Price steering is the practice of “changing the order of search results to highlight specific products” and products prices. In this paper, we show an initial investigation to quantify the price steering level in search results shown to different kind of users on Google Shopping. We mimic the category of affluent users. Affluent users visit websites offering expensive services, search for luxury goods and always click on the most costly items results at Google Shopping. The goal is checking if users trained in specific ways get different search results, based on the price of the products in the results. Evaluation is based on well known metrics to measure page results differences and similarities. Experiments are automised, rendering large-scale investigations feasible. Results of our experiments, based on a preliminary experimental setting, show that users trained on some particular topics are not always influenced by previous search and click activities. However, different trained users actually achieve different search results, thus paving the way for further investigation.
Online user behavioural modeling with applications to price steering
Cozza, V.;
2016-01-01
Abstract
Price steering is the practice of “changing the order of search results to highlight specific products” and products prices. In this paper, we show an initial investigation to quantify the price steering level in search results shown to different kind of users on Google Shopping. We mimic the category of affluent users. Affluent users visit websites offering expensive services, search for luxury goods and always click on the most costly items results at Google Shopping. The goal is checking if users trained in specific ways get different search results, based on the price of the products in the results. Evaluation is based on well known metrics to measure page results differences and similarities. Experiments are automised, rendering large-scale investigations feasible. Results of our experiments, based on a preliminary experimental setting, show that users trained on some particular topics are not always influenced by previous search and click activities. However, different trained users actually achieve different search results, thus paving the way for further investigation.File | Dimensione | Formato | |
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