Market Modeling
            Companies invest in model building presumably because it leads to better decisions.

            “Better” is understood here as contributing to the fulfillment of the company’s goals.
Market modeling is statistical analysis on sales and marketing data to estimate the impact of various marketing tactics on sales and then forecast the impact of future sets of tactics.
Model often allows management to pinpoint changes in the environment faster than is possible otherwise.
Models help managers decide what information should be collected. Thus models lead to improved data collection, and their use may avoid the collection and storage of large amounts of data without apparent purpose.
Our market models helps businesses define and visualize scenario planning effectively:

1) Business Modeling
2) Marketing Modeling for New Products
3) Marketing mix modeling (MMM)
4) Decision modeling
5) Cost modeling
6) Commodity modeling

Helps businesses in:
Our market modeling techniques

1) Marketing mix modeling (MMM)
2) Boston Consulting Group Matrix
3) Customer Lifetime Value models
4) Ansoff’s model (Growth strategy matrix)

5) PEST model
6) PESTLE model
7) Diffusion innovation models
8) Segmentation, Targeting and Positioning (STP)
9) 7P's of the Marketing mix model
10) Causal analysis and modelling
11) Discrete Choice Modeling
12) Applied Regression Modeling
13) Dynamic modeling
14) Interactive Modeling and Simulation
Dynamic and Stochastic Modeling proficiency
Better ROI
in-season vs. out of season performance analysis
Accurate Marketing Mix Models
Market Modeling:


                   Market modeling is mathematical representation of the interactions among various participants, economic forces, and choices made. There are hundreds or even thousands of market models that attempt to explain or predict the behavior of one or more aspects of a market. The objective is to maximize the returns of a portfolio or product mix or a single product. We have proficiency in building market models that are Stable, Dynamic and Stochastic with adequate robustness and flexibility to adapt and deliver in the flux of market uncertainty.


                  At the heart of our approach is the ability to develop abstract models of real-life business problems that are instinctive to use, yet sufficiently realistic to support robust decision-making. These models are used to provide insight, and quantify the risks and benefits associated with solutions to complex business problems.


                 Our aim is to help you fully understand a market's future spending patterns and provide quantified insight to support your business decision making.



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Decision Science Services
AI > Decision Science