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  • Predicting Returns with Review Sentiment – Actowiz Solutions

Case Study: How Actowiz Solutions Enabled Return Prediction Using Consumer Sentiment Analysis from Amazon & Walmart Reviews

Actowiz Solutions helped a global brand use consumer sentiment scraping from Amazon & Walmart reviews to predict product returns and improve design decisions.

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Real-Time Regional Insights with Customizable E-commerce Dashboards

Client Overview

  • Client: Global Apparel & Footwear Brand
  • Region: Operations across the U.S. (focus on Midwest and South regions)
  • Retail Channels: Amazon, Walmart, Brand Website, 200+ Retail Outlets
  • Engagement Duration: 7 months (2024 Q2–Q4)
  • Data Partner: Actowiz Solutions

The Business Problem

The-Client

With tens of thousands of monthly online orders, the client faced two major challenges:

1. High return rates for certain products—ranging from 15% to 35%—but lacked insight into why.

2. Limited access to structured consumer feedback beyond their own post-purchase surveys, which had a <5% response rate.

Returns were cutting into profit margins, bloating reverse logistics costs, and impacting customer satisfaction.

The client needed to proactively detect products likely to be returned, and adapt product features, size guides, and inventory strategies accordingly.

Why Actowiz Solutions?

Actowiz Solutions proposed a consumer sentiment analytics solution, driven by real-time review scraping from Amazon and Walmart—two platforms where customers freely express detailed opinions on product performance, fit, material, and durability.

Our Approach

Key-Solutions

The solution involved 4 key phases:

  • 1. Review Data Scraping
  • 2. NLP-Based Sentiment Classification
  • 3. Return Prediction Modeling
  • 4. Actionable Dashboard Reporting

📥 1. Review Data Scraping from Amazon & Walmart

Key-Challenges

Actowiz crawled reviews for over 2,000 SKUs across apparel, footwear, and accessories. Each review pulled included:

  • Product Name & Category
  • Platform (Amazon/Walmart)
  • Review Title & Text
  • Star Rating (1–5)
  • Reviewer Location
  • Review Date
  • Verified Purchase Indicator
  • Attached Images
  • Size/Color/Variant Details
Sample Raw Scraped Data:
SKU Platform Star Review Text Location Date
M-TRK-BLK-L Amazon 2 Too tight around the thighs. Returned it. Houston, TX 2024-08-12
W-JKT-RD-M Walmart 5 Color is vibrant. Fits well even after wash. Atlanta, GA 2024-08-14
K-SND-YW-10C Amazon 3 Strap broke in a week. Got a refund. Phoenix, AZ 2024-08-16

🧠 2. Sentiment Analysis Using NLP

Using custom-trained Natural Language Processing (NLP) models, Actowiz tagged reviews into:

  • Positive, Neutral, or Negative
  • Mapped to categories: Fit, Quality, Appearance, Sizing, Durability, Comfort
  • Detected intent such as: “Returned”, “Exchanged”, “Will Buy Again”, “Cancelled”
Example Sentiment Breakdown (Women’s Jackets):
Aspect Positive (%) Neutral (%) Negative (%)
Fit 54% 22% 24%
Fabric 66% 18% 16%
Zipper 39% 40% 21%
Return Flag — — 13% (explicit mentions of “return”)

This tagging enabled early identification of SKUs showing return-related dissatisfaction even before internal return reports flagged issues.

🔁 3. Return Prediction Modeling

Actowiz built a machine learning model trained on:

  • Review sentiment scores
  • Volume of negative aspect mentions
  • Star rating trends over 30, 60, and 90 days
  • Review velocity (surge in reviews = launch phase or trending SKU)

The model categorized SKUs as:

  • Low Risk (<10% return)
  • Moderate Risk (10–20%)
  • High Risk (>20%)
Sample Prediction Output:
SKU Avg Star Return Flags Sentiment Score Risk Level
M-TRK-BLK-L 2.8 15% -0.45 High Risk
W-JKT-RD-M 4.6 0.5% +0.81 Low Risk
K-SND-YW-10C 3.2 11% -0.33 Moderate Risk

📊 4. Visualization & Insights Dashboard

The client was given access to a custom BI dashboard with:

  • SKU-wise sentiment tracking
  • Aspect-level complaint drill-down
  • Regional return prediction (e.g., higher complaints in Southern states for tighter fits)
  • Weekly alerts for “rising risk” products
  • Comparison with in-house return logs for validation

📈 Business Impact

✅ Faster Response to Problematic SKUs

The client proactively paused promotion of 36 SKUs within 2 weeks of launch due to early return risk signals from Amazon reviews—saving an estimated $210K in reverse logistics costs.

✅ Improved Product Design Decisions

Feedback around tight fits and poor zipper quality led to:

  • Updated fit templates for next production batch
  • Supplier switch for zippers on two high-risk product lines
  • Added “size-up” notice for selected styles
✅ Marketing Copy Optimization

By identifying language in 5-star reviews, the client revised product bullet points to echo customer-preferred phrases like “lightweight but cozy” and “stretchy waistband”—improving conversion rates by 12%.

🎯 Regional Return Trend Examples

State SKU Complaint Type Suggested Action
Texas M-TRK-BLK-L “Too Tight” Add Size Guide Pop-Up
Georgia K-SND-YW-10C “Weak Strap” Reinforce Strap or Remove
California W-JKT-RD-M “Color mismatch” Standardize color photos

💬 Client Testimonial

“Actowiz didn’t just give us review data. They gave us return prevention power. We now flag high-risk products within a week of launch—and act on them fast.”

— VP, Customer Insights, Global Apparel Brand

🧩 Why Actowiz Solutions?

  • Proven success in Amazon & Walmart review scraping
  • Custom sentiment engines trained on apparel and footwear lexicon
  • Historical trend tracking and return signal detection
  • Secure, scalable infrastructure with 99.9% data accuracy
  • Seamless dashboard/API integration with ERP, CRM, and analytics tools

🧠 Future Enhancements

Key-Challenges

Actowiz is enhancing its return prediction solution with:

  • Image sentiment AI to detect visible product issues (e.g., damaged or poor fit images)
  • Social media comment scraping to capture feedback from Instagram, Reddit, and Facebook
  • Multilingual sentiment parsing to expand coverage beyond English
  • Voice-of-Customer scoring for sales and support teams to react faster

✅ Summary of Results

Metric Before Actowiz After Actowiz (6 Months)
Average Return Rate 21.3% 14.1%
Return Cost Savings — $340,000+
SKU Risk Classification Accuracy — 87%
Design Feedback Cycle 3 months 2 weeks
Marketing Copy CTR Uplift — +12%

🔚 Conclusion

Returns aren’t just a logistics issue—they're a customer sentiment signal. With Actowiz Solutions, global retailers can proactively analyze, predict, and reduce returns by listening to the voice of the customer where it's loudest: in online reviews.

From Raw Data to Real-Time Decisions

All in One Pipeline

Scrape → Structure → Analyze → Visualize
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Look Back Analyze historical data to discover patterns, anomalies, and shifts in customer behavior.

Find Insights Use AI to connect data points and uncover market changes. Meanwhile.

Move Forward Predict demand, price shifts, and future opportunities across geographies.

Ecommerce
Q-Commerce
Travel & OTA
Food Delivery
Real Estate
Social Media
Trusted by Global Leaders – Secured by International Standards

Industry:

Coffee / Beverage / D2C

Result

2x Faster

Smarter product targeting

★★★★★

“Actowiz Solutions has been instrumental in optimizing our data scraping processes. Their services have provided us with valuable insights into our customer preferences, helping us stay ahead of the competition.”

Operations Manager, Beanly Coffee

✓ Competitive insights from multiple platforms

Industry:

Real Estate

Result

2x Faster

Real-time RERA insights for 20+ states

★★★★★

“Actowiz Solutions provided exceptional RERA Website Data Scraping Solution Service across PAN India, ensuring we received accurate and up-to-date real estate data for our analysis.”

Data Analyst, Aditya Birla Group

✓ Boosted data acquisition speed by 3×

Industry:

Organic Grocery / FMCG

Result

Improved

competitive benchmarking

★★★★★

“With Actowiz Solutions' data scraping, we’ve gained a clear edge in tracking product availability and pricing across various platforms. Their service has been a key to improving our market intelligence.”

Product Manager, 24Mantra Organic

✓ Real-time SKU-level tracking

Industry:

Quick Commerce

Result

2x Faster

Inventory Decisions

★★★★★

“Actowiz Solutions has greatly helped us monitor product availability from top three Quick Commerce brands. Their real-time data and accurate insights have streamlined our inventory management and decision-making process. Highly recommended!”

Aarav Shah, Senior Data Analyst, Mensa Brands

✓ 28% product availability accuracy

✓ Reduced OOS by 34% in 3 weeks

Industry:

Quick Commerce

Result

3x Faster

improvement in operational efficiency

★★★★★

“Actowiz Solutions' data scraping services have helped streamline our processes and improve our operational efficiency. Their expertise has provided us with actionable data to enhance our market positioning.”

Business Development Lead,Organic Tattva

✓ Weekly competitor pricing feeds

Industry:

Beverage / D2C

Result

Faster

Trend Detection

★★★★★

“The data scraping services offered by Actowiz Solutions have been crucial in refining our strategies. They have significantly improved our ability to analyze and respond to market trends quickly.”

Marketing Director, Sleepyowl Coffee

Boosted marketing responsiveness

Industry:

Quick Commerce

Result

Enhanced

stock tracking across SKUs

★★★★★

“Actowiz Solutions provided accurate Product Availability and Ranking Data Collection from 3 Quick Commerce Applications, improving our product visibility and stock management.”

Growth Analyst, TheBakersDozen.in

✓ Improved rank visibility of top products

Trusted by Industry Leaders Worldwide

Real results from real businesses using Actowiz Solutions

★★★★★
'Great value for the money. The expertise you get vs. what you pay makes this a no brainer"
Thomas Gallao
Thomas Galido
Co-Founder / Head of Product at Upright Data Inc.
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2 min
★★★★★
“I strongly recommend Actowiz Solutions for their outstanding web scraping services. Their team delivered impeccable results with a nice price, ensuring data on time.”
Thomas Gallao
Iulen Ibanez
CEO / Datacy.es
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★★★★★
“Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing highly recommended!”
Thomas Gallao
Febbin Chacko
-Fin, Small Business Owner
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See Actowiz in Action – Real-Time Scraping Dashboard + Success Insights

Blinkit (Delhi NCR)

In Stock
₹524

Amazon USA

Price Drop + 12 min
in 6 hrs across Lel.6

Appzon AirPdos Pro

Price
Drop −12 thr

Zepto (Mumbai)

Improved inventory
visibility & palniring

Monitor Prices, Availability & Trends -Live Across Regions

Actowiz's real-time scraping dashboard helps you monitor stock levels, delivery times, and price drops across Blinkit, Amazon: Zepto & more.

✔ Scraped Data: Price inights Top-slling SKUs

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Our Data Drives Impact - Real Client Stories

Blinkit | India (Relail Partner)

"Actow's helped us reduce out of ststack incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

US Electronics Seller (Amazon - Walmart)

With hourly price monitoring, we aligned promotions with competitors, drove 17%

✔ Scraped Data, SKU availability, delivery time

Zepto Q Commerce Brand

"Actow's helped us reduce out of ststack incidents by 23% within 6 weeks"

✔ Scraped Data, SKU availability, delivery time

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