Market Research | Ideal Product Features

Ideal Product Features

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Intermediate

The Ideal Product Features study uses a mathematical model to give predictive results regarding the acceptance of rejection of a product or service by a population segment.

Evaluate the features you wish to highlight, through a conjoint model, counterposing them with a price range. Through this we can identify which attributes are most relevant to the consumer and the value they represent.

You determine the depth of the study, intermediate or detailed, by selecting the modules it will include.

Why choose it?

We link the characteristics consumers desire with a price range they're willing to pay them to help you make informed decisions on product configurations and pricing
The results allow you to generate various scenarios relating attributes with the desireability of certain products or services, leading you to conceptualize a new one that you may not have imagined
We have a pre-segmented consumer panel by category, which reduces the time needed for data collection
Our report's Data Visualization makes sure the insights inside are easily understood and shareable

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The Ideal Product Features study uses a mathematical model to give predictive results regarding the acceptance of rejection of a product or service by a population segment.

You determine the depth of the study, intermediate or detailed, by selecting the modules it will include.

Why choose it?

We link the characteristics consumers desire with a price range they're willing to pay them to help you make informed decisions on product configurations and pricing
The results allow you to generate various scenarios relating attributes with the desireability of certain products or services, leading you to conceptualize a new one that you may not have imagined
We have a pre-segmented consumer panel by category, which reduces the time needed for data collection
Our report's Data Visualization makes sure the insights inside are easily understood and shareable

See One page

Product Information

What includes? Methodology

The Ideal Product Features study includes:

Main indicators:

Best Valued Product
Relative Price by Feature
Importance Associated with Each Product or Service Feature

Price Associated with Each Feature
Product or Service Market Share
Preferred Products Ranking

Intermediate Study

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

Detailed Study
Includes the information from the intermediate study and also measures:

Consumption Intensity
Resilience to Change

Atlantia Search’s IPF methodology is based primarily on a conjoint analysis which yields highly relevant data and allows us to provide the most actionable insights for defining your product.

Main Methodologies:

Conjoint Analysis: A comprehensive method of analysis for new products in an highly competitive environment. Using multinomial logistic regression, it creates samples of all possible product configurations, based on features and their respective attributes, in order to identify the ideal product. This also provides an aggregated analysis of the relative value of each feature by attribute
Resilience to Change: with an advanced methodological analysis, we identify the aspects that trigger behavior changes among consumers. Through this study profiles are created and the ideal product features are perfected/adapted in order to detonate a purchase in each group
Price Sensitivity Index: Using the utility that is assigned to each change in the price by feature, the study sample is classified according to its price sensitivity
Market Share Simulator (Product vs Product): We use advanced statistical methods and standardized calculations to simulate the market share (as a percentage) that an ideal product would have, in comparison with competitors' products or with other combinations of ideal products

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.

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