The latest iPhone from Apple was released in early September and started shipping shortly after. The release included a standard and Pro version, available in two sizes and various memory configurations. Other than the move to USB-C, the iPhone 15 doesn’t make major performance or feature leaps. For consumers, these advancements are largely iterative, and the upgrade cycle is driven more by contract and retailer incentives than hype. The launch prices for these new models are similar to previous years, ranging from $800 to $1600, and consumers often trade in their current device for credit towards their new one. This has made securing these trade-ins a priority for carriers and retailers.
The secondary mobile market, where pre-owned devices are sold at consumer or business levels, continues to grow faster than the market for new devices. This trend has been driven by COVID, which led to increased demand for devices for remote work, schooling, and entertainment, and the trend of trading in old phones for discounts on newer models or credits. This has resulted in high quality pre-owned devices entering the secondary market at a higher rate.
The macro-level factors impacting the B2B market for pre-owned iPhones include growing demand for refurbished iPhones, supply chain issues, market share, inventory levels, consumer spending and inflation, and competitive discounts. The micro-level factors affecting device pricing include age, model, condition, carrier locked states, and seasonality. B-Stock has built machine learning algorithms to predict B2B and B2C market prices of iPhones, empowering organizations to make data-backed decisions and optimize margins. B-Stock has collected B2B pricing data for all auctions across all phones since 2012 and has sold 34 million units in 270,000 auctions since 2017, allowing for outlier detection, interpolation, and machine learning techniques to be used in predicting market prices.
