How to price seemingly unique goods in the global resale market
Traditional retail pricing is often calculated at the SKU level (i.e This “Cute New Dress by this Trendy Designer”) and is marked up based on the cost to produce the item. Items are then discounted throughout the season. Simple, right?
In the Wild-Wild West of the nascent resale market; that “Cute New Dress” becomes that “Cute off-white dress, size small, in great condition but with small wear on the left bottom hem, from this designer but a special diffusion line from 5 years ago, but the brand is on trend again…for now” Hmm, now how do you price that? The easiest answer is to take a flat percentage off MSRP but beware — the item may actually sell near or above MSRP on the secondary market and you may not even have access to original MSRP data.
Create a Bid/Ask Marketplace
Resale companies like StockX do not estimate what a super rare pair of Jordans should sell for on a particular day — they let the market decide.
StockX is the world’s first stock market for things — a live ‘bid/ask’ marketplace. Buyers place bids, sellers place asks and when a bid and ask meet, the transaction happens automatically. Retro Jordans, Nikes, Yeezys and more — now 100% authentic guaranteed. (StockX Website)
Assuming you have the demand on your platform, this is a transparent way to give the pricing power to your customers while still insuring a secure transaction. StockX is best known for sneakers and streetwear but they also have handbags & watches on their platform.
Taking this even a step further, StockX has seen success with their “IPO’s (Initial Product Offerings)” — most recently with brands like New Balance . This model has lead to much higher than normal prices for newly released styles. The average clearing price for the “No Vacancy Inn’s New Balance 650” was $400, over 200% higher than New Balance’s similar style retail prices (Note: Only 400 pairs were released).
Price Match with Other Resale Platforms
Brands and resale platforms may look to web scraping competitor sites to determine a realistic price range for each item. This can be extremely helpful to gain insight about the current market for your items but it can become complicated for a few reasons:
Web scraping can be difficult. Each site is organized differently and some resellers intentionally remove the price after the item sells. More often than not you are actually scraping the most recent list price which could vary from the price the item sold. Historical pricing may be harder to find.
Parsing and cleaning the scraped data is time intensive. Scraping data is great but you need to parse and clean the data to make it useful. Most resale sites name products differently. In the luxury sector this can have a huge impact on prices. Have you seen the endless color and material combination’s of an Hermes Birkin bag? Brings a tear to your eye. Resale is not for the timid.
On a positive note, start-ups have emerged to help brands and resellers tackle and standardize the elephant in the room: Item identification . A great example of this is New York based Eon.
Eon was founded with the vision to power the digital foundation for the connected and circular business. Eon connects brands and customers, unlocks unprecedented business intelligence, and powers new business models.
Eon has partnered with brands and retailers to create a unique identity, CircularID, which stays with the item through its lifecycle — from manufacturing to resale and even garment recycling. The CircularID includes key information like MSRP, style name, material and manufacturing location. For newer items, this will have a large impact on resale pricing and resale processing in general.
Build your own pricing model
If option A or B are not up your alley, consider machine learning to automate your pricing. There are many different approaches to take to build a pricing model but also some key things to consider.
Do you have historical sales data available? Machine learning requires large amounts of clean and tagged historical data that you trust. This may seem obvious but with new brands and retailers entering the space, they can’t rely on robust historical pricing data. As brands & retailers continue to standardize the resale process (condition ratings, authenticity etc.), this will aid in creating more useful data.
What are your pricing goals as a resale program? The prices your model will return will be based on the data you are feeding it — if you are using price matching with sites that discount heavily to move items as quickly as possible, the prices your model returns will reflect that.
Ultimately, you as a brand or retailer need to think through what additional value does your resale platform have? You may learn that your platform may garner higher prices than competitors because of a unique selection or ability to verify authenticity. Would a customer pay the same for a Rolex at pawn shop as they would if resold directly from brand? Do you guarantee the buy-back of items purchased on your site within a certain period of time like ReBag?
There are many approaches to resale pricing. Like everything in the resale market, it is not black & white. Take time to consider where and how you add the most value and price accordingly.