18 International Journal Of Engineering Research And Development e- ISSN: 2278-067X, p-ISSN: 2278-800X, www.ijerd.com Volume 16, Issue 8 (August 2020), PP. 18-22 A Website Analytics System Considering User’s Category Ayush Sharma 1 , Prashant Kumar Mishra 2 , Snehal D Chaudhary 3 1,2,3 Department of Information Technology, Bharati Vidyapeeth (Deemed to be University) College of Engineering, Pune,India. ABSTRACT One of the most important field of e- commerce is, Website analysis and it has been the top main concerns of the website administrator. The most focused or important issue in this field is, the interaction and the exploration of the web content done by the users and where their attention lies in the process of navigation. However, different studies have been made for the analysis of the all kinds of categories of users. It can be said that different categories of person have a different need from a particular website. A particular element may be useful fora particular person but it may be useful for the second one too, as both the persons don’t show up the same interest. Hence the paper proposes a website analysis method which is based on users’ categorie s, categorizes users using two different methods of Data mining, Classification and Clustering. The first approach deals with the Organizational categories and the second approach deals with the users’ behaviour on the website. The two approaches have been implemented on the University of Tehran’s website. With the use of heat map, we have presented the important items in a page for respective category of users which can be used to restructure the pages appropriate to each category KEYWORDS: Web analysis, Heat Maps, Data Mining, Clustering, Data Classification Date of Submission: 15-08-2020 Date of Acceptance: 01-09-2020 I. INTRODUCTION The companies that don‟t get engrossed in e- commerce can also be benefited from an effective website, as customers often find business through internet searching. There are hundreds of reasons a company may perform a website analysis. If we take up an example, the customers might show curiosity how well their website is functioning or what do their competitors do with the web pages. A website analysis can also help to determine the design of the particular site once it has been created. The focal pointof the website analysis to tell how supportive the site becomes for a company‟s goal or target. As website analysis becomes the most important part in e-commerce and has been the main concern and challenge of the web administrator. To achieve the deep understanding the users‟ behaviour, web administrators need to keep analysing their website to know or examine the extent of their goals achieved, also develop the future goals and strategies, and try to improve the user experience. Hencethese tools help the administrator to identify the strength and the weakness of their website and develop the future strategies. Web analysis There are several numbers of tools for analysing the website like Google analytics1 and piwik2. These different tools offer a variety of reports, like website traffic, browser type, visitor‟s geolocation, most viewed pages and the different versions. In the present time, these tools are designed for the purpose like, CrazyEgg3,MouseFlow4and Hotjar5. These different tools analyse the behaviour of the users and presents a report which is based on heat map. It shows the usage of heat maps to display reports of website analysis. The Heat map is an illustrative diagram, where the colour is representative of the amount of the users click on the page or is also representative of the areas of the page which attracts more visitors. In the map, the warm colours are representative of the areas which have been most visited by the users whereas the cold colours are representative of the few visits. To maintain the growth of this graphical tool, one of the most important reason is the ability to make easy transfer of the concepts in different conditions, which synchronizes the data collected over a period of time and reduces the complexity of data and gives a comprehensive portrait of multi- dimensional analysis result. As the development of the mobile devices took place, the web analytic approach