Customer Complaints: Identify New Product Ideals

People love the Fitbit because they can quickly get performance feedback along with a coach from a single device. When they are not so happy with the invention, they turn to Twitter and talk to the brand's customer support team. As the company assesses the tweets over time patterns emerge as well as the customer's attitude or sentiment. No one expects a happy customer when they are having issues, but it can be positive if the support is quick and useful.

In this social media customer study, the analyst pulled tweets consumers sent to @FITBITSUPPORT. In one six-month period, there were over 33,000 posts. Fitbit is popular! That is too much data for one person to digest and even attempt to identify all of the trends.

However, with text analytic applications, the analyst was able to break out the tweets by model and then zero-in on specific issues. For the Fitbit Charge HR, the strap was an issue. It would break, bubbles would develop in the band, and the rubber stamp would peel off. The Fitbit Blaze had problems with the operating system where it could not get past the logo screen.

Within a few short mouse clicks, the user comments are available.

Information Extract from Twitter

The product team knows which features are annoying the customer and where to focus their energy.

Understanding the customer experience is essential and these online reviews provide a reliable way to understand it.

It's basically the words right out of their fingertips. If you are an after-market company, then you might see an opportunity to supply bands.

Questions

1.The data collection is actually done by a Web crawler continuously checking the tweets on the Web based twitter site. Which type of Web mining is it called? What benefits can this Web mining bring to this specific scenario?

2.Once the text comments are fetched from the twitter site, text mining techniques are applied to structure the comments and extract knowledge. In this step, a term-by-document (tweet) matrix will be created. According to the tweets shown in the table, please design such a matrix and fill in the values (You can design the matrix in a separate file and attach it) . Explain why you design it like that (e.g., in terms of the words included, best representation)?