Customer Perception Driven Product Evolution - Facilitation of Structured Feedback Collection

Oleksiy Khriyenko

2016

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.

References

  1. Adida, B., Birbeck, M., McCarron, S., Herman, I., 2015. RDFa Core 1.1 - Third Edition. W3C Recommendation. 17 March 2015, URL: http://www.w3.org/TR/rdfa-core/
  2. Bailey, A.A., 2005. Consumer Awareness and Use of Product Review Websites. Journal of Interactive Advertising. 6, 68-81.
  3. Berners-Lee, T., Hendler, J., Lassila, O., 2001. The Semantic Web, Scientific American 284(5), pp.34-43.
  4. Chen, Y., Xie, J., 2008. Online Consumer Review: Wordof-Mouth as a New Element of Marketing Communication Mix. Management Science. 54, 477- 491.
  5. Chevalier, J.A., Mayzlin, D., 2006. The Effect of Word of Mouth on Sales: Online Book Reviews. Journal of Marketing Research. 43, 345-354.
  6. Cunningham, H., Maynard, D., Bontcheva, K., Tablan, V., 2002. GATE: an Architecture for Development of Robust HLT Applications. Proceedings of the 40th Anniversary Meeting of the Association for Computational Linguistics (ACL).
  7. Ehrmann, T., Schmale, H., 2008. The Hitchhiker's Guide to the Long Tail: The Influence of Online-Reviews and Product Recommendations on Book Sales - Evidence from Ger- man Online Retailing. ICIS 2008 Proceedings.
  8. Ghose, A., Ipeirotis, P.G., 2011. Estimating the Helpfulness and Economic Impact of Prod- uct Reviews: Mining Text and Reviewer Characteristics. IEEE Transactions on Knowledge and Data Engineering. 23, 1498-1512.
  9. Jain, P., Hitzler, P., Sheth, A.P., Verma, K., Yeh, P.Z., 2010. Ontology Alignment for Linked Open Data. In: Proceedings of the 9th International SemanticWeb Conference, ISWC 2010, Shanghai, China, November 7-11, 2010, Springer-Verlag, 402-417.
  10. Khriyenko, O., 2015a. Customer Feedback System: Evolution towards semantically-enhanced systems, In: Proceedings of the 11th International Conference on Web Information Systems and Technologies, WEBIST 2015, 20-22 May, 2015, Lisbon, Portugal, 518-525.
  11. Khriyenko, O., 2015b. Semantic UI: Automated Creation of Semantically Personalized User Interface, In: GSTF International Journal on Computing (JoC), ISSN 2251-3043 (E-periodical: 2010-2283), October 2015, Vol. 4, No. 3, pp. 42-50, DOI: 10.5176/2251- 3043_4.3.330.
  12. Manning, C.D., Surdeanu, M., Bauer, J., Finkel, J., Bethard, S.J., McClosky, D., 2014. The Stanford CoreNLP Natural Language Processing Toolkit. In Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pp. 55-60.
  13. Semantic Web, 2001. URL: http://www.w3.org/2001/sw/ Shvaiko, P., Euzenat, J., 2012. Ontology matching: state of the art and future challenges. IEEE Transactions on Knowledge and Data Engineering, 2012.
  14. Witte, R., Khamis, N., Rilling, J., 2010. Flexible Ontology Population from Text: The OwlExporter. In: Int. Conf. on Language Resources and Evaluation (LREC), Valletta, Malta, ELRA (05/2010 2010).
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Paper Citation


in Harvard Style

Khriyenko O. (2016). Customer Perception Driven Product Evolution - Facilitation of Structured Feedback Collection . In Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST, ISBN 978-989-758-186-1, pages 196-203. DOI: 10.5220/0005793901960203


in Bibtex Style

@conference{webist16,
author={Oleksiy Khriyenko},
title={Customer Perception Driven Product Evolution - Facilitation of Structured Feedback Collection},
booktitle={Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST,},
year={2016},
pages={196-203},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005793901960203},
isbn={978-989-758-186-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST,
TI - Customer Perception Driven Product Evolution - Facilitation of Structured Feedback Collection
SN - 978-989-758-186-1
AU - Khriyenko O.
PY - 2016
SP - 196
EP - 203
DO - 10.5220/0005793901960203