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This paper seeks to explore approaches to consumer‐driven optimization of package design utilizing a novel modified conjoint analysis approach. The approach allows for dynamic creation and testing of a large number of design prototypes with consumers and finds optimal solutions on an aggregated, segmented (pattern‐based latent mindset segmentation) and individual basis.

The approach extends the consumer insights‐driven process, Rule Developing Experimentation (RDE), introduced by the authors (AG and HM) and developed in cooperation with Wharton School of Business (University of Pennsylvania), to graphical concepts.

Disciplined experimentation based on individual permuted experimental designs produces more targeted package designs with higher appeal to the consumers. The proposed steps describe fast, parsimonious and actionable process of application of RDE to package optimization, which provides valuable input for designers about consumer preferences.

The paper demonstrates that consumer research could and should be a central part not only at the final stages of the package design but at the initial stage as well. The steps of fitting the research into the package design process are shown providing a parsimonious way to include consumers in the early stages of package design.

The approach could help the marketers efficiently create better packages that consumers like and which will help marketers to differentiate their respective products from the competition.

This paper sets out to explore different approaches to optimizing web sites based on consumer preferences, introducing the most advanced form of landing page optimization, multivariate landing page optimization, and its variations. The approach aims to allow for the testing of a large number of web page prototypes with consumers and find real optimal solutions on an aggregated, segmented and individual basis. The latter aims to paveing the road to individually optimized pages and one‐on‐one marketing in the near future.

The approach described employs a new variation of multivariate landing page optimization to improve customer experiences with web sites through optimal design of the landing pages. The approach uses consumer insights‐driven rule‐developing experimentation (RDE) introduced by the authors and developed in cooperation with Wharton School of Business.

A disciplined experimentation based on statistically sound experimental designs produces much better web page designs. The resulting web pages have increased consumer acceptability, improved conversion rates and general customer experience.

Consumer research should be a central part in planning how to optimize web site experiences. The steps of fitting it into the web design are shown. There are already several readily available tools for effecting this.

The approach could help marketers create better web sites that consumers like and which will help marketers to differentiate their respective web sites from their competitors.

This paper aims to summarize the results of an empirical project to understand the perceptions of consumers of the future high end products in the USA. This project was a precursor of a larger global project on the topic.

The approach utilizes the consumer insights‐driven process, rule‐developing experimentation (RDE), introduced by the senior authors and developed in cooperation with Wharton School of Business (University of Pennsylvania). The empirical part was conducted with qualified US consumers (middle‐ and upper‐middle class respondents). Based on a series of in‐depth qualitative interviews with global leaders of luxury and premium companies, star designers and thought leaders, five dimensions of high end offering were identified, with each dimension having a unique set of four factors (elements). The second part included a quantitative survey based on RDE (modified conjoint analysis) conducted in the USA with 373 qualified middle‐ and upper‐middle class respondents to discover the driving forces behind their perceptions of high end.

There are four distinct consumer mindsets towards future high end products. The segmentation is based on a disciplined experimentation afforded by RDE and produces a more targeted understanding of the consumer mind.

The paper provides insights of what might drive the consumer perception of high end products in the near future. The pattern‐based consumer mind‐set segmentation creates actionable directions for corporations in answering today's big question “How can brands migrate from being cost‐driven commodities to higher margins and profits?” The answer is in the high end.

The approach offered here could help designers and brand managers to efficiently create better products that consumers like and perceive as high end. This will result in higher margins and help marketers to differentiate their respective products from the competition.

The purpose of this study is to use an approach that helps the pharma industry develop and structure communications that provide buyers and sellers with a better procedure to drive decisions to buy/sell stocks. Messages related to pharmaceutical companies and their products were collected from many sources.

An experimental design was employed to evaluate communication concepts in a systematic way.

The most important finding was that the proclivity to buy/sell individual pharmaceutical stocks responds to varying sets of messages.

The study only covers the pharmaceutical industry.

From a practical stand‐point, the methodology facilitates the design of informative messages for consumers and shareholders within the pharma industry.

The study is unique in that it presents a statistically grounded experimental design evaluating communications messages and personal values that are important for individuals who routinely sell or purchase stocks.

Innovation cannot come without in‐depth understanding of the product and its consumer perception. This paper aims to show the approach for consumer‐centric re‐development strategy, from design of the experiment to execution, analysis, modeling and strategies for implementation.

The approach described uses a relatively large‐scale experimental design of ingredients (12 variables) to vary sensory attributes and conduct sensitivity analysis with consumers.

The resulting product was a big marketing success for the producer. A disciplined experimentation based on statistically sound experimental designs produces much better food products with increased acceptability by consumers.

Statisticians have turned their attention to modeling the relations between physical variables and subjective consumer responses. The resulting products are optimized to meet sensory preferences of the consumers including varied sensory segmentation of the markets.

Using advanced multivariate experimental design for sensory optimization has proved many times its advantages although still not universally used. The approach could help the marketers and developers create better products that consumers like.