123ArticleOnline Logo
Welcome to 123ArticleOnline.com!
ALL >> Business >> View Article

Automating Review Sentiment Dashboards For Amazon, Flipkart & Myntra

Profile Picture
By Author: DataZivot
Total Articles: 61
Comment this article
Facebook ShareTwitter ShareGoogle+ ShareTwitter Share

Automating Review Sentiment Dashboards Across Amazon, Flipkart & Myntra

Business Challenge

A leading omnichannel retail brand with 200+ SKUs across fashion and electronics platforms faced this recurring issue:
“We manually check Amazon and Flipkart reviews every week, but it’s too slow to act on.”

The brand’s product and marketing teams lacked:
A centralized review sentiment view
A way to track sentiment shifts daily
Live keyword monitoring across categories
They partnered with Datazivot to build a fully automated, cross-platform sentiment dashboard updated in near real-time.

Objectives

Scrape and process daily Reviews from Amazon, Flipkart, and Myntra
Run sentiment analysis and keyword extraction for all SKUs
Build an automated dashboard by product, brand, and platform
Provide alerting for negative sentiment spikes or trending complaints

Our Approach

1. Real-Time Review Scraping Infrastructure
We deployed dedicated scrapers and rotating proxy pools to extract review data every 12 hours.
Fields Captured:
...
... SKU & Product Name
Review Title & Body
Star Rating
Platform
Timestamp
Sentiment Score
Feature Mentions (e.g., battery, fit, color, packaging)
Platforms Integrated:
Amazon.in
Flipkart.com
Myntra.com

2. Sentiment + Keyword Pipeline
Used BERT and RoBERTa models for sentiment tagging.
Built keyword classification based on category:
Fashion: fabric, stitching, fit, design, delivery
Electronics: battery, audio, UI, packaging, build quality
We added time-series analysis to detect rising complaint clusters (e.g., “battery drains fast,” “size mismatch”).

Note: SKUs with negative sentiment >25% are auto-flagged for weekly review

3. Dashboard Architecture
Backend: Python ETL scripts (scheduled via Airflow), AWS Lambda
Database: Google BigQuery for scalable review storage
Frontend: Google Data Studio + Power BI (client-selected)
Alert System: Slack + Email notifications when negative mentions spike

Key Features of the Dashboard
SKU-Level View
Avg rating, review count, sentiment breakdown (last 7, 30, 90 days)
Keyword cloud with volume and polarity
Trend Tracker
Daily sentiment shifts
Top emerging positive/negative keywords
Spike alerts for product managers
Category Comparisons
Which category (e.g., shirts, mobiles, shoes) has the best customer sentiment?
Identify gaps vs competitors (integrated competitor tracking in Phase 2)
Automated Weekly Summary Report
Sent every Monday morning to product and marketing heads

Outcomes & Impact

1. Reduced Review Monitoring Time
Manual review checks that took 6–8 hours/week were replaced with auto-generated dashboards.
Marketing and product teams could focus on acting, not aggregating.
2. Faster Sentiment Response
Negative spikes now detected within 12–24 hours of trend onset.
Example: A “loose stitching” issue in a Myntra-exclusive SKU was caught in 36 hours, preventing 300+ potential returns.

3. Marketing Campaign Alignment
Positive keyword trends like “comfortable fit,” “premium look,” and “fast delivery” were integrated into ad creatives and influencer briefs.
Click-through rates increased by 18% on campaigns using sentiment-derived messaging.

Strategic Value Delivered

Fully automated sentiment feedback loop
Real-time product insight engine
Actionable voice-of-customer (VoC) monitoring
Alerts for reputation risk management
Rather than relying on anecdotal feedback or outdated monthly summaries, the client now had a data-driven radar across all major platforms.

Conclusion
With a live dashboard powered by Datazivot, the brand moved from reactive review reading to proactive sentiment-led decision-making.
No more scattered spreadsheets or delayed decisions — just a single screen showing exactly what their customers felt, platform-by-platform, product-by-product.

Want your review data to work while you sleep?
Datazivot builds automated sentiment dashboards across Amazon, Flipkart, and Myntra—so you act on customer feedback faster than ever.

Originally Published By https://www.datazivot.com/automated-review-sentiment-dashboards-amazon-flipkart-myntra.php

Total Views: 56Word Count: 473See All articles From Author

Add Comment

Business Articles

1. The Evolution Of The Fanny Pack Over The Years
Author: iven gayash

2. Powering Sustainable Agriculture With Efficient Pumps
Author: Sundar

3. Step Inside Tomorrow: How Cogito's 3d Walkthroughs Redefine Coimbatore Spaces
Author: cogito

4. How To Pick The Best Civil Contractor In Valasaravakkam For Your Home Project
Author: bharathi

5. Enhancing Your Property With Quality Driveways, Patios, And Pathways: A Comprehensive Guide
Author: Vikram kumar

6. The Importance Of Surface Finishing In Aluminum Products
Author: bqmp

7. Simplifying Global Trade With Workseer’s Advanced Hs Code & Eccn Classification Tools
Author: sumit

8. How To Start A Crab-themed Home Garden For Beginners
Author: bharathi

9. How To Choose The Best Six Sigma Training Institute In Chennai
Author: bharathi

10. Rv Essentials For Long-term Living: What You Really Need
Author: Devon Curran

11. Dubai's Best Laptop Screen Replacement Services: Fast, Dependable Fixes
Author: laptop screen replacement services in dubai

12. Black Magic Specialist In Udupi
Author: astrobest09

13. Steps For Plastic Injection Molding Process
Author: Ryan

14. Understanding Injection Mold Life: Spi Classes And Key Longevity Factors
Author: Ryan

15. How To Identify High-quality Stainless Steel Flanges
Author: Neelam Forge India

Login To Account
Login Email:
Password:
Forgot Password?
New User?
Sign Up Newsletter
Email Address: