Algorithmic pricing

Algorithmic pricing is the practice of automatically setting the requested price for items for sale, in order to maximize the seller's profits.

Dynamic pricing algorithms usually rely on one or more of the following data.

  • Probabilistic and statistical information[1] on potential buyers; see Bayesian-optimal pricing.
  • Prices of competitors. E.g., a seller of an item may automatically detect the lowest price currently offered for that item, and suggest a price within $1 of that price.[2][3] Automated technology applications for pricing differ among competitors which makes price discovery highly complex and dynamic in the general retail marketplace.[4][5] Retailers and technology vendors claim the adoption of new pricing tools continues to be dependent on their consumer's price sensitivity and trust that it will not be working against them.[6]

Personal information of the currently active buyer, such as her or his demographics and her or his interest in the product. If the seller detects that you are about to buy, your price goes up.[citation needed][original research?]

  • Business information of the seller, such as the expected date in which he or she is going to receive new stocks, or her or his target selling velocity in units per day.[7]

See also

References

  1. ^ Cohen, Maxime; Spittle, Tim; Royer, Jimmy (September 16, 2024). "Assessing Algorithmic Versus Generative AI Pricing Tools" (PDF). Retrieved April 8, 2025.
  2. ^ Chen, Le; Mislove, Alan; Wilson, Christo (2016). "An Empirical Analysis of Algorithmic Pricing on Amazon Marketplace". Proceedings of the 25th International Conference on World Wide Web. pp. 1339–1349. doi:10.1145/2872427.2883089. ISBN 9781450341431. S2CID 9570936.
  3. ^ Vanni, Olivia (2016-04-12). "The Truth Behind Pricing Algorithms on Amazon's Marketplace". BostInno. Archived from the original on 2016-04-13. Retrieved 29 June 2016.
  4. ^ Brown, Zach Y., and Alexander MacKay. “Competition in Pricing Algorithms.” American Economic Journal: Microeconomics, vol. 15, no. 2, 2023, pp. 109–56. JSTOR Accessed 5 May 2026.
  5. ^ Skye Jacobs. (20 March 2026). "Walmart secures two AI pricing patents, raising dynamic pricing concerns." TechSpot website Accessed 5 May 2026.
  6. ^ Kevin Williams. (21 March 2026). "The Bottom Line: Walmart digital price labels are coming to every store shelf in U.S. by end of 2026." CNBC website Accessed 5 May 2026.
  7. ^ Douglas Karr. "How to Use Algorithmic Pricing to Maximize Profits". Archived from the original on 1 June 2016. Retrieved 29 June 2016.

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