The Ideal Product Features (IPF) 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.
IPF is indispensable for analyzing the viability of a product or service before its commercialization, as well as identifying its competitive advantages and the price range that the consumer is willing to pay for them.
Our customers use this product when they are planning product launches or intending to add features to an existing product. They also find it useful when they want to know their products' market share and analyze the profitability of a business.
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 along with other methodologies such as price sensitivity index, resilience to change, and a market share simulator (product vs product).
For collecting data IPF utilizes Computer-Assisted Web Interviewing (CAWI) and the study sample's quality is ensured by quality control systems like Anti-Speeder, Unique User Validation (UUV), Anti-Random Answers (ARA), and Geo-Referenced validation, among others.
With our AI-driven and automated data analytics tools, we carry out different single and multivariable analyses in a matter of minutes to identify the most relevant insights of your study.
- 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
- You decide the depth of your study and you can select between intermediate and detailed versions
- Our delivery times are faster than our competitors'
- Only pay for the things you want to know by selecting modules that group together key questions for each indicator
- We use data visualization in your report to make the insights quickly and easily understandable and sharable
The Ideal Product Features study includes:
- 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
Describes and executes crosses of demographic data in addition to identifying the population segments with greater and lesser acceptance.
Includes the information from the intermediate study and also measures:
- Consumption Intensity
- Resilience to Change
With the results obtained from your study you'll be able to...
- Your product's or service's areas for improvement
- Yhe value added with regard to the preferences of the customer
- Purchase intention
Design, maintain, reinforce or redesign strategies for:
- Differentiating yourself from the competition
- Key messages to highlight about products or services
- The viability of additional product or service features
- The profitability of a business idea
- Products or services based on their internal characteristics
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.
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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