Sentiment Analysis

Sentiment Analysis

How Sentiment Analysis Drives Benefit to Business

Understanding what the key Influencers of your marketplace say or feel has been proven to be of great value to businesses. These key influencers can be customers, suppliers, competitors, third-party industry experts, etc. This information may be highly unstructured and in various formats, most commonly text and audio. Prior to the advent of AI & Natural Language Processing (NLP), this unstructured data could not be accurately and consistently translated into anything close to actionable. With Macrosoft AI’s Sentiment Analysis solutions, we distill actionable and structured data from unstructured content for use by marketing, sales, customer support and other critical business functions.

Various Techniques in Sentiment Analysis

There is no shortage of sentiment analysis solutions in the market today.  Many solutions typically look for adjectives and nouns, and then translate the adjective(s) into a positive-negative score related to that noun.  Unfortunately, such solutions rarely provide the level of specificity needed to be certain of the topic(s) for which sentiment is expressed.

For example, let’s consider a blog for a prescription medication. Such blogs are abundant in social media today and often provide content of great value.  For our example, let’s consider a post by a current user of that medication. A post by this user may address one or more of the key dimensions of the medication, such as it’s cost, or effectiveness, or side-affects, or availability… and often, many or all of these dimensions are mentioned in a single post.

With some Sentiment Analysis solutions on the market, all of the adjectives related to the medication are “scored” as positive (between 0 and 1) or negative (between 0 and -1), and then these scores are averaged together and presented as a single sentiment expressed by the user relative to the medication.  These solutions are unable to provide the sentiment expressed for each dimension separately, preventing a business from reacting to the specific “message” provided by the user (“Should I react to price objections?” “Should we communicate more about potential side-affects?” “Do we have a distribution issue in a specific location?”).

The Macrosoft AI Sentiment Analysis Solution Advantage

At Macrosoft AI, our mastery of NLP allows us to break down unstructured content into the specific topic(s) and associate the sentiment expressed to that topic or topics.   These results can be returned to our customers in a structured data format, allowing for targeted follow-up by the business process(s) impacted by any of the topics that we have defined in the content.   When one considers the sheer volume of “unstructured data” (i.e. written and verbal content) that exists, a growth-oriented business cannot ignore the value that AI – NLP can provide by distilling this unstructured content into structured and actionable data.

AI Recommendation Engine Case Study

Transforming Blogs into Data for Life Sciences

See how this Life Sciences company used the power of Sentiment Analysis to extract relevant data from content based social media.