One of the hardest parts of selling an item secondhand is determining the optimal price. If you price an item too high, it might not sell. If you price an item too low, you leave money on the table. But with so little data available to consumers and brands, pricing a secondhand item can require time-consuming research or a lot of testing and learning.
For this reason, Archive has built an algorithm that takes into account a number of variables— such as MSRP, item condition, and sales trend data—and through our dynamic pricing feature, we provide each individual item with an optimal selling price.
In a peer-to-peer resale model, providing a sale price removes any guesswork on behalf of the seller and ensures a quick and seamless listing process, thus increasing listing conversion. Our prices are optimized for sell-through, ensuring sellers see a faster time-to-sell than on third party platforms and incentivizing them to list through a branded experience. That being said, if a seller is looking to sell an item as fast as possible rather than maximizing value, they can opt in to our Smart Pricing feature. Smart Pricing will automatically lower the price of a listing 10 days after listing by 10% every 7 days until the item sells or it hits a preset price floor.
In a managed resale model, in which Archive processes brand-owned inventory to be cleaned and repaired as necessary, our pricing functionality is an important factor in helping brands build profitable resale businesses. In these scenarios, our pricing algorithm takes into account the cost to repair and clean each item in addition to other variables, to ensure every item sold drives profitable revenue for the brand. Archive’s technology can also set specific brand rules around pricing, so that if an item’s cost to clean and repair leaves little-to-no margin for a brand after resale, we can instead route that item to be recycled or donated.
Archive’s dynamic pricing feature was built to address a key pain point in the secondhand market, and to ensure a first class user experience for both consumers and brands.
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