Neurointerview as the latest method of marketing research

The modern marketing paradigm requires not only data collection, but also a deeper understanding of the emotional component of consumer behavior. An innovative approach to marketing research such as neurointerview has been presented. This approach combines traditional in terviewing methods with advanced computer vision technologies. It al lows to identify and analyze emotional reactions of study participants in real time. Neurointerview provides a unique opportunity to study consumer preferences, as well as their emotional reactions to specific products, services, and marketing messages. During the survey, participants fill out a standard questionnaire, and their facial expressions are recorded by the camera. Emotional reactions can be analyzed in real time, and a dynamic profile of consumer emotions can be compiled. Neurointerview results turn into a journal that records the percentage of subjects showing various emotions, such as joy, surprise, and excitement. This data allows marketers to gain a deeper understanding of consumer behavior and emotional preferences, opening up new opportunities to develop more accurate and effective marketing strategies and products. The results provide precise forecasts of market trends.

1. Svetunkov S.G. Marketing research methods. St. Petersburg: DNK; 2003. 346 p. (In Russian).

2. Mikhailova O.P. From the experience of using traditional marketing research tools in industrial and technical products market. Bulletin of OSU. 2006;8:240–245. (In Russian).

3. Magerramov I.M., Akperov G.I. Solving Internet marketing problems via Python. Proceedings in Cybernetics. 2022;1(45):29–37. (In Russian). https://doi.org/10.34822/1999-7604-2022-1-29-37

4. Lagunova D.O., Safonova A.S. Social media monitoring and social media listening as marketing research tools. In: SPbPU Science Week: Proceedings of Scientific Conference with international participation, St. Petersburg, November 19–24, 2018. St. Petersburg: Peter the Great St. Petersburg Polytechnic University; 2019. (In Russian).

5. Akgaev A.J., Akgayeva M.J., Charymyradov N., Urazmetov H. Research of the influence of innovative technologies on the effectiveness of digital marketing strategies. Vsemirnyi uchenyi. 2024;24. (In Russian).

6. Volodko V.F. Innovative Models of Enterprise Marketing Activity. Science & Technique. 2020;2:130–138. (In Russian). https://doi.org/10.21122/2227-1031-2020-19-2-130-138

7. Omer A. Review of Internet marketing activities: affiliate marketing and retargeting. Polites: Milan Polytechnic Institute; 2014. (In Russian).

8. Bogdanov A.L., Dulya I.S. Sentiment analysis of short Russian texts in social media. Tomsk State University Journal of Eco nomics. 2019;47:220–241. (In Russian).

9. Zheliznyk M.N. Online Focus-Groups: Methodical Reflection. Interaction. Interview. Interpretation. 2023;2:51–71. (In Rus sian). https://doi.org/10.19181/inter.2023.15.2.3

10. Grudanova A.A., Grudanov N.A. Overview of online survey tools for information support of marketing research. StudNet. 2021;7:1814–1829. (In Russian).

11. Alexandrova I.Yu. Methodology of a marketing research of Internet users. E-Management. 2019;1:7–18. (In Russian). https://doi.org/10.26425/2658-3445-2019-1-7-18

12. Shishkina D.R. UGC content as an effective tool for brand promotion in market. Vladimir: Vladimir State University named after Alexander and Nikolai Stoletovs; 2023. (In Russian).

13. Nefedov M.S., Semenova O.A. Chatbots in marketing: functions, roles, opportunities. In: Management, Education, Econom ics: Challenges and Prospects: Proceedings of the All-Russian Scientific and Practical Conference. Saransk: M.E. Evseviev Mordovian State Pedagogical Institute; 2019. Pp. 89–93. (In Russian).

14. Shin S. Research on the use of artificial intelligence in interviews. Natural sciences of a general nature. 2022;1. (In Russian).

15. Shukla D., Kumari R., Bhargavi A. R Human Face Detection and Emotion Recognition Using OpenCV through AI. In: Internet of Everything, Microwave, Embedded, Communication and Networks (IEMECON): Proceedings of 12th International Conference. 2024. http://dx.doi.org/10.1109/IEMECON62401.2024.10845980

16. Willman J.M. Creating GUIs with Qt Designer. In: Beginning PyQt. Springer. 2022.

17. Scherer K.R., Ellgring H., Dieckmann A., Unfried M., Mortillaro M. Dynamic Facial Expression of Emotion and Observer In ference. Frontiers in Psychology. 2019. https://doi.org/10.3389/FPSYG.2019.00508