Blinkit reviews and ratings data show how shoppers rate your products and how those ratings change over time. So FMCG and D2C brands can spot weak products, benchmark rivals, and fix problems before sales slip.

The stakes keep rising, too. In Q2 FY27, Blinkit’s net order value rose 79.3% to ₹20,940 crore, across 2,751 stores. As a result, more of your sales and more of your ratings now flow through one app.

This guide explains what Blinkit shows publicly, which fields to collect, and how to turn ratings into product fixes.

What Blinkit Shows: Ratings, Rating Counts and Reviews

Blinkit product listings usually show an average star rating out of five. Many also show a rating count. However, newly listed products often show no rating until enough shoppers rate them.

Written product reviews are a different story. Product pages focus on ratings, so written reviews are rarely visible there. As a result, most Blinkit reviews and ratings data is numeric.

For written feedback, look at Blinkit’s app reviews instead. On Google Play, the app rates 4.7 stars from over 1 crore reviews. Similarly, the App Store shows 4.7 stars from 3.9 million ratings. These reviews mostly cover Blinkit’s service. Still, some mention product issues, such as damaged packs or short expiry dates.

Why Brands Need Blinkit Reviews and Ratings Data

Shoppers on Blinkit decide fast, and they have plenty of choice. In Delhi NCR alone, Blinkit’s catalogue grew to about 100,000 products in 2026. So a star rating is often the quickest signal shoppers see.

Quality also drives platform choice. In an October 2026 LocalCircles survey of Mumbai shoppers, 62% put product quality first when choosing a festive shopping platform.

Handling matters, too. Blinkit now holds about 90% to 95% of the stock it sells. So storage and handling at its dark stores shape what reaches shoppers. In addition, FSSAI wants online food sellers to deliver items with enough shelf life left. Its 2024 advisory set at least 30%, or 45 days, before expiry.

So when a rating drops, the cause may be the product, the pack, or the supply chain. That’s why Blinkit reviews and ratings data work best alongside price, stock, and delivery data.

Blinkit Reviews and Ratings Data Fields

Blinkit reviews and ratings data should include these fields:

How to Set Up Products and Pincodes

First, list your own SKUs, along with 5 to 10 rival SKUs in each category. Then pick fixed test addresses in your key cities and pincodes.

A product’s rating may look the same across cities. However, stock, price, and delivery times often change by pincode. So capture them together, because local issues can explain a rating shift.

Finally, keep every capture of your Blinkit reviews and ratings data. Listings show the current average rating, so the history is yours to build.

How to Collect Blinkit Reviews and Ratings Data

Blinkit doesn’t offer a public API for product or rating data. So brands either scrape public listings or use a managed feed of Blinkit reviews and ratings data.

Follow these steps:

1. Pick products: start with your top SKUs and their closest rivals.
2. Set locations: use the same test addresses every time, so results stay comparable.
3. Collect on a schedule: weekly suits most brands, while daily helps after a launch or a pack change.
4. Capture context: record price, discount, stock, and delivery time with each rating.
5. Store history: save each capture with a timestamp, then track changes over time.
6. Add written reviews: pull text from Blinkit’s app reviews and your other channels.

Compliance and Personal Data

App reviews can show reviewer names and photos. So leave out anything that identifies a person, and follow each site’s terms. In addition, India notified its Digital Personal Data Protection Rules in November 2025, with a phased rollout. This isn’t legal advice, so check with a lawyer.

For more on collecting this data, see our quick commerce data scraping service.

Product Sentiment Analysis With Blinkit Ratings

With Blinkit reviews and ratings data, sentiment comes mostly from ratings and how they move. Start with three signals:

• Rating level: the current average, compared with rival products.
• Rating velocity: new ratings per week, from the change in rating count.
• Recent rating: the average of only the newest ratings.

The recent rating is the most useful, because the headline average moves slowly. You can estimate it from two captures. For example, say a product moves from 4.40 with 1,000 ratings to 4.30 with 1,200. Then the 200 new ratings average about 3.80.

The formula is: (new average × new count − old average × old count) ÷ number of new ratings. However, displayed ratings and counts are often rounded. So only trust this estimate across large batches of new ratings.

Tagging Written Reviews

Where you have written reviews, tag each one by aspect. Then score it as positive, neutral or negative:

Also, reviews often mix English, Hindi, and Hinglish. So use a multilingual model, then check a sample by hand.

Turning Blinkit Reviews and Ratings Data Into Product Fixes

Once your Blinkit reviews and ratings data is clean, link each rating change to a likely cause:

• Pack problems: a drop after a pack change, with leak or damage complaints, points to the pack.
• Short shelf life: drops alongside expiry complaints suggest checking stock rotation with Blinkit.
• Value concerns: a drop after a price rise or a smaller pack suggests testing price or size.
• Listing mismatch: “smaller than it looks” comments suggest updating images and pack details.
• Rival gaps: if a rival rates higher, compare pack size, price, and claims.

For example, say your 1-litre juice slips from 4.4 to 4.2 in a month, while a rival holds 4.5. If app reviews mention leaking cartons in the same weeks, test a stronger cap first.

KPIs to Track

• Average rating by SKU: compared with your category’s average.
• New ratings per week: a rough guide to sales momentum.
• Recent rating: the average of the newest ratings.
• Rival gap: your rating minus the average of close rivals.
• Complaint share: the share of written reviews about each aspect.

Common Pitfalls

• Reading only the headline rating: it hides recent drops.
• Ignoring context: stockouts and price changes often explain rating shifts.
• Mixing service and product issues: a late delivery isn’t a product problem.
• Judging new SKUs too early: wait for enough ratings first.

How FoodSpark Delivers Blinkit Reviews and Ratings Data

FoodSpark collects public Blinkit product data, including ratings, for your products and your rivals. Here’s what you get:

• Fields: average rating and rating count, as well as price, discount, stock, and delivery time, where shown publicly.
• Reviews: written review text, where shown publicly.
• Location: by city and pincode.
• No personal data: we leave out reviewer names and profiles.
• Refresh: one-time, weekly, daily, or hourly.
• Delivery: CSV, JSON, or XML, through a REST API or webhook. Or we push it to AWS S3, BigQuery, Snowflake, or Google Sheets.
• Free sample: 100 rows in CSV or JSON, so you can test our Blinkit reviews and ratings data first.

See our Blinkit grocery data scraping service and Blinkit API. For pricing context, read our guide to Blinkit price tracking. Alternatively, use our Blinkit, Zepto and Instamart benchmarking guide to compare prices.

We collect public data only, with no personal user data, payment information, or non-public content.

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Blinkit Reviews and Ratings Data: FAQs

What is Blinkit reviews and ratings data?

It’s structured data on how shoppers rate products on Blinkit. Typically, it includes each product’s average rating, rating count, price, and stock, captured over time.

Does Blinkit show product ratings?

Yes, on many listings. Product pages usually show an average star rating, and often a rating count. However, new products may show none.

Does Blinkit show written product reviews?

Written reviews are rarely visible on product pages. So pair ratings with Blinkit’s app reviews and reviews from your other channels.

Does Blinkit have a public API for ratings?

No. Blinkit doesn’t offer a public API for product or rating data. So brands use public listings or a managed data feed.

How often should I track Blinkit ratings?

Weekly collection of Blinkit reviews and ratings data suits most brands. However, track daily after a launch, a pack change, or a price change.

Can you analyse reviews in Hindi or Hinglish?

Yes. Use a multilingual model, or translate reviews first, then check a sample by hand.

How much does Blinkit ratings data cost?

Overall, it depends on products, cities, fields, and refresh. So start with a free 100-row sample, and then get a custom quote.