Introduction of Sentiment Analysis: What It Is, How & Why It’s Used | AI | Machine Learning

What is sentiment analysis?

Sentiment analysis is the process of understanding the emotions of the customer since the customer has been able to state their thoughts and feelings concerning any product or service on social platforms or feedback form any other media. Sentiment analysis is a machine learning technique area of artificial intelligence works as detecting polarity taking data from text, comments, paragraph etc. For example, sentiment analysis can analyze through more than 10,000 reviews from customer to study in a short period that consumers are happy with your product/service or not.

How sentiment analysis works 

This technique works as extracting insights from customers feedback & evaluations. "Shifts in sentiment on social media had been proven to correlate with shifts within the inventory market".

Basic sentiment analysis of text documents follows a straightforward process:

1. Break each text document down into its parts (sentences, phrases, tokens and parts of speech)
2. Identify each sentiment-bearing phrase and component
3. Assign a sentiment score to each phrase and component (-1 to +1)
4. Optional: Combine scores for multi-layered sentiment analysis

 What is predictive analytics in data science?

Types of sentiment analysis :- 

As sentiment analysis process identifies opinions and judgements from apiece of text, it focuses on the polarity of a sentence like positivity, negativity & neutrals even intentions of the customers.

Emotion detection :-

This kind of sentiment evaluation ambitions at detecting feelings, like happiness, frustration, anger, unhappiness and so forth. This makes it less complicated to categorize the terms in step with their sentiment. This way the corporation can apprehend customers unique emotions.

Fine-grained sentiment Analysis :-

This process gives a precise meaning of the polarity input and makes it easier to understand a customer's feedback.

The fine-grained sentiment analysis process considers polarity categories as (example Rated as the star from 1-5)

• Very positive
• positive
• Neutral
• Negative 
• Very Negative

Aspect Based Sentiment analysis :-

This process of sentiment analysis filters out the emotions of customers towards specific attributes of a product, example a product review cases like the battery life of a phone, display quality, speaker quality, camera quality etc. It is necessary to know which particular aspects or features people are mentioning in a positive, neutral, or negative way.

Intent Analysis :-

This is a deep analysis of a customer which involves Natural Language Processing (NLP) understanding the intention of the customer. This can be tracked through the customers shopping pattern, behavior overview. In this process Machine learning is used to decode the feedback provided by each customer to get the precise results.

 

 

Sentiment Analysis | Monitor social media | Analyze views on a Product or Service|Targeted Marketing

 

 

Sentiment Analysis Applications & Use Cases

Sentiment analysis is an high-quality manner to apprehend what the overall opinion of the public is, unique to a corporation or a product. However, it has its personal set of demanding situations and barriers, which can be triumph over if it's miles used effectively. That is a top-level view of all time & destiny viable use cases of sentiment evaluation.

Track customer sentiment over time -

Tracking customer sentiment can be determined as customer's affection towards your brand, product or service to gain new customers or retain existing one is through good communication, by tracking the customer's satisfaction score, comments and feedback, social engagement. 

Customers segments and opinions determination -

Customer segmentation is the practice of dividing a customer base into groups of individuals that are similar in specific ways relevant to marketing, such as age, gender, interests and spending habits, which will help the business to focus respective individuals with respective products of interest to increase the sales according to customer segment. 

Market research and insights into industry trends -

Customer insight research is the process of taking data gathered through market research and analyzing it to predict customer's respond towards business trends, product release. 

Determine Most effective communication strategy with the customer -

Setting a communication strategy helps the customer care services to improve its services by analyzing the customer and service agent's conversations and improvising their service delivery by taking necessary steps.

Product Analysis improvement planning -

Product analysis is conducted by product managers attempting to understand competitors and by third-party reviewers. Product analysis can also be used as part of product design to convert a high-level product requirement into project deliverables. It helps the product managers to analyze its performance in the market.

Customer issue prioritization -

Customer issue prioritization helps a business to set focus on the most important and essentials tasks to be attended in order. Customer prioritization ultimately helps to higher average customer profitability and a higher return on sales. Furthermore, the ability to evaluate customer profitability, the excellent of consumer data, selective organizational alignment, and selective elaboration of making plans to solve a customer problem.

Brand monitoring –

Brand Monitoring is an vital business analytics tactics which deal with strategically monitoring different channels on media to discover and subsequently react to the distinctive sentiments approximately your organization, merchandise, logo and anything explicitly connected to the business. It lets you higher recognize the entity's fee in the marketplace.

Competitive Research -

Competitive research is the collection and review of information about competitors. It helps a firm to understand its strength and weaknesses. A firm needs to compete in the market by analyzing the best strategy with an interest level of prediction.

Data collection and preparation -

it's the system of collecting and measuring statistics on the client base of hobby, in a long-time systematic fashion that enables said research, test speculation and evaluates outcomes to reform approach for what’s subsequent.

Employee Engagement Monitoring -

Employee Monitoring is the act of employers surveying employee activity through different surveillance methods. Organizations engage in employee monitoring for different reasons such as to track performance, to avoid legal liability, to protect trade secret etc.