Struggling to choose between Microsoft Forms and Sentiments? Both products offer unique advantages, making it a tough decision.
Microsoft Forms is a Office & Productivity solution with tags like survey, questionnaire, quiz, form-builder.
It boasts features such as Create surveys, quizzes and polls, Distribute forms via links or embed in websites, Collect responses in real time, View analytics and summarize results, Grade quizzes automatically, Customizable themes, Accessibility support, Integration with other Microsoft 365 apps and pros including Free and easy to use, Good for basic forms and surveys, Real-time response collection, Automatic grading for quizzes, Analytics and summary views, Mobile-friendly forms, Good for education and business use cases.
On the other hand, Sentiments is a Ai Tools & Services product tagged with sentiment-analysis, natural-language-processing, machine-learning, text-classification.
Its standout features include Sentiment analysis, Text analysis, Document analysis, Keyword extraction, Entity recognition, Topic modeling, Language detection, Multi-language support, Custom models, Integration with apps, and it shines with pros like Accurate sentiment analysis, Easy to use interface, Good for analyzing social media, Can process large volumes of text, Customizable models and rules, Good for brand monitoring, Helps understand customer feedback.
To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.
Microsoft Forms is a survey, questionnaire, and quiz tool included in Microsoft 365. It allows users to easily create forms, polls, and quizzes and distribute them to others. Results and analytics are provided.
Sentiments is a sentiment analysis tool that allows users to analyze text or documents to understand the overall sentiment and emotional tone. It uses natural language processing and machine learning to categorize text as positive, negative, or neutral.