What is Customer Sentiment Data? Examples, Datasets and Providers
What is Customer Sentiment Data?
Customer sentiment data refers to the information that reflects customers’ feelings and opinions about a brand, product, or service. This data is gathered through various channels such as social media, customer reviews, feedback forms, and surveys. By analyzing customer sentiment data, businesses can gain insights into customer satisfaction, brand perception, and areas for improvement.
What are Examples of Customer Sentiment Data?
Examples of customer sentiment data include positive, negative, and neutral feedback from social media posts, online reviews, survey responses, and customer service interactions. This data helps businesses understand how customers feel about their offerings and identify trends or issues that need addressing.
Best Customer Sentiment Datasets & APIs
TagX Ecommerce Reviews data | Customer sentiment Analysis | Customer feedback data | Ecommerce data
The Data Appeal | Sentiment Data | API, Dataset | 200 Million+ POI Data Mapped | Monitor Customer Sentiment and Satisfaction by Points of Interest
Customer Sentiment Data: 2+ Years of Insights for Market Research & Customer Insights (G2, Capterra,Trustpilot) | Public Web Data
WiserBrand | Customer Feedback Data | Customer Experience Data | Unique Consumer Sentiment Data: Transcription of the calls to the companies
PromptCloud | Consumer Review Insights | Customer Sentiment Data Analysis | Market Trends | Scrape Ecommerce Websites
The Data Appeal | Map Data | API, Dataset | 200 Million + POI Data Mapped | Evaluate Customer Experience and Sentiment
WiserBrand | Customer Feedback Data | Customer Experience Data | Reasons of the calls from consumers to companies
FileMarket |AI & ML Training Data from Sotheby's International Realty | Real Estate Dataset for AI Agents | LLM | ML | DL Training Data
The Data Appeal | Business Listings Data | API, Dataset | 200 Millions POI Data Mapped | Evaluate Customer Experience & Sentiment
WiserBrand.com: Customer Feedback Data | Customer Experience Data | 140 000+ companies | 5 000 000+ reviews from PissedConsumer
Monetize data on Datarade Marketplace
Customer Sentiment Data Attributes
- Sentiment Scores: Quantitative analysis indicating positive, negative, or neutral sentiment.
- Emotion Detection: Analysis of emotions expressed in customer feedback.
- Topic Analysis: Identifying key themes and topics in customer discussions.
- Feedback Trends: Patterns and changes in customer sentiment over time.
How is Customer Sentiment Data Collected?
Customer sentiment data is collected using:
- Text analysis tools
- Sentiment analysis algorithms
- Natural language processing (NLP) techniques
These tools analyze text from social media, reviews, and surveys to determine sentiment scores. Additionally, businesses can use customer feedback platforms and CRM systems to gather sentiment data from direct customer interactions and feedback.
Why is Customer Sentiment Data Important?
Customer sentiment data provides a direct insight into how customers perceive a brand and its offerings. By understanding customer sentiment, businesses can make informed decisions to improve customer experiences, enhance products or services, and address any negative perceptions. Positive sentiment is linked to customer loyalty and brand advocacy, while negative sentiment can highlight areas that need improvement.
Customer Sentiment Data Use Cases
- Brand Reputation Management: Monitoring and responding to customer feedback to maintain a positive brand image.
- Product Development: Using sentiment analysis to gather insights for product improvements or new features.
- Marketing Campaigns: Crafting targeted marketing strategies based on customer opinions and emotions.
- Customer Service Improvement: Identifying common issues and improving service responses based on sentiment data.
- Competitive Analysis: Comparing customer sentiment across competitors to identify strengths and weaknesses.