8 Real-World Sentiment Analysis Use Cases www.repustate.com
One of the most effective ways to measure marketing and branding campaigns is to analyze consumer sentiment around them. Sentiment analysis of your brand gives you tangible data to review your strengths, weaknesses and business opportunities. Let’s see in-depth, what sentiment analysis is and what it can do for your business. As well as, eight real-world examples where companies have used sentiment analysis as a business strategy for growth, brand insights and competitor analysis.
What Are Real-World Examples of Sentiment Analysis? Almost every industry, company or organization today is going through some form of digital transformation that results in greater and greater quantities of both structured and unstructured data. The biggest challenge that companies have is turning their unusable, unstructured data into useful insights that can help them make data driven decisions, create operational efficiencies, value improvement, and overall competitive advantage. Any industry can benefit from text analytics and sentiment analysis, as all industries collect data and require that it is transformed into actionable, tangible intelligence that can be applied to drive change. Here are some real-world use cases of sentiment analysis across industries and geographies that demonstrate this.
1. Sentiment Analysis in Banking
2. Sentiment Analysis in Call Centers A European mobile network operator wanted to integrate its call center software so it could track and analyse all customer service representative (CSR) interactions. They wanted to get a sense as to what the tipping point of a certain number of negative interactions was, that was causing customer attrition. Repustate’s robust sentiment analysis software analysed each stored call. They were first converted to text using an intricate speech-text program and then decoded to look for semantic meaning in relation to products and services. All this data was further broken down into a granular level to check if a customer sustained a negative overall sentiment below a certain score. If the software identified this, a text message was sent to the customer apologizing for the inconvenience and they were also offered discounts and other promotional offers.
3. Sentiment Analysis in Healthcare A large healthcare consultancy company called Health-Links, based in Jeddah, reached out to Repustate because it needed help in its efforts to improve the overall quality of healthcare in the Gulf region including villages. The company locates the invisible dysfunctions and gaps in care services and maps every phase of the patient’s journey at a hospital with thorough, data-backed information. They wanted a sentiment analysis solution that could read and analyse Arabic text accurately without using translations, and have the scalability and speed to process 12 million surveys, at the least.
Why is Sentiment Analysis Important for Businesses? Sentiment analysis turns unstructured data into meaningful information. It is powered by Machine Learning - a part of AI that runs on algorithms that propel the software to keep learning and improving itself automatically through experience. Unstructured data gathered from social media listening, chatbots, medical and call centre transcripts, survey responses, and the like, can be powerful reservoirs of intelligence. They can guide focused, strategic change for overall improvement in a brand’s value proposition, brand experience, and value delivery.
The insights gained from sentiment analysis can help a company bring accurate change and transformation of their business. It can be in areas that are either creating the most negative sentiment such as product features, price, return policies, customer service, or prices, or areas that stakeholders are most positive about such as net banking, price match, and such. Overall, these strategic measures help businesses: 1.
Become more competitive
2.
Attract new customers
3.
Retain present customers
4.
Sell more products and services
5.
Reduce customer servicing
6.
Make customers more profitable
7.
Improve marketing messages and campaigns
Understand your data, customers, & employees with 12X the speed and accuracy.
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