Sentiment Analyzer for E-Commerce

AISS-SentimentAnalyzer identifies sentiments in texts and tells whether a given text contains positive sentiments, negative sentiments or its combinations. It assigns sentiment scores for each sentiment and extracts the attributes associated with the sentiments.


Huge amounts of text data can be instantly classified by the AISS-SentimentAnalyzer i.e, assigned labels, sentiment attributes and the sentiment scores. Thus the resulting text data will now be structured and ready to provide the actionable insights.


Once the text is tagged with the predefined classes, the potential applications are unlimited. Applications range from being as simple as just classifying the text based on the sentiments (eg: categorizing customer reviews under positive/negative labels and significant attributes based on the contents without reading them), to using the analysis reports for further improvement of the products, identifying new marketing opportunities, etc...


The following are few examples of how marketers can use the AISS-SentimentAnalyzer to analyze product reviews/comments on online shopping sites.

Let us consider the following is the review section of a mobile phone: Review 1: I bought this two weeks ago. The battery life could have been better. Review 2: Best camera ever. Review 3: I am planning to buy this in the next sale. Review 4: Good phone Review 5: Poor battery

Sentiments: Positive; Negative

Results*: Review 1: Positive and Negative Review 2: Positive Review 3: Positive Review 4: Positive Review 5: Negative

Much more complex applications such as automating several business processes such as Marketing, Customer Relationship Management, fulfilling online orders, etc… are also possible when AISS-SentimentAnalyzer is combined with various other primary technology from AISS.


*The following are the screenshots of the actual analysis performed by our Text Analytics module on the example review sentences shown above.

Review 1:The reviewer has expressed both positive and negative sentiments in one line. Our AI has identified and the positive and negative parts of the review and has specified the attributes (Spans) corresponding to each sentiment.


Review 2: The reviewer has positively commented on the product.


Review 3: The reviewer has positively expressed their intent of purchase.


Review 4: The reviewer has positively commented on the product.


Review 5: The reviewer has negatively commented on the product.


Unlike the traditional way of identifying business objectives and then developing complete products around those business requirements, primary techs of AISS can be seamlessly integrated with each other in various sequences to create a complete solution which can achieve specific business requirements thereby greatly reducing associated time and costs.


If you would like our experts to provide a walkthrough of the AISS, please request a demo by filling out the form. A member of our team will reach out to you shortly to schedule a meeting.



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