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In today's internet environment, Content Management Systems (CMS) are widely used for managing and publishing website content. To gain deeper insights into user browsing behaviors, site operators often need to analyze user visit paths. This article provides a detailed explanation of how to use Python to build user visit path analysis functionality in a CMS system, accompanied by code examples to help you implement it.
User visit path analysis aims to track the sequence of pages users browse on a website, their dwell time, and conversion rates. These insights enable website administrators to understand user needs, optimize site design and content layout, and thereby enhance user experience and overall traffic.
To realize user visit path analysis, the first step is collecting user visit data. A common method is embedding a small JavaScript snippet on each page to send visit information to the server in real time. In this article, we use Python’s Flask framework to build the data receiving and processing backend.
Install Flask using pip:
pip install flask
Create a file named app.py, import necessary modules, and initialize the Flask app:
from flask import Flask, request
<p>app = Flask(<strong>name</strong>)</p>
<p>@app.route('/api/analyze', methods=['POST'])<br>
def analyze():<br>
data = request.get_json()<br>
# Further processing and analysis of collected data can be done here<br>
# Return analysis results to the frontend<br>
return {'success': True}</p>
<p>if <strong>name</strong> == '<strong>main</strong>':<br>
app.run()
This code defines an endpoint /api/analyze that receives user visit data sent from the frontend in JSON format. The backend processes the data and returns a response.
Insert the following JavaScript code into your web pages to send user visit data:
<script>
document.addEventListener('DOMContentLoaded', function () {
fetch('/api/analyze', {
method: 'POST',
headers: {
'Content-Type': 'application/json'
},
body: JSON.stringify({
// Add data such as page URL, dwell time, etc. here
})
});
});
</script>
This script triggers after the page loads and automatically sends the current user’s visit info to the server. You can extend the data sent according to your needs.
The above example shows a basic data collection and transmission process. In practice, you can combine it with databases to store visit records, apply data analysis algorithms to mine user behavior patterns, and use visualization tools to display visit paths, supporting website optimization.
With this guide, you now understand the basic method of implementing user visit path analysis in a CMS system using Python and the Flask framework. Scientific data collection and analysis help to deeply understand user needs and enhance the website’s functionality and experience.
