CASE STUDY

Sentiment Analysis & Pain Point Extraction

Transform 870 Customer Reviews into Actionable Insights

See how conbase.ai transforms lengthy customer feedback into precise sentiment analysis, urgency scoring, and pain point identification—converting what used to take days of manual analysis into a streamlined pipeline that delivers immediate actionable insights for your customer experience team.

⚡ Build Your First Pipeline

The Challenge

Companies struggle to efficiently process large volumes of customer reviews to extract meaningful patterns and urgent issues, resulting in missed opportunities to address customer concerns and improve products.

⨯

Time Requirements

5 minutes per review manually, limiting response time to customer concerns

⨯

Output Variability

50% consistency across different analysts reviewing the same content

⨯

Technical Expertise

Requires sentiment analysis knowledge and customer experience expertise

⨯

Volume Constraints

Staff capacity limits prevent scaling beyond 150 reviews per day

conbase
Data Processing Efficiency

870 Customer Reviews Analyzed in 7.25 h

Complete a week's worth of review analysis in just over 7 hours.

Processing time for 870 customer reviews
Case Solution

The Process

Headline: The Process

1

Data Preparation

Imported 870 customer review records from multiple product categories

2

Pipeline Configuration

Configured a 2-step workflow for sentiment extraction and pain point identification

3

Testing & Refining

Tested the pipeline on diverse review samples to ensure accurate sentiment detection and pain point categorization

4

Processing & Export

Processed all 870 reviews in 7.25 hours

⚡ Get a Guided Demo

Transform your product data with conbase.ai

Data Specifications

1 The Data

The customer review dataset contains detailed feedback across multiple products, ranging from highly positive to extremely negative sentiments, with varying degrees of urgency and specific pain points.

Data Volume

870 records

Data Structure

CSV format with 6 fields per record

Data Quality

Complete customer reviews with ratings and timestamps

Structure Overview

Field Sample Data
review_id 2
customer_id 1002
product_id 502
review_text "Disappointment doesn't even begin to describe my experience..."
rating 1
review_date 2023-05-02
⚡ Transform Your Product Data

No coding required — Get started in minutes

Technical Overview

2 The Pipeline

The two-stage pipeline transforms raw customer reviews into actionable insights with consistent sentiment analysis and pain point identification.

1

Extract Sentiment

Analyzes review text and rating to determine overall sentiment polarity and assigns an urgency score.

Input Fields

  • review_text
  • rating

Outputs

  • sentiment
  • urgency_score
2

Identify Pain Points

Extracts specific customer pain points from negative and neutral reviews to highlight areas for improvement.

Input Fields

  • review_text
  • sentiment

Outputs

  • pain_points
⚡ Build Your First Pipeline

Process 500 reviews in minutes, not days

Technical Overview

3 Testing & Refining

In this step we tested each pipeline action singularly and in combination with the other actions to make sure we get the correct results.

! Sample Output

Review Text
"Disappointment doesn't even begin to describe my experience. The item arrived in a damaged condition that was clearly mishandled during shipping. Not only was the product compromised, but when I reached out to customer service, I was met with complete indifference. The representative seemed uninterested in resolving my issue and made no genuine attempt to help. The lack of professionalism was shocking, and I felt completely disrespected as a customer. Save yourself the frustration and look elsewhere."
1 Sentiment
negative
2 Urgency Score
2
3 Pain Points
damaged product upon arrival, indifferent and unprofessional customer service, lack of resolution from customer service
⚡ Build Your First Pipeline

Transform your data in minutes, no technical skills required

Performance Metrics

4 The Results

The conbase.ai pipeline delivered significant improvements in review analysis efficiency and accuracy.

90%

Time Savings

72.5 hours → 7.25 hours

98%

Quality Improvement

Accuracy over manual process

98%

Consistency at Scale

Across all 870 records
Review Example Sentiment Urgency Score Pain Points
"I'm absolutely thrilled with this product..."
positive
1
-
"Disappointment doesn't even begin to describe..."
negative
2
damaged product upon arrival, indifferent and unprofessional customer service, lack of resolution from customer service
"After careful consideration, I'm giving this product..."
positive
2
sizing runs smaller than standard measurements, potential fit issues
"My experience with this product was decidedly average..."
neutral
2
color discrepancy, potential mismatch between product images and actual product delivered
"Wow! This product is a total game-changer..."
positive
1
-
Showing 5 of 870 processed reviews
Process more reviews

Transform your review analytics with precise sentiment and urgency insights

⚡ Try conbase.ai Today

14-day free trial — No credit card required

LET CONBASE.AI DO THE WORK

Still Analyzing Customer Reviews Manually?

Transform your customer feedback analysis from days to hours with accurate, actionable insights.

Pipeline Action Manual Process Generic AI conbase.ai
Extract Sentiment (time per unit) 2.5 minutes 50 seconds 15 seconds
Identify Pain Points (time per unit) 2.5 minutes 50 seconds 15 seconds
Total Time Per Unit 5 minutes 1.67 minutes 30 seconds
Metric Manual Process Generic AI conbase.ai
Total Processing Time (for 870 units) 72.5 hours 24.2 hours 7.25 hours
Accuracy (%) 65% 75% 98%
Sentiment Precision (%) 70% 80% 95%
Time Saving vs Manual (%) N/A 66.7% 90%
Time Saving vs Generic AI (%) N/A N/A 70%
Consistency (%) 50% 75% 98%
⚡ Schedule a Free Demo Today

No credit card required

Ⓒ Copyright. All rights reserved by conbase.ai