Nikhil.
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AVAILABLE FOR WORK • AI & MACHINE LEARNING • FULL STACK DEVELOPMENT • OPEN SOURCE • DEEP LEARNING • COMPUTER VISION • NLP • AVAILABLE FOR WORK • AI & MACHINE LEARNING • FULL STACK DEVELOPMENT • OPEN SOURCE • DEEP LEARNING • COMPUTER VISION • NLP • AVAILABLE FOR WORK • AI & MACHINE LEARNING • FULL STACK DEVELOPMENT • OPEN SOURCE • DEEP LEARNING • COMPUTER VISION • NLP •
AVAILABLE FOR WORK • AI & MACHINE LEARNING • FULL STACK DEVELOPMENT • OPEN SOURCE • DEEP LEARNING • COMPUTER VISION • NLP • AVAILABLE FOR WORK • AI & MACHINE LEARNING • FULL STACK DEVELOPMENT • OPEN SOURCE • DEEP LEARNING • COMPUTER VISION • NLP • AVAILABLE FOR WORK • AI & MACHINE LEARNING • FULL STACK DEVELOPMENT • OPEN SOURCE • DEEP LEARNING • COMPUTER VISION • NLP •
Nikhil Shah.

Architecting resilient digital infrastructure and minimalist product experiences.

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Social Media Campaign Performance Tracker
Case Study // Active Record

Social Media Campaign Performance Tracker.

Strategy & Vision

"Optimizing campaign performance through data Analyzed engagement, ROI, and audience behavior to improve marketing decisions."

Technical Stack

Power BIExcel

External Assets

Technical Source

Overview

This project is a data-driven dashboard built using Power BI to analyze the performance of social media advertising campaigns.

The system focuses on tracking engagement, audience behavior, and return on investment (ROI) to support campaign optimization.

Problem

Social media campaigns generate large amounts of data, but without structured analysis it becomes difficult to:

  • evaluate campaign effectiveness
  • understand audience behavior
  • optimize ad spend

Approach

The dashboard was built using Power BI, with data preparation handled in Excel.

The system was designed to provide:

  • high-level KPI summaries
  • detailed audience segmentation
  • performance trends over time

Interactive filters and slicers allow users to explore campaign performance across different dimensions such as age, gender, and interest groups.

Key Features

  • KPI tracking (clicks, spend, CTR, ROI)
  • Campaign engagement analysis
  • Audience segmentation (age and gender)
  • Time-based performance trends
  • Spend vs. impressions efficiency analysis
  • Interactive filtering for deeper insights

Key Insights

  • Campaign performance varies significantly across audience segments
  • Certain age groups show higher engagement rates, indicating better targeting opportunities
  • ROI is influenced not just by spend, but by audience alignment and campaign structure
  • Engagement patterns reveal which campaigns resonate most effectively

Outcome

This project demonstrates how marketing data can be transformed into actionable insights to improve campaign performance.

It highlights the role of data visualization in optimizing decision-making, particularly in marketing and growth-focused environments.

Process Gallery

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