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Enhancing comparison shopping agents through ordering and gradual information disclosure

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Abstract

The plethora of comparison shopping agents (CSAs) in today’s markets enables buyers to query more than a single CSA when shopping, thus expanding the list of sellers whose prices they obtain. This potentially decreases the chance of a purchase within any single interaction between a buyer and a CSA, and consequently decreases each CSAs’ expected revenue per-query. Obviously, a CSA can improve its competence in such settings by acquiring more sellers’ prices, potentially resulting in a more attractive “best price”. In this paper we suggest a complementary approach that improves the attractiveness of the best result returned based on intelligently controlling the order according to which they are presented to the user, in a way that utilizes several known cognitive-biases of human buyers. The advantage of this approach is in its ability to affect the buyer’s tendency to terminate her search for a better price, hence avoid querying further CSAs, without spending valuable resources on finding additional prices to present. The effectiveness of our method is demonstrated using real data, collected from four CSAs for five products. Our experiments confirm that the suggested method effectively influence people in a way that is highly advantageous to the CSA compared to the common method for presenting the prices. Furthermore, we experimentally show that all of the components of our method are essential to its success.

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Notes

  1. As for today, some of the common CSAs are PriceGrabber.com, Bizrate.com and Shopper.com.

  2. In case the number of prices known to the CSA is odd, the lower part includes one additional price compared to the upper one.

  3. In case the number of prices in this subset is odd, the anchor phase includes one additional price compared to the effort phase.

  4. The raw data used for the experiments is available upon request from the corresponding author.

  5. This figure is a composition of Figs. 2 and 3.

  6. The videos are available upon request from the corresponding author.

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Acknowledgments

A preliminary version of this paper appeared in the Proceedings of the Twenty-Eighth National Conference on Artificial Intelligence (AAAI-2014) [24]. We would like to thank the reviewers of AAAI-2014 for the helpful comments on the earlier version of this paper. This research was partially supported by the ISRAEL SCIENCE FOUNDATION (Grants Nos. 1083/13 and 1488/14) and the ISF-NSFC joint research program (Grant No. 2240/15).

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Authors and Affiliations

  1. Department of Computer Science, Bar-Ilan University, Ramat Gan, Israel

    Chen Hajaj & David Sarne

  2. Department of Computer Science, Ariel University, Ariel, Israel

    Noam Hazon

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  1. Chen Hajaj
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Correspondence to Chen Hajaj.

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Hajaj, C., Hazon, N. & Sarne, D. Enhancing comparison shopping agents through ordering and gradual information disclosure. Auton Agent Multi-Agent Syst 31, 696–714 (2017). https://doi.org/10.1007/s10458-016-9342-8

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