TV-Ad-optimization

TV Ad spend optimization AI / ML - Advertising

A major retailer in the US was looking for optimizing their marketing budgets by getting accurate analysis of the ROI on television advertising.

CoreView helped with a solution using AI/ML to measure the effectiveness of the TV Ads to increase the ROI


The Challenges

The key challenges were -

  • To quantify the effectiveness of the promotion of a brand by TV AD and identify the ideal TV AD mix
  • Measurement of TV ad effectiveness and optimization of costs
  • No direct measure for effectiveness
  • Parameters and their impact on results is not well defined

Coreview’s Solution

CoreView built a solution with below features.

  • Analysis of TV Ad data across many channels and Sales data for last 12 campaigns
  • Data mapping and attribution – Time slots and duration, Type of Ads, TV Channels, Website traffic, Sales Numbers
  • Python/MongoDB – Data processing and time-series forecasting
  • Models based on State Space, Clustering and Markov Chain
  • Visualization using Tableau.

The Results - Reduced Customer Churn & Increased Revenues

This helped the company to bring a great customer experience with -

  • 8% reduction in Ad spend
  • 10% increase in ROI
  • Model for Cost Optimization
  • Recommendations for future TV Ad campaigns

8% reduction in TV Ad spend and 10% increase in ROI

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