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] [4] [5]}
• 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. ^[6]
• 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

• Algorithmic trading
• Contribution margin
• Price optimization software
• Pricing
• Tacit collusion
• Yield management

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. "Amazon Repricer For Professional Sellers".
5. "Best Amazon Repricer - Repricing Software Tool".
6. Robert Wagner (2013). "What are the principles behind Amazon's algorithmic pricing and what do they achieve?" . Retrieved 29 June 2016.
7. Douglas Karr. "How to Use Algorithmic Pricing to Maximize Profits". Archived from the original on 1 June 2016. Retrieved 29 June 2016.