There is a common belief that- “Expression says it all”. And we all know the importance
of this statement in our daily life. But surprisingly, the statement has also influenced
the fast-paced modern business fraternity and helped them successfully derive an intelligent
method- known as sentiment analysis that can analyze and disclose effective insights from customer interactions.
Why is it important to analyze customer sentiments?
“Public sentiment is everything. With public sentiment, nothing can fail. Without it, nothing can succeed.”
~ Abraham Lincoln
How does sentiment analysis add values to the enterprises?
Let us consider a call center scenario where the agents get to deal with numerous customers. Each customer expresses their own views/feedbacks/issues etc. while being in a conversation. This voice data can be run through voice to text engine and the output received can be utilized for deriving sentiment analysis. These results can further help in understanding the scope of improvement in the process or in assessing the service levels rendered by the call center.
Apart from voice data as mentioned in the above call center scenario, the other input sources can be either in the form of video signal; television; IVRS; text data; social media streams; search queries and many others. Capturing real time emotions are more in practice these days as it helps in understanding emotions immediately with probably a miniscule negligible delay. Real time sentiment analysis can open scope of improvement for the enterprises without any time slog.
How does Datametica help?
Datametica can help you with its strategic and exclusive way of capturing sentiment analysis with their unique frameworks and accelerators, which can further facilitate in predictive analytics, rumor analytics, revenue optimization, sentiment polarity about products/services and competitive analytics for enterprises so that they can make their business more customer centric. Our Automatic Speech – To – Text Recognition and Conversion Framework ingests Audio/Video Signals and processes the audio files to text using Machine Learning Algorithms and Statistical Model via an ASR model. To draw the intent/sentiment our proprietary approach is a combination of machine learning, deep learning (deep learning libraries and framework), lexicon and many others. With advanced techniques like silence detection, video to audio conversion, audio to text conversion, we use natural language processing to obtain specific words which can help in determining the sentiments. Additionally, the model is trained for improved accuracy up to 85%-90%.
· Improve customer service: Based on the sentiment analysis reports, emotion or polarity results, enterprises can improve and innovate their customer services.
· Make customer segmentation: Identifying the top customers and capturing their sentiments for categorizing them into very high, high, medium, average purchaser, which can be considered for future references. This can help in segregating customers and work upon better retention plans for top customers.
· Predict product performance: Based on identified polarity and text analysis, the top performing products can be categorized. This will help in identifying the products is being used and to be used in future.
· Improve campaign effectiveness: Monitoring the success of marketing campaigns in real-time is easy with the sentiment analysis data. Based on the majority inclination of the customers towards a product or service a campaigns effectiveness can be improvised.
· Determine market strategy: The sentiment analysis data can help in determining number of customers added or removed after a campaign, website traffic after a campaign being run, understanding product feedback, and detect shifts in customer attitude. This can help in planning effective marketing strategy.
Do you have a customer-centric business model? We at Datametica can help you in analyzing the expressions and emotions of your customers. Are you ready to know what your prime stakeholders think about your business?