As the frenzy of holiday shopping comes to an end, it should come as no surprise that more and more companies are looking for ways to make sure that they continue to attract customers. In the time of year when many Americans are trying to recover from overspending on gifts and vacations, companies sometimes have to work even harder to make sure that they convince customers to spend with the same enthusiasm as they did before the holidays. The fact that the beginning of the year is the time when many people are reconsidering their budgets and curtailing their their spending, means that many businesses find it difficult to meet sales goals at the beginning of the year.
In an attempt to increase the chance that a potential customer will show interest in a company’s website and make the move toward a purchase, many companies are making sure that they are using all available resources. From text mining to sentiment analysis software, many companies are making sure that they make more thorough use of the digital data that their websites can provide.
Consider these facts and figures about the analytical uses that digital data can provide companies of all sizes:
- Information retrieval, natural language processing, information extraction, and data mining are the four steps in the text mining process.
- Producing an enormous amount of data every second, Facebook has 1.97 billion monthly active users worldwide.
- Although text mining can bridge the gap to the missing 99%, the International Data Corporation (IDC) estimates that less than 1% of this data is ever analyzed.
- Forecasted to reach almost $6 billion by the year 2020, the current value of the text analytic market is currently estimated at $3 billion.
- Companies that want to understand customers? sentiment about their business, its products, or its competitors understand the value of getting the most out of all of the available digital data.
Sentiment analysis software, as well as identity resolution applications, monitor the items that potential customers are the most interested in. This information can be used to make sure that customers who show an interest in a specific product are reminded when that product price decreases.