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