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Tytuł artykułu

Use of customer satisfaction survey in analytical marketing of a research institute

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Purpose: Research institutes in Poland, when focusing on scientific and research activities, do not always find time and are not always keen on preparing and using modern marketing tools. Meanwhile, these tools in the conditions of strong competition could significantly improve their relations with customers and the strength of market influence. Given the above circumstances, the purpose of this article is to present the design, implementation and results of a customer satisfaction survey at one of the Polish research institutes. Design/methodology/approach: As part of the design and implementation of the customer satisfaction survey, the Net Promoter Score method and marketing automation instruments were used to assess the quality of customer relations and the level of customer loyalty to the studied institute (case study). Findings: The surveyed customers were mostly satisfied with the services and relationships with the described research institute. The areas requiring improvement were the pricing policy and the way the offer was presented. Research limitations/implications: Limitations resulting from research are typical for case studies and relate to the inability to generalize the results. Nevertheless, the obtained conclusions may constitute the basis for improving analytical marketing tools in other research units. Originality/value: The cognitive value of the article includes the design and implementation of a customer satisfaction survey at a research institute, and personalized practical conclusions about the level of customer satisfaction and loyalty of the studied institute.
Rocznik
Tom
Strony
117--128
Opis fizyczny
Bibliogr. 12 poz.
Twórcy
  • Central Mining Institute, Poland
  • Silesian University of Technology. Faculty of Organization and Management, Poland
Bibliografia
  • 1. Banach, A. (2016). Data-Driven Marketing w Polsce. Marketing danych. Executive summary. Netsprint Group.
  • 2. Banach, A. (2017). Marketing oparty na danych buduje sprzedaż, zasięg i wizerunek. Sprawny Marketing, 6.
  • 3. Cao, G., Duan, Y., Banna, A.E. (2019). A dynamic capability view of marketing analytics: Evidence from UK firms. Industrial Marketing Management, 76, pp. 72-83.
  • 4. France, S.L., Ghose, S. (2019). Marketing analytics: Methods, practice, implementation, and links to other fields. Expert Systems with Applications, 1191, pp. 456-475.
  • 5. https://www.webankieta.pl/badania-klientow/net-promoter-score.
  • 6. Kakatkar, Ch., Spann, M. (2019). Marketing analytics using anonymized and fragmented tracking data. International Journal of Research in Marketing, 36(1), pp. 117-136.
  • 7. Lytras, M., Visvizi, A., Zhang, X., Aljohani, N.R. (2020). Cognitive computing, Big Data Analytics and data driven industrial marketing. Industrial Marketing Management.
  • 8. Misirlis, N., Vlachopoulou, M. (2019). Social media metrics and analytics in marketing – S3M: A mapping literature review. International Journal of Information Management, 38, pp. 270-276.
  • 9. Mondry, A. (2017). Bluerank i Rainbow – kampanie reklamowe napędzane danymi. Online Marketing Magazyn, 3(34).
  • 10. Wang, W.Y.Ch., Wang, Y. (2020). Analytics in the era of big data: The digital transformations and value creation in industrial marketing. Industrial Marketing Management, 86, pp. 12-15.
  • 11. Yu, Ch., Zhang, Z., Lin, Ch., Wu, Y.J. (2019). Can data-driven precision marketing promote user ad clicks? Evidence from advertising in WeChat moments. Industrial Marketing Management.
  • 12. Żulicki, R. (2019). Pułapki myślowe data-driven. Krytyka (nie tylko) metodologiczna. Marketing i Rynek, 8, DOI: 10.13140/RG.2.2.12375.83368.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-d1902537-5fdb-404b-8c8c-30b10f93e87d
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