Searching visually resembling products with particular style or shape shows a strong demand in electronic commerce. We apply our preliminary content-based image retrieval (CBIR) achievements to work towards this end. Though the visual clue is useful to product recommendation, customers usually also care the functionality, accessories, etc. Consequently, we propose a novel approach that exploits visual features, product descriptions and sale records to reformulate product recommendation by calculating the correlations and weights of such multifaceted aspects. The simulation results demonstrate that the proposed approach is feasible and can be applied to online shopping, auction or advertisement.