Flipkart India: Sentiment Analysis from 1L+ Product Reviews for FMCG Brand Planning

Overview

In India’s fast-evolving FMCG landscape, customer sentiment is a strategic asset—especially when harnessed at scale. With more than 100,000 Reviews Scraping and analyzed from Flipkart, Datazivot helped multiple FMCG brands decode real-time consumer opinions, detect pain points, and shape better product strategies.

This case study highlights how Flipkart review sentiment analysis powered better brand planning, SKU development, and packaging updates across food, personal care, and household categories.

Client Profile

• Industry: FMCG (Food, Hygiene, Household, Personal Care)
• Platform: Flipkart India
• Scope: 1,00,000+ reviews across 1,000+ SKUs
• Services Used: Review scraping, NLP-based sentiment analysis, keyword clustering, packaging & price feedback tagging

Objective

• Understand real feedback on taste, packaging, quantity, pricing, delivery condition
• Compare brand sentiment vs. competitors
• Plan 2025 product lineups using consumer voice
• Reduce returns and improve product satisfaction

Datazivot’s Solution

Flipkart Review Sentiment Intelligence :

Sample Extracted Review Data

Key Insights from 1L+ Review Sentiment Analysis

• Packaging Problems Drive Negative Sentiment

  19% of all negative reviews mentioned leakage, breakage, or spillage.
  80% of affected items were part of “combo” or value packs.

• Price Sensitivity in Tier-2 and Tier-3 Cities

  “Too costly for refill” and “smaller quantity now” were common in household cleaners and shampoos.
  Consumers expect value-per-rupee clarity in Flipkart listings.

• Delivery Conditions Affect Brand Trust

  Poorly packed liquids or heavy items result in lower review ratings, even if the product is good.
  “Sealed box” vs “taped pack” perceptions matter in hygiene and baby care products.

• Flavor/Taste Preferences for Food Items

  “Too sweet” or “no spice” shows strong regional taste variation.
  Brands adjusted seasoning SKUs based on South vs. North Indian reviews.

Use Case

Household Cleaning Brand Improves Packaging & SKU Strategy :

• Brand: CleanMax
• Problem: 2-in-1 combo packs of disinfectants were receiving 1 star reviews due to leakage

Datazivot Analysis:

• Scraped 7,000+ reviews across Flipkart
• 23% had keywords like “broken cap,” “half bottle,” “not sealed”
• Sentiment score dropped below 2.8 star for 2 weeks

Action Taken:

• Introduced tamper-proof cap and extra inner seal
• Reduced combo weight by 10% to improve handling
• Changed Flipkart listing images to show “double seal” visual

Results:

• Avg. rating rose from 3.1 to 4.2 within 30 days
• Negative packaging reviews dropped by 68%
• Repeat purchase rate grew 1.6X for Tier-2 buyers

Sentiment Breakdown Across FMCG Categories

Competitor Brand Benchmarking Example

How Flipkart Reviews Helped in 2025 Planning

• Product Line Revisions: Removed low-rated SKUs and repackaged high-potential ones
• Pricing Models: Adjusted pack sizes for ₹99, ₹199, and ₹499 tiers based on buyer perception
• Localized SKUs: Introduced spice variants and herbal formats based on regional sentiment clusters
• Trust Messaging: Added “Leak-Proof,” “New Cap,” and “Fresh Stock” tags based on review language

Why Datazivot?

Conclusion

FMCG Growth Begins with Listening :

For India’s FMCG brands, real feedback is no longer optional—it’s mission-critical. Review sentiment from Flipkart is the consumer’s voice at scale. With Datazivot, brands move beyond guesswork and into evidence-based product planning.

• Launch smarter SKUs
• Reduce packaging complaints
• Improve satisfaction and loyalty
• Align offerings with real demand

Want to Decode 2025 FMCG Sentiment on Flipkart?

Contact Datazivot for a free Flipkart sentiment snapshot across your product category and see how 1L+ review voices can reshape your strategy.