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Descriptive & Predictive Modeling

We model your behavioral and self-reported data, together or separately, to understand what drives performance or predicts key outcomes.

We leverage our robust toolkit of traditional – as well as innovative and proprietary methods including Bayesian, machine learning and AI-based tools – to organize, describe, diagnose and predict important outcomes.

We apply our tools to your first party data, bespoke surveys, experimentally designed stimuli, A/B tests or naturally occurring in-market variations, whichever is required to address your business question.

Descriptive & Predictive Modeling lets you:

  • Understand how consumers think about brands
  • Identify early indicators of likely churn
  • Prove or disprove hypotheses about what works
  • Optimize prices and feature sets
  • Fine-tune media buys

Approaches

  • Perceptual Mapping

    Visualize where you and your competitors fall in consumers’ minds along the dimensions that are most salient to them in differentiating brands.

  • Factor Analysis

    Understand which needs, attitudes, behaviors or perceptions tend to go together in order to condense hyper granular data into executive level themes.

  • Bayesian Network Drivers

    Understand which in-market perceptions currently drive preference or purchase, learn how the perceptions are inter-related, and identify the set of items that together are worth focusing improvement efforts against.

  • Conjoint / Choice Modeling

    Explore possibilities outside the realm of today’s reality by testing hypothetical combinations of features and benefits to understand what customers value and estimate how they would react to things you might create.

  • Media Mix Modeling

    Optimize the efficiency and performance of your media strategy by quantifying the relationships between tactics and outcomes to surface how best to achieve maximum results.

  • Survival (Churn) Modeling

    Spot signs in your CRM data that a customer is likely to churn, either by modeling actual churned customers or, if available, modeling those who have low satisfaction scores so you can have more time to intervene.

Have Questions? Get In Touch

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