Do you wish for effective marketing strategies?

Optimize media spend up to 25% using media mix simulator

What We Do

Generate aggregate-level time series data
  • Channel-level marketing spend
  • Website visits
  • Competitor spend
  • Pricing
  • Sales volume
Model wide variety of marketing situations
  • Different mixes of advertising spend
  • Levels of ad effectiveness
  • Types of ad targeting
  • Sales seasonality
  • Competitor activity and much more volume
Improve measurement methods
  • Create ground truth for marketing performance metrics
  • Have better Media Mix Models (MMMs), campaign optimization, and geo experiments

How It Works

Consumer

  • Category
  • Activity state
  • Satiation state
  • Market state
  • Brand
  • Loyalty
  • Favorability
  • Availability

Media

  • YouTube
  • Radio
  • Billboard
  • Paid search
  • Television
  • Newspaper

Other data

  • Sales
  • Seasonality
  • Competition

What You Get

Create Synthetic Data

A realistic ad system for the complex interplay between consumers, marketing tools, and environmental phenomena

Model

Response data (business KPIs) connected to media and marketing metrics along with control factors i.e. seasonality, weather and market competition

Analyze

Quantification of the effectiveness and sales impact of all activities

Optimize

Simulations and optimizations to adjust marketing spends for improved results

Application of Media Simulator for MMM

Old Age MMM
  • MMM data collection can take anywhere between 1-2 months

  • Often very expensive of impractical to run

  • Team aggregate historical data based on availability, leading to loss of information

  • Very high both in terms of time and resources
VS
  • Time


  • Validation


  • Data


  • Cost

New Age Simulator based MMM
  • Captures complex consumer purchase behaviour and response to marketing techniques

  • Can replicate data features such as different levels of aggregation and hidden confounders

  • Data can be generated with varying degrees of ad system complexity to better understand the capabilities and limitations of analytical models

  • Possible to run virtual experiments, to provide ground truth for the evaluation of any measurement approach grounded in the analysis of aggregate data

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