Product Concept Test

Product Concept Test

The Product Concept Test will evaluate the acceptance of an idea or product regardless of its current phase of iteration.  You'll get actionable insights corresponding to the level of depth you select for the study: exploratory, intermediate, or detailed.  It's ideal for not just evaluating if what you have in mind satisfies the needs of consumers, but for detecting the main draws of a product/ its packaging,  and measuring its potential against the competition. 

Why choose it?

  • Not only will you determine the product's viability but also the purchase intent of consumers 

  • According to the modules you choose, you'll be able to identify the emotions your concept, product, and/or packaging arrouses in consumers

  • Our deliver times are faster than similar offers on the market

  • Our report's Data Visualization  makes sure the insights inside are easily understood and shareable 

Analyze modules like concept evaluation,  name, packaging, and engagement dynamics or promotions.

Main Indicators:
  • Most Valued Concept 
  • Perceived Quality
  • Purchase Intention
  • Concept Attractiveness 
  • Triggered Emotions
  • Detected Differentiators  

Study Depth:

Describes and executes crosses of demographic data in addition to identifying the population segments with greater and lesser acceptance.

Includes the information of the Exploratory study in addition to measuring:

  • Price elasticity
  • Purchase intention linked to price

This version adds:

  • Concept Match Index, for identifying the desired characteristics of a product such as your.  It considers emotional responses, price elasticity, and desired characteristics

With the results obtained from the study on your concept, product or package...


  • Areas for improvement
  • Consumer rationales for acceptance or rejection
  • Emotions generated in the consumer

Design, maintain, reinforce or redesign strategies for:

  • Differentiation from the competition
  • Advertising and communication

Atlantia Search’s proprietary methodology for evaluating a product concept includes multiple types of statistical analyses and methodologies that yield highly relevant data and the most actionable insights.

Among which we include:

  • Concept Match Index:  a method that combines the consumer’s emotional response, price elasticity, and desired characteristics to gain a holistic consideration of the their perceptions of your product concept
  • 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

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 such as:

  • 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: we utilize additional tools and methods to guarantee the sample quality; control questions, anomalous answers rejection, automatic validation of open answers, missing data algorithms, contingency tables, etc.

We leverage Artificial Intelligence for our data analysis:

Atlantia Search’s automated AI-driven statistical 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 which 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 methods 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.