Usage and Attitudes (U&A)

Usage and Attitudes (U&A)

$5 115 USD


Know your consumer and shopper. Understand the consumption trends of the category and/or brand. Profile your consumers and shoppers based on their lifestyles. If you lack understanding about your consumers or shoppers, don't know your customer personas or those of the category, or you don't understand their lifestyles and behaviors, this is the ideal product for you.

This product allows you to understand:

  • The panorama of consumption and/or purchase of the category and brand.

  • Consumers by consumption intensity.

  • Consumers and shoppers based on lifestyles.

  • The main decision trees for the purchase. 



In your delivered U&A, you will find the necessary indicators for understanding your consumer, shopper, and their consumption habits for your category and brand. You'll be able to select from:

PROFILES

  • Category Consumer
  • Category Shopper
  • Brand Consumer
  • Brand Shopper

PROFILE MODULES

  • Media Consumption
  • Social Networks
  • Health Habits
  • Technology
  • Social Causes
  • Free Time
  • Brand Orientation
  • Eating Habits
  • Sustainability
  • Brand Loyalty
  • Digital Habits
  • Price Orientation

CONSUMPTION PANORAMA FOR THE CATEGORY AND/OR BRAND - IN ALL STUDY SCOPES

  • Consumption Funnel
  • Most Consumed Packaging
  • Preferred Versions
  • Complimentary Categories/Brands
  • Consumed Categories/Brands
  • Spontaneous Consumption Drivers
  • Spontaneous Consumption Limiters
  • Forms of Consumption
  • Consumption Places
  • Total Consumption Places
  • Consumption Pairings
  • Consumption Frequency

CONSUMERS BY CONSUMPTION INTENSITY

  • Heavy, Medium, and Light
  • Weight by Type of Consumer
  • Packaging Consumed
  • Preferred Brands
  • Consumption Drivers
  • Consumption Limiters
  • Consumption Frequency

The indicators will depend on the selected profiling dimensions:

  • Customer Personas Through a K-Means Clustering Algorithm 
  • Consumption Weight by Cluster
  • Packaging Consumed by Cluster
  • Preferred Brand by Cluster
  • Consumption Drivers by Cluster
  • Consumption Limiters by Cluster
  • Consumption Frequency by Cluster
  • Specific Indicators for Each Lifestyle

CONSUMPTION DECISION TREE - ONLY IN DETAILED SCOPE

  • Consumption Decision Trees of the Category and/or Brand
  • Ranking of the Category and/or Brand

PURCHASE PANORAMA FOR THE CATEGORY AND/OR BRAND - IN ALL STUDY SCOPES

  • Purchase Funnel of the Category
  • Purchase Triggers
  • Zero Moment of Truth
  • Purchase Places and Volume
  • Purchase Journey
  • Times and Days of Highest Demand
  • Purpose of the Purchase
  • Brands Purchased
  • Spontaneous Purchase Drivers and Conditions
  • Spontaneous Purchase Limiters
  • Payment Methods
  • Purchase Decision Maker and Influencer
  • Total Purchase Places
  • Purchase Frequency

SHOPPERS BY FREQUENCY AND PURCHASE INTENSITY 

  • Occasional vs. Frequent Shopper
  • Weight by Type of Shopper
  • Purchased Packaging 
  • Preferred Brands
  • Purchase Drivers
  • Purchase Limiters
  • Purchase Frequency
  • Payment Methods

The indicators will depend on the selected profiling dimensions:

The indicators will depend on the selected profiling dimensions:

  • Shopper Personas Through a K-Means Clustering Algorithm 
  • Purchase Weight by Cluster
  • Packaging Purchased by Cluster
  • Preferred Brand by Cluster
  • Purchase Drivers by Cluster
  • Purchase Limiters by Cluster
  • Purchase Frequency by Cluster
  • Specific Indicators for Each Lifestyle

PURCHASE DECISION TREE - ONLY IN DETAILED SCOPE

  • Purchase Decision Trees of the Category and/or Brand
  • Ranking of the Category and/or Brand

Our report provides the data that will help you make decisions for generating or adapting your comercialization, communication, or product strategies:

  • Get back in the loop with your consumers' changing habits and attitudes
  • Validate or discover the causes of sales movements
  • Extend product lines
  • Validate co-branding strategies
  • Discover new market niches
  • Generate more effective campaigns
  • Identify where to improve your offer
  • Improve your profit margins by identifying the demand elasticity in terms of product price and/or brand
 

Atlantia Search’s methodology for identifying consumer and shopper profiles includes multiple types of statistical analyses which yield highly relevant data and actionable insights.

Among which stand out:

  • Profile Clustering: through a analysis of combinatorial K-means and MCA we generate groups of differentiated profiles with statistically relevant heterogeneous consumption patterns.
  • CHAID Analysis: through a Chi-square Automatic Interaction Detector we obtain a predictive model to highlight a specific group of consumers. Two of the strengths of this method are: the simplicity of the graphical representation via a classification tree and the compact format of the rules of natural language. 
  • Single and Multivariable Correlation Analysis: through our AI-driven and automated data analytics tools, we quickly and efficiently carry out different single and multivariable analysis of the data so we can identify the most relevant insights of your study. 

Our methodology allows us to generate differential analyses in the following ways:

  • Individual
  • Modular 
  • Clustered

The Most Advanced Tools for Assuring Sample Quality:

By default, all of our studies done through CAWI, CAPI and CATI, include automated systems for sample quality control:

  • Anti-Speeder: a validation algorithm that estimates the minimum time needed to complete a survey and rejects whatever values fall below it.
  • Unique User Validation (UUV): to avoid multiple survey replies from the same respondent more than 20 parameters from the respondent and their device are validated.  
  • Anti-Random Answers (ARA): an algorithm that identifies psychological patterns that indicate random responses and removes them. 
  • Geo-referenced Validation: We guarantee location authenticity by GPS-tracking respondents or by using their  IP address. 
  • Other Tools: we use tools for assuring sample quality; control questions, anomalous answers rejection, automatic validation of open answers, missing data algorithms, contingency tables, etc.