Clickstream analytics is associated with which characteristics of big data?

Clickstream analytics is associated with which characteristics of big data

Tracking and analyzing traffic to the website is known as clickstream assessment. Clickstream analysis commonly uses the Web service log files to analyze and quantify website activities, while there are different ways to get this data. 

This study may be used to track user activity on a particular website, including navigation, stickiness, origin and exit points, and user origin and exit points. 

In order to determine how the website functions from a technological, customer experiences, and business standpoint, it may also be used for more general statistics like the number of visits, page views, and distinctive and repeated users.

Obtaining and analyzing user clickstream data is known as “clickstream statistics.” The majority of businesses in the e-commerce sector employ clickstream analytics. 

The term “clickstream information” refers to information on user behavior on a website, such as how long a user spends on each page, how many times they click, and how they move between sites. 

Clickstream analytics is associated with which characteristics of big data aid in the comprehension of user activity. Clickstream analysis aids in identifying user preferences and suggests related items. 

Clickstream analytics falls under the category of volume features among the three vs. of big data since it involves storing and processing a lot of data.

Statistics for clickstream data

The succeeding online marketing data are included in clickstream data: whether such a user is a new or returning visitor to the website the recommendation terms they enter into search engines the page they land on first the time. 

They spend on that page the characteristics they click on and interact with where and when an item is decided to add to or eliminated from a shopping cart in which the customer ends up going next and when they use this same back button.

It’s possible that the clickstream data from either a user’s single sitting on a website won’t be helpful. 

However Big data consulting company might enhance its website or service by using aggregate data obtained from numerous visits.

If many people abandon a website after arriving at a page with a lack of information, the company may need to improve the page by adding more useful content. The business may wish to revamp that webpage to be more welcoming and user-friendly if visitors frequently land on one that isn’t the webpage homepage.

Clickstream data is normally kept on the server that maintains the website and does not contain personal information about a user. Keyword Research data can be usefully supplemented with clickstream data.

Analysis of clickstream data and its application

Businesses utilize clickstream analytics to identify patterns and make judgments about their websites’ various data. To keep track of user activities on a website, this technique commonly employs a web application log file.

An organization may get statistics on the number of page visits, views, and original and returning customers while using the clickstream technique. This information gives a sense of how the company’s website functions and may be used to approximate the usual online experience (UX). 

The webmasters may then make changes to the site to enhance its accessibility and raise the likelihood that visitors will remain on it longer, make a purchase, or engage with it in additional ways.


Volume is the amount of data that is actually gathered. For a certain objective, an analyst must decide what data and how much of it should be collected. 

Consider a social networking platform where users may make updates, like photographs, comment on merchants’ services, watch movies, look for new products, and generally engage with everything they see on their screens. 

Each of these encounters produces information about the person that may be used to feed algorithms.


How trustworthy data is related to veracity? An analyst wants to make sure the information they examine is accurate and from a reliable source. Where the data came from and how it was gathered will affect this. 

For accurate findings, data gathered from native sites rather than outside parties is required. Furthermore, testing procedures must be well thought out to guarantee that the data yields the needed information and is not excessive.

Millions of internet users consent to share their data with firms who gather clickstream data and provide insights in the trade, these users are referred to as “panelists.” 

Data businesses use “panelist hashing IDs” to recognize panelists and completely anonymize their data while enabling cross-device data collecting. Even while a separate user’s clickstream data might not be meaningful, when you combine data from many millions of users, you can start to see trends and make judgments about various metrics.


Provide immediate insights since clickstream data is acquired as consumers explore the web in real-time. This eliminates the waiting period involved in traditional research for tasks like hiring, administering tests and expert analysis.

More flexible although preparing clickstream data and creating algorithms to evaluate it is extremely difficult, once datasets are created they may be utilized to extract endless insights, reducing the amount of labor required for gathering and evaluating data using more conventional research approaches.

Provides a comprehensive picture unlike traditional research approaches, which frequently only target particular groups, regions, and timeframes, clickstream data presents a diverse range of individuals and their behaviors as they naturally explore the web

Read More: Which Characteristics of Big Data Deals With Trustworthiness of Data?



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