While many analytics teams deliver value in specific, well-defined situations, applying those same models to all business problems doesn’t always work. Organizations need analytics that are fluid, agile, and capable of applying knowledge acquired for one purpose to new domains and challenges. Our Information Sciences team combines different forms of data and methodologies, unpacks causal relationships, and creates models through an iterative process to determine the best approach for you.
The goal for many analytics teams is to be an insights delivery machine — one that constantly churns out an abundance of data. That’s not us. At CMI, we focus on finding the right data and transforming that data into compelling narratives that are customized for your organization through the power of advanced analytics.
This is how we will tackle your most pressing issues, together.
Models & Techniques
- Trade Off Analysis
- Max Diff
- TURF
- Conjoint (Traditional , Adaptive, Menu based)
- Discrete Choice
- yPrescribe™
- Predictive Modeling / Key Drivers
- Regression (Linear, Logistic, Latent Class)
- SEM
- Decision Trees
- Data Reduction
- Principal component Analysis (aka Factor analysis)
- Machine Learning
- Random Forest
- Gradient Boosting
- MARS (Multivariate adaptive regression spline)
- Time Series / Forecasting
- ARIMA (Autoregressive Integrated Moving Average)
- Dynamic Modeling
- MMM (Marketing Mix Modeling)
- Pricing Models
- Gabor-Granger
- Choice modeling
- Van Westendorp
- Cluster Analysis/ Segmentation
- Latent Class
- CCEA (Convergent Cluster Ensemble Analysis)
- Hierarchical Clustering
- Two-Step Clustering
- Test/Sentiment Analysis
- Perceptual Mapping
Advanced Analytics Related Work
Let's Talk Analytics
We are committed to providing spot-on research to inform your critical business decisions.
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