — for your products and competitors'. The result is a weekly, quantified read on product quality, delivery issues and competitor weaknesses, instead of manually reading reviews one platform at a time.

Yes — reviews are public content, and we scrub personal identifiers (reviewer names, handles) at collection, so the dataset keeps the review text, rating and metadata without identifiable individuals. This keeps it clear of GDPR-style privacy concerns while preserving all the signal that matters.

Yes — competitor review mining is a core use. Rivals' recurring complaints reveal category-wide pain points and specific weaknesses you can position against, while their praise shows what buyers reward. It's benchmarking from the customer's own words.

Reviews are broken down by region and platform, so a ratings dip in one city surfaces instead of averaging away nationally. Multiple languages are supported, with sentiment scored in-language, so regional signal stays accurate rather than lost in translation.

Get a free sample dataset in 48 hours.