Algorithmic pricing
Algorithmic pricing is the practice of automatically setting the practice of items for sale, in order to maximize the seller's profits.
Dynamic pricing algorithms usually rely on one or more of the following data.
- Statistical information on potential buyers, similarly to Bayesian-optimal mechanism design and random-sampling mechanisms.
- 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.
- Personal information of the currently active buyer, such as his demographics and his interest in the product. If the seller detects that you are about to buy, your price goes up.[3]
- Business information of the seller, such as the expected date in which he is going to receive new stocks, or his target selling velocity in units per day.[4]
References
- ^ "An Empirical Analysis of Algorithmic Pricing on Amazon Marketplace". doi:10.1145/2872427.2883089.
{{cite journal}}: Cite journal requires|journal=(help) - ^ Olivia Vanni. "The Truth Behind Pricing Algorithms on Amazon's Marketplace". Retrieved 29 June 2016.
- ^ Robert Wagner (2013). "What are the principles behind Amazon's algorithmic pricing and what do they achieve?". Retrieved 29 June 2016.
- ^ Douglas Karr. "How to Use Algorithmic Pricing to Maximize Profits". Retrieved 29 June 2016.