Data analysis has long been an effective way to sort between things that can be quantified, such as how many customers bought which products. This can reveal much about your audience, but Opinion Mining is now letting us take that to the next level.
There is a greater variety of information available today than ever before. To meet this challenge, Opinion Mining allows us to analyse different forms of content so that we can understand attitudes and trends expressed in text data. We can categorise statements as positive, negative, and neutral and also judge intent.
We can use this information to understand the sentiment and strategic knowledge from financial news, which can in turn be summarised into important insights relevant to your industry. This can help you gain insight into the constant fluctuations of financial markets, and how this relates to news from your industry. Perhaps the biggest benefit of this is that it can be performed on a large amount of news, summarising information for intuitive analysis.
Understanding language has always been a priority for us as we feel customer opinion is at the heart of business. Understanding the sentiment of your customers is the key to letting data inform your customer service.
Advanced algorithms can recognise both the subject and context of written text, and how people feel about your product. It will help you understand what influences the decisions of your customers, and guide them as they browse. Once you know your customers desires and pain points, you can present your product accordingly.
This is an important way to understand your customers as it allows you to know whether they are expressing positive, negative or neutral sentiments about your product or service. These can be collated to give an overview for which features of your products are well received and which require changes to better suit a target audience. This allows us to go beyond statistics and add meaning and sentiment to your business insights.