Web Analytics Project Goal and Challenges Step by Step

Phase 0.1 – Defining Project Goals and Challenges for SankalandTech.com

This is your first step in a wonderful journey into web analytics! Well, before we start collecting data or even begin writing code, we must understand why we do this undertaking. Just think of it like planning for a trip, you wouldn't just jump into the car you'd figure out where you want to go and what you hope to see along the way!

Creating a custom web analytics system is not simply technical for our website, www.sankalandtech.com it really goes beyond that. It is really all about arriving at real answers that can improve our tutorial offerings even further for you, our readers.


Why Are We Building This? The Big Picture for https://www.google.com/search?q=SankalandTech.com

Sankalandtech.com was built with one simple goal in mind — to help people learn. Whether you're getting started with C programming, trying to figure out SQL or diving into Python, we aim to share tutorials that are clear, useful and easy to follow.Our aim is to make tech simpler and more accessible for everyone.

But how do we know if we're really helping? That's why we use web analytics. It shows us how people use the site, so we can make it better and keep it a great place to learn.


planning analytics goals for SankalandTech website to improve tutorials and user experience

What Puzzles and Problems Do We Want to Solve? (Our Challenges)

Even when a website is built with the best intentions, there are always things happening behind the scenes that we can't see right away. At sankalandtech.com, we’ve been thinking a lot about how people actually use the site — and we’ve got some important questions we want answers to. That’s where this analytics project comes in.

1. Are people really learning, or just passing through?
We can tell how many people visit a page, sure but that doesn’t say much about what they’re doing there. Are they reading the full tutorial? Are they spending time on the tougher parts, like detailed code examples? We want to know if the content is sinking in or if folks are just skimming.

2. Which tutorials are hitting the mark and which ones need help?
Is our tutorial on calloc in C doing well? Or are more people checking out the SQL interview prep? We want to spot the tutorials that are truly helping readers so we can create more like them and give extra attention to the ones that aren’t connecting as well.

3. Where are people dropping off?
Sometimes readers start a multipage tutorial and don’t make it to the end. Why? Maybe something’s unclear or too complicated. Finding those drop off points helps us improve navigation or explain things better where needed.

4. Are our job prep sections actually useful?
We put a lot of effort into sections like Python Interview Questions and SQL Interview Questions, hoping they help people prepare for real interviews. But do they? Or are visitors clicking in and quickly leaving? We want to know if they’re truly helpful or if we need to make them better.

5. How are people finding us and does that change how they use the site?
Are most of our visitors coming from Google searches? Social media? Shared links from friends? Knowing this helps us understand how people discover the site and whether different sources bring different kinds of readers.

6. Does the device people use make a difference?
Some people read tutorials on their phones, others on tablets or desktops. We want to know if the experience is working well across all devices — so learning feels smooth no matter how someone chooses to access the site.


The Big Win: How Analytics Will Make https://www.google.com/search?q=SankalandTech.com Even Better

We plan to build this completely new analytical system to bring some really good "wins" for you-all readers who benefit out of it as much as for sankalandtech.com:

• Threaded Content Creation: We'll know exactly what topics to focus on, the kind of depth readers prefer, and the best formats (for example, more code examples, more practical exercises).

• Improved User Experience: Repetitive identification and amendation through the website brings a smother experience for the navigation. Areas with a very high "bounce rate" will be investigated and improved accordingly.

• Tailored learning pathways: How users navigate through tutorials can trigger a better recommendation of matched-content sites that would guide you to the next learning step.

• Concrete Measurement of Engagement: Beyond mere visits, involvement of readers will be gauged from this measure, ensuring that tutorials are impractically impacting.

• Strategic Growth: By knowing where our audience comes from and what they love, we can make better decisions about how to reach even more aspiring tech learners.

The first stage comprises setting our compass. Now with the clear definition of goals and challenges, we can move on to selecting suitable tools and planning to collect all these valuable data!


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Website Analytics Project: Phases and Action Steps

  • Home
  • 🟢 Live App: Web Analytics Simulator
  • Phase 0: Project Setup & Problem Definition
  • 0.1 Define Project Goals & Challenges
  • 0.2 Select Tools, Tech Stack & Data Sources
  • 0.3 Software Requirements & Installation
  • 0.4 Folder Structure & GitHub Repo
  • 0.5 Testing Project Locally
  • Phase 1: Planning for Analytics
  • 1.1 Website Analytics Project Overview
  • 1.2 Define KPIs, Bounce Rate, Engagement
  • 1.3 Identify Target Users & Pain Points
  • Phase 2: Data Collection
  • 2.1 Setup Google Analytics 4 (GA4)
  • 2.2 Export GA4 Data to BigQuery/CSV
  • 2.3 Design SQL Schema for Web Analytics
  • Phase 3: Data Cleaning & Feature Engineering
  • 3.1 Clean Website Data with Python & Pandas
  • 3.2 Create Custom Metrics (Session, Bounce, etc.)
  • Phase 4: Exploratory Data Analysis (EDA)
  • 4.1 Analyze Website Traffic Trends
  • 4.2 Behavior by Device, Source, Location
  • 4.3 Top Pages & High Bounce Pages
  • 4.4 Diagnose Low Traffic & User Drop
  • Phase 5: Business Insights
  • 5.1 Funnel Analysis & Drop-Off Points
  • 5.2 New vs Returning Users
  • 5.3 Time Spent & Scroll Depth
  • Phase 6: SQL for Business
  • 6.1 SQL for Business Insights
  • 6.2 Combine Web Data Using SQL
  • 6.3 Find Problematic Pages Using SQL
  • Phase 7: Machine Learning
  • 7.1 Segment Users with Clustering
  • 7.2 Predict Bounce Rate with ML
  • 7.3 Recommend Pages or Content
  • Phase 8: Dashboards & Visualization
  • 8.1 Dashboard with Streamlit
  • 8.2 Visualize KPIs with Python
  • 8.3 Page-Level Metrics & Drop Heatmaps
  • Phase 9: Final Analytics Story
  • 9.1 Summary Report & Findings
  • Phase 10: Hosting & Portfolio Presentation
  • 10.1 Host Website Project Online
  • 10.2 Add to GitHub with ReadMe
  • 10.3 Pitch Project in Interview
  • Other Topics
  • SQL Interview Questions
  • SQL Case Study: Account Management
  • Python Interview Questions
  • Why C Language

Get in touch

  • tech2dsm@gmail.com

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