How to Implement Server-Side Web Analytics for Better User Data Privacy and Analysis

Berkay Demirbas Co-founder/developer

raufsamestone

In the era of data privacy concerns and increasing user demands for more control over their data, server-side web analytics has become a popular solution for businesses to track user behavior while protecting their data privacy. In this post, we’ll discuss how our web analytics tool helped a mid-sized business optimize their marketing campaigns using server-side tracking with Python and R.

What is Server-Side Web Analytics?

Server-side web analytics is a technique for collecting and analyzing user data on the server-side of a web application, as opposed to client-side tracking with JavaScript. This approach is becoming more popular due to its advantages in data privacy and security, as well as its ability to handle more complex tracking scenarios.

In server-side tracking, the tracking events are sent from the server-side code instead of the client-side browser. This allows for greater control over the data collected, as well as more accurate tracking of user behavior.

Our Client’s Challenge

Our client, a mid-sized e-commerce business, was struggling to optimize their marketing campaigns due to limited data privacy and accuracy in their client-side tracking with the Facebook Pixel. They wanted a solution that would allow them to track user behavior on their website without relying on cookies or other client-side technologies. Solution: Server-Side Tracking with Python and R

We recommended implementing server-side web analytics using our web analytics tool, which provides cookieless and server-side tracking capabilities. We integrated our tool with the client’s website and used Python and R to send tracking events from the server-side code.

Here’s an example of how we sent a server-side event using Python:

python
 
import requests
 
payload = { 'event_name': 'product_purchase', 'user_id': '1234', 'product_id': '5678', 'quantity': 2, 'price': 29.99 }
 
url = 'https://analytics.example.com/api/events'
 
response = requests.post(url, json=payload)
 
if response.status_code == 200: print('Event sent successfully!') else: print('Event sending failed.')

In this example, we sent an event named product_purchase with the user ID, product ID, quantity, and price as payload.

By using server-side tracking with Python and R, our client was able to collect more accurate and granular data about user behavior on their website, without compromising their data privacy. They were able to optimize their marketing campaigns based on this data, resulting in a 20% increase in sales within the first quarter of implementation. Benefits of Server-Side Web Analytics

By implementing server-side web analytics with our web analytics tool and Python and R, our client was able to gain several benefits, including:

• Improved data privacy and security: Server-side tracking provides better data privacy and security by eliminating the need for client-side cookies or other tracking technologies.

• More accurate data: Server-side tracking allows for more accurate tracking of user behavior, as it is not affected by browser settings or ad-blockers.

• Greater control over data: With server-side tracking, businesses have greater control over the data collected, as well as the ability to customize the tracking for their specific needs.

Server-side web analytics is an effective solution for businesses to collect user data while protecting their data privacy. By using our web analytics tool with Python and R, our client was able to optimize their marketing campaigns based on more accurate and granular user data, resulting in significant sales growth. If you’re looking for a better way to track user behavior on your website, consider implementing server-side web analytics with our tool and server-side scripting languages like Python and R.

Happy marketin engineering!