🎯 Clique Bait Marketing Analysis

SQL-Based Digital Marketing Analytics Project

The Clique Bait project dives into user interaction and digital marketing performance across multiple campaigns. Using advanced SQL techniques including joins, subqueries, and window functions, the project focuses on measuring ad effectiveness, customer engagement, and conversion funnels. The results help the marketing team make data-driven decisions for optimizing campaigns, targeting strategies, and content design.

Clique Bait SQL Project

Project Highlights

  • User Engagement Insights

    Measured website interaction metrics like click-through rate and session duration using SQL aggregation and joins.

  • Campaign Performance

    Analyzed campaign-level conversion performance and bounce rates using CTEs and subqueries for funnel analysis.

  • Customer Journey Tracking

    Tracked user navigation paths and identified drop-off points using SQL ranking and partition logic.

  • A/B Testing Analysis

    Compared ad versions using SQL statistical functions to identify high-performing creatives and placements.

  • Revenue Attribution

    Linked ad clicks to actual purchases using transaction-level joins to determine ROI by marketing channel.

About the Project

Clique Bait Overview

Overview

The Clique Bait project is designed to evaluate the performance of online marketing campaigns and user engagement patterns. Using SQL, the project uncovers how users interact with digital ads and websites, helping marketing teams fine-tune their advertising strategy and increase conversion efficiency across digital platforms.

SQL Process & Data Modeling

  • 📥 Extract: Combined campaign, user click, and conversion data from multiple relational tables.
  • 🧹 Transform: Cleaned and normalized session data using SQL string and date functions.
  • 🔍 Analyze: Built clickstream and funnel reports with CTEs and ranking logic.
  • 📊 Model: Created an analytical schema to relate clicks, sessions, and conversions for deeper insights.
Clique Bait SQL Model
Clique Bait Insights

Key Insights

  • 📈 Identified that 40% of conversions came from mobile ad campaigns.
  • 🧠 Revealed that users from social media sources had higher engagement rates than email campaigns.
  • 💡 Top-performing ad creatives increased click-through rates by 25% compared to previous designs.
  • 🔎 SQL-driven funnel analysis highlighted major drop-offs at the signup stage.

When:
2025

Mode:
SQL Data Analysis

Dataset:
Marketing Campaign & User Interaction Data

Focus:
Engagement, Conversion & Funnel Analytics

Project Snapshots

Business Impact

📊 Enhanced marketing ROI through accurate tracking of user conversion data.

💬 Enabled data-driven ad budget allocation to top-performing digital channels.

🚀 Improved overall click-through rate and reduced bounce rate with SQL-based insights.

Challenges & Learnings

⚙️ Managing large clickstream datasets while maintaining query efficiency.

🧩 Constructing accurate funnel analysis using multi-table joins and time-based logic.

💡 Enhanced expertise in data cleaning, campaign analytics, and SQL optimization techniques.

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