One of the most important part of running a profitable business is to attentively listen to what your customers want and how they feel so as to improve your services and increase customer satisfaction. Nowadays customers are becoming more and more vocal in sharing their experiences with different brands through social media channels, blogs and review sites. To unlock the hidden value of this text in order to understand the customer’s opinions and needs companies are increasingly using sentiment analytics to make better and more informed business decisions.
Sentiment analytics harnesses the power of machine learning and artificial intelligence to determine whether a piece of writing is positive, negative or neutral. It helps in extracting value from the wealth of information available in the form of tweets, reviews, comments etc. It can also lead to increased understanding of the business.
An Indian mobile network operator that offered voice and internet services had an 85 million subscriber base. The telecom company had a sizeable social media presence with more than 0.6 million followers on Twitter. The company was encountering a myriad of customer opinions about the brand on social media in the form of tweets, comments etc. The company wanted to gauge the customer sentiment towards the brand.
To uncover the hidden value of the tweets and comments the company had to set up an architecture which could extract tweets and comments in real time and integrate the text data into a single data mart. The incoming data was in huge volume and was being extracted at a rapid velocity. Legacy data storage systems were not able to keep up to the velocity and volume of incoming data. So the company had to set up a Hadoop based big data architecture to store the data. The data stored was then analyzed using advanced machine learning techniques and algorithms and the output was displayed in the form of dashboards so as to get a comprehensive picture of the customer opinions about the brand. It was observed that about 20% of the tweets were negative nature.
On the basis of the customer opinion the company was able to:
- Fine tune the marketing strategy: The Company had a social media marketing strategy in place to promote its brand and services so as to impart a message to its audience. By listening to what the customers felt and thought about the brand the company was able to adjust high level messaging to meet their needs.
- Gauge the effectiveness of the marketing campaigns: The effectiveness of the marketing campaigns not only depends on the web and social media traffic but it also depends on the amount of positive discussion you are able to facilitate on social media platforms.
- Improve customer service: The Company wanted to have the best customer practice in place so as to keep the current customers happy. By performing sentiment analytics the company was able to see if customers are complaining about something related to the internet or the voice services being offered by the firm and take quick corrective measures.
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