Entity analytics are an extremely useful tool for marketing purposes. According to Boris Evelson, businesses typically utilize 27% of their semistructured data and 31% of their unstructured data accumulated through entity analytics to assist in their decision making as well as their business insights.
The use of entity analytics in marketing has become more functional in recent years what with an estimated number of 2.67 billion social media users predicted to be online in 2018, a .33 billion increase since 2016. With more users online, businesses are able to optimize entity extraction and analytics, specifically entity-based sentiment analysis, in order to gain useful insights for marketing purposes.
Like a kind of text mining software, sentiment analysis (also known as aspect based sentiment analysis) takes a provided text and converts it into unstructured text data. From this unstructured data, sentiment analysis then predicts whether or not the given sentences have a positive or negative polarity.
However, sentiment analysis in general tends to work particularly well when the given sentences only have a single entity and a single polarity. To predict multiple entities as well as the opinions attached to each entity would be a more complicated task.
Sentiment analysis can be useful on social media platforms by analyzing the information provided by entity extraction and analytics for further detail. For instance, entity analytics can inform a business of the related entities across a larger collection of data and how they relate to each other, to people, and to transactions. Sentiment analysis additionally analyzes the opinions of the people and the relationships extracted.
It’s one thing to know that a particular consumer has used your brand, but another to identify that consumer’s opinion of your brand. Sentiment analysis eliminates the need for businesses to ask their customers to report back to them using surveys or questionnaires regarding their experiences with their product or services.
The data provided by these surveys can often be skewed considering many customers do not fill them out or answer questions truthfully due to pressure for time. Sentiment analysis determines opinions based on consumers’ own words on social media where they are more likely to be honest without fear of reprimand.
Therefore, sentiment analysis software is a beneficial addition to a business’ entity analytics and name matching software. To gain knowledge regarding your audience’s opinion on your products, brand, and business services consider utilizing aspect sentiment analysis in your next online data collection and analysis.