Online AD Revenue Optimizer

Case Study - BI, Machine Learning, Mobility

  Business Scenario

The Client is a Silicon Valley based start up funded top VC Firms. They
provides SaaS platform for online advertisement publisher to maximize ad revenue using machine learning.

  Proposed Solution

  • Development of a BI platform showing dashboards for various metrics
  • Rich data model to accommodate real time bidding leveraging machine learning

  Key Highlights

  • Dashboards
    • Dashboards and reports showings requests, fill rate, eCMP and revenue for publisher
    • Role based access control for functions and data
  • Advance Analytics and Machine Learning
    • Analytics for revenue optimization
    • Leverages machine learning algorithms for getting programmatic high yield bids considering paranerters like price floors,
      frequency caps, device types, geo-loation and visibility etc
  • Campaign Management
    • Cookie syncing and content based targeting
    • Platform supporting industry standard OpenRTB (Real Time Bidding)
    • Configuration module for Campaign details like AdUnits, Orders, Line items, various tags and supported DSPs
    • Targeting and filtering based on parameters like geo-locations, device types and gender etc
  • Mobile Dashboards
    • Android and iOS native apps


  • Web UI : J2EE, Hibernate
  • Database : RDBMS (Azure SQL Server), MongoDB, Redis
  • BI Tools : Microsoft PowerBI, R script