In the United States alone, millions of tons of waste are generated every year, highlighting the urgency for innovative solutions for waste management. Traditional strategies of reducing the amount of End-of-Life (EOL) products include reuse, recycle, remanufacture and disposal. Recently, resynthesis has been proposed in the design community as an alternate approach that aims to combine assemblies/subassemblies of EOL products from multiple domains to create a 'new' product, distinct from its parent products. The original work on resynthesis assumes that there is an equal demand for 'resynthesized products' based on the available supply of EOL components that the resynthesized products are composed of. Furthermore, the price was assumed to be equal to the price of similar products on the market. However, such an assumption may underestimate or overestimate the value of resynthesized products, which in turn impacts the demand of these products. Recent research has shown that customer reviews express customers' true opinion and value for specific products or product features. The authors of this paper propose a data mining methodology to quantify the price and demand for resynthesized products by mining user-generated reviews of products publicly available on the internet. A case study involving a resynthesized electronic mouse and white board eraser is presented to demonstrate the feasibility of the proposed methodology.