We offer customer sentiment analysis services that use NLP, AI/ML technologies, and data operation strategies.
Our insights help businesses understand their customers from their onsite experience and feedback to deliver exceptional services.
Drive onsite customer engagement with Sentiment Analysis
Attract, engage & retain your best customers
Sentiment analysis or opinion mining helps you to identify likes, dislikes, feelings, moods, and opinions and is often useful to social media assessments, reviews, blogs, community posts, chats, and many other parallel sources.
Industry-specific Sentiment Analysis
Hospitality
We offer sentiment analysis/analytics for hospitality and all other industries, nowadays the hospitality industry is more than delivering food and shelter.
Using sentiment analysis models, you can stand out from the competition and drive foot traffic to your locations.
Our Sentiment Analytics Python model uses real-time localized intelligence to drive continuous improvement at your locations.
Each review that visitors post on any platform is measured for sentiment analysis. It contributes in developing the positives and negatives of any hospitality and all other business.
It helped many leading hospitality businesses to analyze the variances in online discussions such as – the tone of discussions and buyer interests, which, in turn, facilitated them to recognize key supporters and critics.
Insurance
Help insurance businesses develop chatbots, enabling customers to perform other processes properly and with nominal intervention.
E-commerce
Sentiment analysis in e-commerce allows businesses to inspect the sentiment within product reviews, survey responses, and other online reviews.
Retail
Used to predict trends, understand customers’ sentiments, and analyze competition in product development.
Banking
Used to identify suspicious activity and sudden changes of behavior, understand the real sentiments of investors via sentiment analysis tools to track net promoter score, personalized customer offerings, and credit.
Identify how well you know your customers
How Our Sentiment Analytics Model Works
Key Features of Our Sentiment Analysis Solution
- Sentiment tracking in real-time
- Multi-language support
- Sentiment-based audience segmentation
- Emotion detection (sadness, anger, and joy)
- Aspect-enabled sentiment analysis
- Custom sentiment models for several sectors
Steps Involved in Sentiment Analysis
Use Cases of Sentiment Analysis
Brand management and social media monitoring
Companies can search for social media mentions and gather both negative and positive sentiments regarding the brand and its products.
CRM enhancement
Businesses can use customer sentiment to notify customer service representatives when a customer is not satisfied and help them refocus on the issue and respond to them with kindness.
Product analysis
Gathering feedback is necessary after the product and service launch. Sentiment analysis makes it easy to monitor reactions and suggestions.
Why Choose Our Sentiment Analysis Service?
Real-time tracking
Stay in touch with the most recent customer sentiments in real time.
Our services allow you to monitor and respond to fluctuating sentiments promptly.
Managing brand reputation
Monitor the reputation of your brand perfectly and manage negative sentiments before they grow rapidly.
Competitor analysis
Benchmark the sentiment of your brand against your competitors and identify regions of improvement.
Personalized Solutions
Our services can be personalized to match your business needs and industry needs.
Improved CX
Identify the demographics of your audience, inspect customer reviews, and pinpoint market trends to improve your services and products.
Decreased customer churn
Getting customer feedback and reviews in real-time helps in increased customer retention.
Domain expertise
We serve companies of small, mid, and large sizes to Fortune 500 companies having abundant experience.
Effortless integration
Our effortless cloud API enables fast and perfect cloud or in-house integration with your existing tech stack.