Author:
Oleksiy Khriyenko
Affiliation:
University of Jyväskylä, Finland
Keyword(s):
Structured Feedback Collection, Triple Generation Support, Semantic Customer Feedback, Semantic Personalization, Product Customization, Customer Analytics.
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.
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