Using advanced data analysis methods to develop Marketing Mix Models (MMM) and Agent-Based Modeling (ABM) for strategic decision making
At CIMA, we use cutting-edge data analysis methods to help you move from guesswork to facts and make strategic decisions based on real data. In today's marketing world, knowing what is happening is not enough—you need to understand why and be able to accurately predict future outcomes.
Our data analysis and modeling service allows you to:
We use a combination of Marketing Mix Models (MMM) and Agent-Based Modeling (ABM) to give you a complete picture of your market at both macro and micro levels, helping you make more informed and effective decisions.
The combination of statistical analysis and behavioral modeling delivers results unavailable in traditional analytics
MMM is a statistical analysis using Bayesian causal inference to measure the incremental impact of various marketing tactics on sales and other business metrics.
What this provides:
ABM is a modeling method that simulates the actions and interactions of autonomous "agents" (potential customers) to assess their impact on the entire system from the bottom up.
What this provides:
Why the combination of MMM and ABM gives a more complete picture of your marketing effectiveness
MMM provides overall channel effectiveness, while ABM models individual consumer responses, giving you a complete picture from strategic level to tactical.
Our models allow you to understand how different audience segments respond differently to your marketing, going beyond what traditional analytics can show.
We identify unexpected patterns and consumer behaviors that arise from complex market interactions and cannot be detected through simple analysis.
Test marketing strategies in a virtual environment before investing real money, reducing risks and increasing confidence in decisions.
We use data directly from your website and customer touchpoints, calibrating models based on real customer behavior, not just assumptions.
Our entire analytical stack is designed with privacy in mind, allowing deep analysis without compromising customer data or regulatory compliance.
Our process of data analysis and model creation to obtain truly meaningful insights
We automatically collect data from all your marketing channels, website, and market conditions. We use API integrations with Google, Meta, TikTok, set up website analytics, analyze external factors (weather, economy) and competitor actions.
We clean data, identify outliers, process missing values, and prepare data for modeling. We create unified customer profiles based on all touchpoints for a complete representation of the customer journey.
We analyze historical performance to quantify the contribution of each channel. We conduct channel ROI assessment, budget optimization, sales forecasting, and statistical validation of results.
We create a simulation of consumer and competitor interactions in your market. We model consumer behavior, analyze competitive dynamics, forecast demand, and test "what if" scenarios.
We transform complex data into understandable, actionable recommendations. We automate analysis and reports, explain reasons for metric changes, provide optimization recommendations, and formulate a strategic action plan.
Examples of specific insights and recommendations you will receive
Your Facebook ROAS dropped because:
Recommended Actions:
Update creatives and adjust targeting to segments with high interest, which, according to our model, are still responsive (mainly the 25-34 age group from urban areas).
Based on MMM analysis and ABM simulations:
Detailed Analysis:
Our ABM simulation tested 32 different budget allocation options and found that this combination maximizes ROI while maintaining brand awareness metrics.
Our analysis predicts:
Recommendation:
Implement the strategy in phases, starting with high-response segments, and track competitor reactions weekly. Prepare alternative creatives for the second phase to prevent ad fatigue.
Based on customer profile analysis and analytics:
Recommended Solution:
Implement multi-tier free shipping thresholds and improve checkout performance on mobile devices. Our ABM simulation predicts this will reduce abandonment rate by 31% and increase average order value by €12.40.
Contact us today for a free consultation and learn how our advanced analytical tools can help you make more accurate, data-driven marketing decisions.