Sentiment Analytics

Adopt Sentiment Tracking to stay on the edge

• Track sentiment Across Channels: Exact , analyze, and act on sentiments across multiple touch points. Make sure your product resonates with the consumers, score big on customer experience, and rely on real-user feedback to inform your strategy.
• Plan Product Improvement: take the pulse of public opinion and consumer sentiment data into analyze your latest product release. Collect user insights to identify gaps, add much-awaited, features and improve user experience.
• Prioritize Customer Service Issues: Identify critical consumer issues and put top-priority service tickets at the head of the queue. Enable ChatGPT solutions to avoids escalations when consumer complaints arrive-based o users real-time feelings.
• Monitor Brand Reputation: Let our sentiment analysis company help you establish a strong brand image through NLP and machine Learning. Use sentiment data to spot negative mentors, react swiftly to alerts, and effectively manage your online reputation.

Sentiment Analysis for Brand Building

• Monitor your Brand’s Social Media: Make a health check of public opinion about your brand and verify is it’s in the green or the red zone. We build customer opinion tracking solutions that run opinion mining on unstructured data from the brands social media channel.
• Get Insights from Products Analysis.: Convert negative comments into positive interactions and keep customers satisfied during product changes. Uncover gaps between your product and the competition and predict your customer’s response to new products.
• Focus on the Voice of the Customers: Gain insight into customer expectations, preferences, and pain points to gain competitive intelligence. From VOC solutions analyze and derive insight from all types of voc data using a variety from analytical and visualization techniques.
• Track Your Competitors: Benchmark the strengths and weaknesses of your brand against competitors and detect reputation risks before they break loose. Lift your business ranking , get a better handle on your competitions , and position your products strategically.

Transform emotions into quantitative metrices and deliver the right products at the right time.

1. Get Live Insights: Use our customer sentiment analytics solutions to recognize emotions behind texts across the web and integrate customer interaction into a single source of truth.

2. Provide Better service: Gain a clear picture of the level of customer happiness, close the gap between your company and your customers and maintain high service quality.

3. Reduce Customer Churn: Gather unsolicited feedback to surface what’s truly top of mind for your clients. Identify frustrated customers and respond with right retention strategy.

4. Detect changes in customer opinion: Detect drops, and rises in optimism about your brand, monitor recurring trends, and align messages to consumer mind sets to build a positive brage image.

Industries We Serve: We inject our cross-domain experience into building customer solutions aligned with individual business needs like as : Ecommerce , Marketing and Advertising, Supply Chin & Logistics , Financial Services, Health Care and Pharma , Manufacturing.

Sentiment analysis as a service allows companies to look into the customer sentiment expressed through text or audio data . The technology enables individuals to identify , extract , quantify, and analyze subjective information as well as act on the subjective data to boost customer loyalty. Business can improve consumer satisfaction by analyzing how well the products or services click with the user needs. Companies can also employ the technology to predict the success of a new product or service.

Customer Sentiment Data: This type of data gives you an overall image of your customer’s emotions and opinions based on engaging with your brand at a specific moment. By getting a better handle on this data, you can measure customer satisfaction, identify pain points and track opinions over time. Best Models for Sentiment Analytics: The technology is based on the latest advancements of Machine Learning and NLP techniques. Sentiment analysis as a service can also be divided into fine-grained, aspect-based, emotion and intent-based analysis. The tech stack is different for each type.

There is no single best model for this technology. Instead , there are a variety of methods that can be used to build a sentiment analysis model with high accuracy. Some of the most popular methods for building sentiment analytics models include support vector machines, Naïve bays classifiers, and recurrent neural networks. Our ML engineers select a custom set of technologies that fit your data specs.

The technology has been proven to be an effective tool for improving customer experience driving sales and increasing revenue.

Some of the most popular use case in marketing include:

• Brand reputation monitoring.
• Audience Research
• Marketing /PR effort tracking.
• Influencer Marketing.