Customer Perception Driven Product Evolution : Facilitation of Structured Feedback Collection

Abstract

Competitive environment not only requires effective advertising strategies from the product producers and service providers, but also to do comprehensive and sufficient analysis of their customers to understand their needs and expectations. Successfully involving customers into a product/service co-creation process, companies more likely increase their future revenue. Customer feedback analysis is widely applied in marketing and product development. Among other challenges (e.g. customer engagement, feedback collection, etc.) automation of customer feedback analysis becomes very demanding task and requires advance intelligent tools to understand customers’ product perception and preferences. Since, mining of free text feedbacks (which is still the most representing form of the real voice of the customer) is challenging, this work presents an approach towards customer-supported transformation of feedback into structured data. Further analysis and manipulation with semantically enhanced customer feedback and product/service description makes possible to automatically generate useful changes in existing products or even a new product description that takes into account actual needs and preferences of customers.