Usage and Attitudes (U&A)

Usage and Attitudes (U&A)


The Usage and Attitudes (U&A) study is a modular product that lets you select just the indicators and depth level you need for your strategy and/or specific moment in your business. It's useful for detecting unmet needs and identifying the behavioral patterns of shoppers and consumers.

Why choose it?

  • We've divided the study at the level of shoppers and consumers to generate actionable insights specific to each of them

  • You decide the depth of your study: exploratory, intermediate, or detailed

  • You only pay for the modules that are most relevant to what you need to know about your shopper or consumer

  • We generate clusters only from groups with the most relevant behavioral similarities, as well as a decision tree. Knowing them in detail will give you a competitive advantage (available in the intermediate and detailed studies)

  • Our data visualization makes understanding and sharing the insights a breeze 


You'll be able to select from these indicators:

Consumer:

  • Category consumption funnel
  • Brand preference funnel
  • Consumption frequency
  • Complementary consumption categories
  • Consumption occassions 
  • Consumption companions
  • Decision making process (deciders vs influencers)
  • Consumption drivers and limiters

Shopper:

  • Activities previous to purchasing
  • Purchase frequency
  • Purchased versions
  • Purchase drivers
  • Point of Sale
  • Journey and escort in the purchase moment
  • Desicion makers vs influencers
  • Payment methods
  • Price paid in preferred point of sale

Modules:

 Each module contains specific questions with the purpose of profiling consumers and/or shoppers of the brand or product category, in addition to variables of lifestyles. Select the necessary ones according to the version of the U&A you selected.

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

Study Depth:

Exploratory Study
Allows you to answer the 6 W's (who/what/where/when/why/how) of the consumer or shopper at a descriptive level (frequencies and averages).
Classify a consumer by their consumption intensity (light consumer, medium consumer, heavy consumer) and the shopper by their purchase intensity (frequent shopper, ocassional shopper).

Intermediate Study
Integrates a Cluster Analysis that segments consumers and/or shoopers according to similar consumption patterns, creating three to six distinct groups of consumers and/or shoppers. The intermediate study will also provide these indicators:

  • Distribution of each segment
  • Lifestyle variables by segment
  • Consumption and/or purchase patterns by segment
  • Plus everything from the exploratory version of the U&A

Detailed Study
Includes the content of the previous versions, in addition to adding a decision tree for the consumption and/or purchase of a category and/or brand (Chaid Tree Analysis) It will give you the variables that have "more weight when deciding" to consume and/or purchase your product or service.

The best moment to do one of these studies is when...

  • you've stopped knowing your consumer or, after a while, you need to approach them again
  • there's a new habit of your shopper/consumer to become familiar with
  • you need to validate/find out the causes of sales movements that you can't explain
  • you're interested in starting a new product line
  • you want to validate cobranding strategies

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

Among which stand out:

  • Profile Clustering: Through a statistical analysis of combinatorial K-means with ACM analysis, we’re able to generate groups of differentiated profiles that have statistically relevant heterogeneous consumption patterns.
  • CHAID Analysis: Through a Chi-square Automatic Interaction Detector, a predictive model is created to highlight a specific group of consumers.CHAID creates all possible cross tabulations for each categorical predictor until the best outcome is achieved and no further splitting can be performed. In the CHAID technique, we can visually see the relationships between the split variables and the associated related factor within the tree. Two of the strengths of this method are the simplicity of the graphical representation vía 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 analyticsl 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 y CATI, include automated systems for sample quality control:

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

Automated Data Analytics Tools:

Atlantia Search’s automated AI-driven data analytics tools allow us to carry out single and multivariable analyses in a question of minutes to find relevant insights. We are also capable of carrying out a host of other analyses that include K-means, CHAID Tree, Conjoint, Maxdiff, M-Estimation, Ordinary Less Scores, Reach Regressions, Logit-regressions, Linear Regressions, Anovas, Pivot Tables, to name a few, and statistics generation tests such as T-test ANOVA, Games-Howell Nonparametric Post-Hoc Tests, Cohen’s F Statistic, Pearson Correlation, Spearman Correlation, Point Biserial Correlation, Cohen’s D, Paired T-test, Fisher’s Exact Test, Chi-Squared Test, Cramer’s V, Z-test, Time-series Analysis, Difference in differences (DID, DD) among many others.