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Every year, retailers launch a myriad of new products. The success rate of such new products directly influences a retailer's success in terms of gross profit, customer loyalty and brand image. In the past decades, many self-report and focus group based methods were implemented to gain insights in future market performance of new products. However, social psychology and market research studies have established that self-reports are unreliable to accurately predict customer preference. In this article, we propose a novel approach based on brain data to forecast product performance and discuss the importance of pre-market forecasting in the footwear retailing industry. We implemented and validated the tool in collaboration with a European shoe store chain. This case study showed that self-report based methods cannot accurately foretell success, while using brain data the prediction accuracy reached 80 per cent. We also compared how these two different methods might influence company gross profit. Simulations based on sales data showed that self-report based prediction would lead to a 12.1 per cent profit growth, while brain scan based prediction would increase profit by 36.4 per cent. Thus, this innovative neuroscientific approach greatly improves brand image and brings considerable value for organizations, shareholders as well as consumers.
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Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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