Monday, April 27, 2020

analysis of web logs to understand how users use the website

Understanding how users use the website is important for improving the ease of use.

Suppose I have 3 website users (1, 2, 3), three webpages ("A", "B", and "C"), and each user visits three pages.

In this post I outline different data structures available for capturing user activity.

A matrix of pages and page visit order

page A page B page C
first page 1, 2 3
second page 3, 1 2
third page 1, 3 2

Here time moves from the top row towards the bottom row.
The steps taken by a single user are easy to trace.

A Markov model

A B C
A 0
B 0
C 0

A list per user

user 1: [A, B, A]
user 2: [A, C, B]
user 3: [C, B, A]

Same information as present in the matrix. 
Here time moves left-to-right
The list length can vary per user.

List of tuples per user

As a modification to the list, each element could include the page name, the render time, and the dwell time:

user 1: [(A, 0.2, 55), (B, 0.3, 20), (A, 0.4, 126)]
user 2: [(A, 0.1, 65), (C, 0.2, 234), (B, 0.4, 23)]
user 3: [(C, 0.3, 15), (B, 0.1, 53), (A, 0.3, 45)]


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