Sentiment analysis: getting to know your customers through their opinions
Posted: Wed Dec 11, 2024 9:09 am
Traditional marketing has always been based on the 4Ps: Product, Price, Promotion and Location. However, a few years ago a new P was added, which corresponds to the People variable . This variable focuses on the relationship between brands and customers, even beyond the completion of the purchase. Sentiment analysis is a method related to artificial intelligence, with which we can learn more about our customers, in a direct and truthful way.
What is sentiment analysis to understand your customers?
Sentiment analysis is an analysis method based on computational linguistics that allows us to identify valuable information and extract it from the digital impacts of overseas chinese consumers in uk world (social networks, websites, forums, etc.) to the real world. This method is so powerful that it allows us to extract information from network users, customer opinions or dialogues between them and understand what they are talking about, including the positive or negative connotations of these conversations.
It is also known as data mining. This set of techniques massively and automatically classifies information documents about the language used by users on the Internet. Its objective is to obtain information about users' opinions regarding a brand, product or service in order to measure its impact on the image of companies.
Data mining allows you to answer what users think, but it also allows you to take advantage of all this as a competitive advantage.
Different techniques come into play in sentiment analysis. Among them we find machine learning, through which, through artificial intelligence systems, an algorithm monitors intention data to predict future behavior.
Sentiment analysis from a marketing perspective
At Mediapost we work with sentiment analysis from a marketing perspective. Through this tool, we help companies make business decisions. Customers write numerous reviews about their experience. They do this on social media and various digital platforms designed for this purpose.
Based on these comments, and thanks to different natural language processing and text mining techniques, different reports are produced that allow the brand to:
Know which words and groups of words are most frequently commented on by customers.
To what extent these words have favorable or unfavorable connotations towards the brand and its products or services.
To what extent these words translate into emotions (love, joy, surprise, disappointment, anger...)
How to develop a marketing strategy based on the results of the analysis.
What is sentiment analysis to understand your customers?
Sentiment analysis is an analysis method based on computational linguistics that allows us to identify valuable information and extract it from the digital impacts of overseas chinese consumers in uk world (social networks, websites, forums, etc.) to the real world. This method is so powerful that it allows us to extract information from network users, customer opinions or dialogues between them and understand what they are talking about, including the positive or negative connotations of these conversations.
It is also known as data mining. This set of techniques massively and automatically classifies information documents about the language used by users on the Internet. Its objective is to obtain information about users' opinions regarding a brand, product or service in order to measure its impact on the image of companies.
Data mining allows you to answer what users think, but it also allows you to take advantage of all this as a competitive advantage.
Different techniques come into play in sentiment analysis. Among them we find machine learning, through which, through artificial intelligence systems, an algorithm monitors intention data to predict future behavior.
Sentiment analysis from a marketing perspective
At Mediapost we work with sentiment analysis from a marketing perspective. Through this tool, we help companies make business decisions. Customers write numerous reviews about their experience. They do this on social media and various digital platforms designed for this purpose.
Based on these comments, and thanks to different natural language processing and text mining techniques, different reports are produced that allow the brand to:
Know which words and groups of words are most frequently commented on by customers.
To what extent these words have favorable or unfavorable connotations towards the brand and its products or services.
To what extent these words translate into emotions (love, joy, surprise, disappointment, anger...)
How to develop a marketing strategy based on the results of the analysis.