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Dynamic Benchmark Analytics Dashboard for Ad Campaign Optimization Platform

itransition.com

Media

Advertising & marketing

Challenges in Ad Campaign Performance Monitoring

The client struggles with static benchmark tables that create unrealistic client expectations, leading to only 62% benchmark achievement. Difficulty tracking multi-channel campaign performance across evolving content types and audience engagement methods. Sales teams lack accurate forecasting tools to predict results and manage budgets effectively.

About the Client

Leading digital media company with 1.5M+ subscribers and 50M+ social media followers, operating across mobile apps, podcasts, social media, and branded content platforms

Key Project Goals

Develop dynamic benchmark dashboards for real-time campaign monitoring
Implement multi-factor forecasting algorithms for accurate performance predictions
Enable cross-channel campaign analysis with historical data comparison
Improve benchmark achievement rate by 8x
Reduce campaign overspending by 7x through proactive monitoring

Core System Capabilities

Multi-factor benchmark calculation engine (Impressions, CTR, Channel, Region, Product, Duration)
Interactive campaign model visualizations (linear/logarithmic/parabolic progressions)
Real-time campaign monitoring with customizable filters
Recommended activity modeling for optimization strategies
Plan-fact analysis with area charts and forecast graphs

Technology Stack

Tableau

Python

Data Writer extension

Custom database

System Integrations

CRM systems
Advertising platforms
Internal data warehouses

Performance Requirements

Real-time data processing
Scalable architecture for new content channels
Role-based access control
High-availability dashboard interface

Expected Business Outcomes

Implementation of dynamic benchmarking system will enable 8x improvement in benchmark achievement rates and 7x reduction in campaign overspending. Real-time monitoring capabilities will enhance client satisfaction through accurate forecasting and data-driven optimization recommendations.