ClickStream Analytics is an information retrieval use case for Mahout. Most of the e-commerce applications, social networking sites and several websites carry out lots of analysis using the ClickStream data. ClickStream data could be generated from any activity performed by the user over a web application. What could be the user activity over any website? For example, I am logging into Amazon, what are the activities I could perform? In a pattern, I may navigate through some pages; spend some time over certain pages and click on certain things. All these activities, including reaching that particular page or application, clicking, navigating from one page to another and spending time make a set of data. All these will be locked by a web application. This data is known as ClickStream Data. It has a high business value, specific to e-commerce applications and for those who want to understand their users’ behavior.
More formally, ClickStream can be defined as data about the links that a user clicked, including the point of time when each one of them were clicked. E-commerce businesses mine and analyse ClickStream data on their own websites. Most of the E-commerce applications have their built-in system, which mines all this information.
Using the ClickStream data adds a lot of value to businesses, through which they can bring many customers or visitors. It helps them understand whether the application is right, and the application experience of users is good or bad, based on the navigation patterns that people take. They can also predict which page you are most likely to visit next and can do Ad Targeting as well. With this, they can understand the needs of users and come up with better recommendations. Several other things are possible using the ClickStream Data.
The kind of data that is captured for ClickStream Analysis may include:
- Where was the visitor before reaching my website?
- What was the search term used if the visitor came from a search engine?
- Which webpage did the visitor first access on my website?
- What are the pages the visitor accessed on my website and in what sequence?
- How much time did the visitor spend on each page?
- When and where did the visitor click the “back” button on the web browser?
- What items did the visitor add to (or remove from) their shopping cart?
- From which page did the visitor exit my website?
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