Stefanie Schreiber

Ratings-/Rankings-Based Versus Choice-Based Conjoint Analysis for Predicting Choices

Nowadays, for market simulation in consumer markets with multi-attributed products, choice-based conjoint analysis (CBC) is most popular. The popularity stems—on one side—from the possibility to use online-panels for affordable data collection and—on the other side—from the possibility to estimate part worths at the respondent level using only few observations. However, a still open question is, whether this money- and time-saving approach provides the same or even better results than ratings-/rankings-based alternatives. An experiment with 787 students from Poland and Germany is used to answer this question: Cola preferences are measured using CBC as well as ratings-/rankings-based alternatives. The results are compared using the Multitrait-Multimethod Matrix for the estimated part worths and first choice hit rates for holdout choice sets. The experiment shows a superiority of CBC, but also important differences between Polish and German cola consumers that outweigh methodological differences.

Multivariate Landing Page Optimization Using Hierarchical Bayes Choice-Based Conjoint

Landing pages are defined to be the home page of a website (e.g., an online shop) or a specific webpage that appears in response to an ad. Their design plays an important role in decreasing the number of visitors leaving the website without any activity (e.g., clicking a banner, purchasing a product). For improving landing pages, the traditional A/B testing approach offers a simple but limited solution to evaluate two different variants. However, recently, new approaches have been introduced. Webpages with multiple variations of website elements (e.g., navigation menu, advertising banners) generated through experimental designs are rated by customers (Gofman et al., J. Consum. Mark. 26(4):286–298, 2009).The paper explores a new approach for multivariate landing page optimization using hierarchical Bayes choice-based conjoint analysis (CBC/HB) that combines the potential to test a large number of variants with a short survey. The new approach is discussed and applied to improve the online shop of a popular German Internet pharmacy. Choice data are collected from a large sample of customers. From the results an optimal landing page is derived and implemented.