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Personalize Voice
Any Audience
Completely Confidential
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F'inn Toolkit

Quantitative Tools & Advanced Analytics

Tools

  • Audience Profiling

  • Attitude & Usage

  • Awareness (Ads, PR campaigns, Brand updates, Policy changes etc.)

  • Brand Perceptions

  • Communication Highlights

  • Concept/ Idea Test

  • Journey

  • Feature Prioritization

  • Message Refinement

  • Naming Evaluation

  • Needs Assessment

  • Payment Plan Optimization

  • Price Sensitivity

  • Product Placement

  • Satisfaction

  • Segmentation

  • UI/UX

Advanced Analytics

  • Cluster, latent class factor analysis for segmentation to define target audience and personas

  • Discrete Choice Modeling, MaxDiff, TURF to optimize bundles, by audience:

    • Product line

    • Features

    • Pricing

    • Use cases

  • Jobs to be done to build needs hierarchy and use cases, MaxDiff or TURF analysis to prioritize them

  • Predictive modeling to measure market size for category, product (via proven forecasting models) including cannibalization

  • Regression and correlation analysis to identify drivers of purchase, consideration, trust, etc.

  • Sentiment analysis to assess brand or product feedback in customers’ own words

  • Simulations: Models complex systems and predicts outcomes under different scenarios

  • Structural Equation Modeling (SEM) to find brand/ category drivers

F'Inn Toolkit

Quantitative Tools & Advanced Analytics

  • Audience Profiling

  • Attitude & Usage

  • Awareness (Ads, PR campaigns, Brand updates, Policy changes etc.)

  • Brand Perceptions

  • Communication Highlights

  • Concept/ Idea Test

  • Journey

  • Feature Prioritization

  • Message Refinement

  • Naming Evaluation

  • Needs Assessment

  • Payment Plan Optimization

  • Price Sensitivity

  • Product Placement

  • Satisfaction

  • Segmentation

  • UI/UX

Tools

Advanced Analytics

  • Cluster, latent class factor analysis for segmentation to define target audience and personas

  • Discrete Choice Modeling, MaxDiff, TURF to optimize bundles, by audience:

    • Product line

    • Features

    • Pricing

    • Use cases

  • Jobs to be done to build needs hierarchy and use cases, MaxDiff or TURF analysis to prioritize them

  • Predictive modeling to measure market size for category, product (via proven forecasting models) including cannibalization

  • Regression and correlation analysis to identify drivers of purchase, consideration, trust, etc.

  • Sentiment analysis to assess brand or product feedback in customers’ own words

  • Simulations: Models complex systems and predicts outcomes under different scenarios

  • Structural Equation Modeling (SEM) to find brand/ category drivers

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