What’s the need for ecommerce sentiment analysis? The e-commerce industry in India is experiencing unprecedented growth. In the ever-evolving world of e-commerce, businesses are constantly seeking innovative ways to understand and cater to their customers’ needs. However, with the sheer volume of customer reviews on different platforms, it is challenging for businesses to do manual monitoring and derive customer sentiment insights from them.
Customer reviews for Samsung Galaxy S23 on Amazon
For example, smartphone, Samsung Galaxy S23 smartphone has over 670 reviews on Amazon (Fig 1), 320+ reviews on Flipkart (Fig 2), 600+ reviews on Snapdeal, and many more. If we have to manually extract online reviews from multiple marketplaces to identify customer sentiment and pain points, it becomes challenging. This is where ecommerce sentiment analysis comes into play.
Customer reviews for Samsung Galaxy S23 on Flipkart
The Need for Ecommerce Customer Sentiment Analysis
Ecommerce sentiment analysis involves employing advanced natural language processing approaches and machine learning algorithms to analyze and categorize customer feedback. In today’s competitive e-commerce market, customer sentiment analysis has emerged as a strong tool that empowers businesses to gain a profound understanding of the sentiments and opinions voiced by their valued consumers.
Examples of positive and negative sentiment are as follows:
Customer Review 1
“I loved the quality of the product delivered and was impressed with the speed of delivery. I got my product before the estimated date of delivery.”
Customer sentiment – Positive
Here, the client can use the feedback to understand their strengths and leverage them to enhance the customer experience in the future.
Customer review 2
“I’m disappointed with the customer service team. It took too long to connect to the agent, and when I finally did, the response was unhelpful. Would never opt for the service again.”
Customer sentiment – Negative
Here, the client can use the feedback to work with the customer service department and address the pain points of customers.
Ecommerce sentiment analysis acts as a strategic advantage, serving the gap between customer expectations and the product/service delivered. Understanding customer emotions helps tailor product and service offerings for businesses.
Power of Ecommerce Sentiment Analysis
Enhanced Customer Experience
A recent report from Adobe that surveyed 1,500 U.S. adults regarding preferences and expectations for digital experiences in the retail, travel & hospitality, media & entertainment, and financial services industries found that expectations for customer experience are much higher coming from the millennial age group than ever before.
With millennials and modern customers demanding higher customer experience, it is imperative for brands to closely monitor customers’ pain points and devise strategies to outcome them. By understanding the positive and negative aspects of a product, businesses can act on it effectively.
For example, let us take the Samsung Galaxy S23 smartphone. What if businesses can easily analyze the positive and negative aspects of the product for different product features like a Camera, Battery, Display, Performance, Size, Design, charger, screen, fingerprint sensor, and more?
Well, that would help with improving the product and make it better right? The great news is, it is possible with 42Signals – an e-commerce analytics tool.
Based on the insights generated from online reviews and ratings, 42Signals helps e-commerce businesses identify the sentiment type, share of discussion, and sentiment score for different aspects of the product with a comprehensive ecommerce sentiment analysis feature.
Competitive advantage
The insights derived from customer reviews enable businesses to understand how their products and services are perceived by their customers. This can help businesses adopt strategies to stay ahead of the competition.
With 42Signals’ easy-to-use dashboard, customers can see how they compare to competitors concerning different aspects of their product.
42Signals – competitive advantage dashboard
How Leading Businesses are Leveraging Customer Sentiment Analysis to Their Advantage
Uber
One of the popular ride-sharing businesses uses ecommerce sentiment analysis to analyze customer reviews and ratings. Uber uses these insights to address the concerns of customers, improve customer service, access driver performance, their pricing in the market, and more. This enables them to optimize their strategies and improve customer experience.
Nike
Nike has been using customer sentiment analysis to fine-tune its marketing and ad strategies. By using customer sentiment analysis, Nike monitors customer reactions to its product launches and marketing efforts.
Marriott International
When people think about the Marriott International hotel chain, they instantly think about consistency in luxury. That’s what customers expect and that’s what they get. Marriott’s secret to success isn’t a secret at all: it’s good CX that involves listening to customers, in person, and via their digital footprint. Customer data tell the real story about everything that customers love and don’t love. They have been using sentiment analysis to gauge customer opinions and monitor feedback. This enables them to address the pain points and enhance CX.
Choosing the Right Customer Sentiment Analysis Tool
Now that you understand the importance of customer sentiment for your business, it is time to choose the best tool that can help you make the right decision.
Look for tools that can accurately analyze and interpret customer sentiment and that have advanced NLP capabilities. Moreover, clear and comprehensive visualizations are important for easy data interpretation. So, choose a tool that has an easy-to-analyze dashboard and customization options.
Easily comprehend customer sentiment with our powerful AI tool, 42Signals. It helps businesses identify the most relevant topics discussed by consumers by sifting through millions of product reviews. Discern multiple facets of your brand to comprehend customer behavior as we bridge the gap between products and consumers.
Frequently Asked Questions on ECommerce Sentiment Analysis
What are the three types of sentiment analysis?
Sentiment analysis is used to determine the emotional tone behind text data. The three main types are:
- Polarity-Based Sentiment Analysis – Classifies text as positive, negative, or neutral based on emotional tone.
- Example: A review saying, “I love this phone; it’s amazing!” is classified as positive sentiment.
- Emotion-Based Sentiment Analysis – Identifies specific emotions such as joy, anger, sadness, or surprise.
- Example: “I feel frustrated with the slow service!” → Classified as anger.
- Aspect-Based Sentiment Analysis – Analyzes opinions on specific product features or topics rather than general sentiment.
- Example: In a restaurant review, “The food was great, but the service was slow,” the food gets positive sentiment, while service gets negative sentiment.
Can ChatGPT do sentiment analysis?
Yes, ChatGPT can perform sentiment analysis by evaluating text input and classifying it as positive, negative, or neutral. While it does not natively analyze sentiment in bulk datasets, it can:
- Interpret and categorize user sentiment from text-based inputs.
- Help businesses assess customer feedback manually by summarizing emotions in product reviews or social media comments.
- Generate sentiment analysis code using Python libraries like TextBlob, VADER, or Hugging Face models.
How does Amazon use sentiment analysis?
Amazon uses sentiment analysis to enhance customer experience and business operations in several ways:
- Product Reviews & Ratings Analysis – AI scans customer reviews to determine common issues and feedback trends.
- Chatbot & Customer Service Optimization – Sentiment-driven AI prioritizes urgent complaints and routes them to human agents when needed.
- Competitor Benchmarking – Amazon monitors sentiment on competing products to adjust pricing and marketing strategies.
- Personalized Recommendations – Positive product sentiment can influence Amazon’s AI-driven suggestions for similar products.
Example: If multiple customers mention “battery life” negatively in a smartphone review, Amazon may flag the issue for manufacturers or adjust the product’s ranking accordingly.
Why do e-commerce companies make use of sentiment analysis?
E-commerce businesses rely on sentiment analysis to understand customer opinions, improve products, and optimize marketing strategies. Key benefits include:
- Enhancing Customer Experience – Identifies negative feedback early to address complaints proactively.
- Improving Product Listings – Helps brands modify product descriptions and features based on recurring complaints or praise.
- Refining Ad & Marketing Campaigns – Measures public reaction to promotions and refines ad targeting accordingly.
- Boosting Brand Reputation – Detects potential public relations risks before they escalate into crises.
- Optimizing Pricing Strategies – If sentiment trends show high customer satisfaction at a specific price point, businesses can adjust prices accordingly.
