Öz
Günümüz dijital reklamcılığı, markalar ve tüketiciler arasındaki etkileşimleri kökten dönüştürmektedir. Geleneksel kitle iletişiminin ötesine geçerek, büyük veri analizi, yapay zeka (YZ) ve davranışsal psikolojiyi entegre eden yeni bir yaklaşım olan "duygusal gıdıklama" kavramı bu çalışmada incelenmektedir. Duygusal gıdıklama, tüketicinin bilinçaltındaki anlık dürtüleri ve gizli arzularını hedef alarak, neredeyse içgüdüsel bir tepki yaratmayı amaçlar. Bu, geleneksel duygusal reklamlardan farklı olarak, anlık, mikro düzeyde ve çoğu zaman bilinçdışı bir etkiyi hedefler; adeta kişisel bir fısıltı gibi, tüketicinin o anki ruh haline veya mevcut bir ihtiyacına hassasça dokunur. Makale, bu stratejilerin temelini oluşturan mikro-hedefleme yetenekleri ve algoritmaların kritik rolünü ele almaktadır. Dijital ayak izlerinin metalaştırılması sayesinde algoritmalar, tüketicilerin demografik özelliklerinin ötesinde, anlık ruh halleri ve "gizli" arzuları hakkında eşi benzeri görülmemiş içgörüler sunar. Bu, reklamların belirli bir zamanda, belirli bir bireyin en hassas duygusal noktasına dokunabilmesini sağlar. Nöro-pazarlama ve davranışsal psikoloji alanlarındaki bulgular, bu stratejilerin bilimsel temelini güçlendirerek, görsel, işitsel ve metinsel gizli tetikleyicilerle beynin ödül mekanizmalarının nasıl harekete geçirildiğini açıklar. Kahneman'ın Sistem 1 düşüncesiyle uyumlu olarak, bu reklamlar mantıksal süzgeçten geçmeden doğrudan sezgisel ve dürtüsel tepkileri tetiklemeyi amaçlar. "Duygusal gıdıklama"nın tüketici davranışları üzerindeki etkileri, dürtüsel satın alma artışı ve marka etkileşiminin güçlenmesi gibi olumlu sonuçlar doğururken, aşırı kişiselleştirme, reklam yorgunluğu ve mahremiyet endişeleri gibi ciddi etik sorunları da beraberinde getirmektedir. Bu durum, algoritmik şeffaflık ve tüketici veri haklarına ilişkin daha güçlü yasal düzenlemelerin önemini vurgular. Çalışma, gelecekteki araştırmalar için ampirik doğrulama, uzun vadeli psikolojik etkiler, etik çerçeveler ve tüketici direnci mekanizmaları gibi çeşitli yönelimler sunmaktadır. "Duygusal gıdıklama", dijital reklamcılığın geleceğini şekillendiren, insan ve makine etkileşimindeki yeni bir dönüm noktası olarak değerlendirilmektedir.
Anahtar Kelimeler
duygusal gıdıklama dijital reklamcılık bilinçaltı pazarlama mikro-hedefleme
Kaynakça
- Aguirre, E., & Mahr, D. (2015). Over personalization in mobile environments: Managing consumer privacy concerns. Journal of Retailing, 91(4), 671-685.
- Bernays, E. L. (1928). Kamuoyunun mühendisliği (propaganda). New York: Horace Liveright.
- Berry, L. L. (1995). Relationship marketing of services: Growing interest, emerging perspectives. Journal of the Academy of Marketing Science, 23(4), 236-245.
- Chen, H. (2017). Big data analytics and marketing intelligence. Journal of Management Information Systems, 34(3), 48-52.
- Cialdini, R. B. (2009). Influence: The psychology of persuasion. New York: HarperCollins.
- Damasio, A. R. (1994). Descartes’ error: Emotion, reason, and the human brain. New York: G. P. Putnam’s Sons.
- Dooley, R. (2019). Neuromarketing 2.0: Marketing your brain. New York: Wiley.
- Floridi, L., & Cowls, J. (2018). Ethical principles in the design of AI. AI & Society, 33(4), 701-707.
- Godin, S. (1999). Permission marketing: Turning strangers into friends and friends into customers. New York: Simon & Schuster.
- Goodfellow, I., & Bengio, Y. (2016). Deep learning. Cambridge: MIT Press.
- Humbry, C. (2006). The value of information: Big data and information technologies. International Journal of Information Management, 31(1), 1-5.
- Iyengar, S. S., & Lepper, M. (2000). When choice is demotivating: Can one desire too much of a good thing? Journal of Personality and Social Psychology, 79(6), 995-1006.
- Jaime E. Sidani, & Carroll, M. (2017). Social media use and perceived social isolation in young adults in the US: An association study. American Journal of Preventive Medicine, 53(1), 1037-1044.
- Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus and Giroux.
- Kohavi, R., & Tang, D. (2014). Trustworthy online controlled experiments: A practical guide to A/B testing. Cambridge: Cambridge University Press.
- Kreiss, D. (2016). Prototype politics: The making of an algorithmic society. New York: Oxford University Press.
- Mangold, W. G., & Faulds, D. (2009). Social media: The new hybrid element of the promotion mix. Business Horizons, 52(4), 357-365.
- Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370-396.
- Morin, C. (2011). Neuromarketing: The new science of consumer behavior. Research Technology Management, 54(6), 2-4.
- Nunes, J. C., & Drèze, X. (2017). Manipulation in marketing: The limits of ethics. Harvard Business Review, 95(3), 12-14.
- Ogilvy, D. (1983). Bir reklamcının itirafları. New York: Vintage Books.
- O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. New York: Crown.
- Pariser, E. (2011). The filter bubble: What the internet Is hiding from you. New York: Penguin Press.
- Pham, M. T. (1998). The role of emotion in consumer decision making: A perspective. Advances in Consumer Research, 25(1), 147-153.
- Picard, R. W. (1997). Affective computing. Cambridge: MIT Press.
- Potter, W. J. (2013). Media literacy. California: Sage Publications.
- Primack, B. A., & Carroll, M. (2017). Social media use and perceived social isolation in young adults in the US: An association study. American Journal of Preventive Medicine, 53(1), 1037-1044.
- Ramachandran, V. S., & Blakeslee, S. (1998). Phantoms in the brain: Probing the mysteries of the human mind. New York: William Morrow.
- Renvoisé, P., & Morin, C. (2007). Neuromarketing: Understanding the buy button in your customer’s brain. New York: HarperCollins.
- Rook, D. W., & Gardner, M. (1993). In the mood: Impulse buying’s affective foundations. Journal of Consumer Research, 20(1), 12-25.
- Russell, S. J., & Norvig, P. (2010). Artificial intelligence: A modern approach. New Jersey: Prentice Hall.
- Rust, R. T., & Verhoef, P. (2005). The future of customer-Centric marketing. Journal of Marketing, 69(4), 119-125.
- Siegel, D. R. (2016). Predictive analytics: The power to predict who will click, buy, lie, or die. New York: Wiley.
- Thaler, R. H., & Sunstein, C. (2008). Nudge: Improving decisions about health, wealth, and happiness. New Haven: Yale University Press.
- Turow, J. (2011). The daily you: How the new advertising industry is defining your identity and your worth. New Haven: Yale University Press.
- Union, E. (2016). General data protection regulation. Luxemburg: Publications Office of the European Union.
- Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. New York: PublicAffairs.
Emotional Tickling: Micro-Triggering the Consumer Subconscious in New-Generation Digital Advertisements
Öz
Today's digital advertising ecosystem is fundamentally transforming the nature of interaction between brands and consumers. Moving beyond traditional mass communication, this study examines the concept of "emotional tickling," an emerging approach integrating big data analytics, artificial intelligence (AI), and behavioral psychology to target consumers' subconscious, instantaneous impulses. Unlike conventional emotional advertising, emotional tickling aims for an immediate, micro-level, and often unconscious response. It subtly touches upon the consumer's current mood or hidden need, much like a whispered suggestion from a friend, evoking an almost instinctive reaction. The article details the critical role of micro-targeting capabilities and algorithms that form the foundation of these "emotional tickling" strategies. Through the commodification of digital footprints, algorithms provide unprecedented insights into consumers' real-time emotional states and latent desires, extending beyond mere demographic data. This precision allows advertisements to pinpoint and engage with an individual's most sensitive emotional triggers at precise moments. Findings from neuro-marketing and behavioral psychology reinforce the scientific basis of these strategies, explaining how visual, auditory, and textual subliminal cues activate the brain's reward mechanisms. Consistent with Kahneman's System 1 thinking, these ads aim to elicit intuitive and impulsive responses without conscious logical processing. While "emotional tickling" strategies can lead to positive outcomes like increased impulse purchases and stronger brand engagement, they also raise significant ethical concerns, including over-personalization, ad fatigue, and privacy anxieties. This underscores the importance of greater algorithmic transparency and robust legal regulations concerning consumer data rights. The study suggests future research directions, such as empirical validation, long-term psychological impacts, ethical frameworks, cultural differences, and consumer resistance mechanisms. Ultimately, "emotional tickling" is viewed not just as a marketing trend, but as a pivotal development in human-machine interaction, shaping the future of digital advertising.
Anahtar Kelimeler
emotional tickling digital advertising subconscious marketing micro-targeting
Kaynakça
- Aguirre, E., & Mahr, D. (2015). Over personalization in mobile environments: Managing consumer privacy concerns. Journal of Retailing, 91(4), 671-685.
- Bernays, E. L. (1928). Kamuoyunun mühendisliği (propaganda). New York: Horace Liveright.
- Berry, L. L. (1995). Relationship marketing of services: Growing interest, emerging perspectives. Journal of the Academy of Marketing Science, 23(4), 236-245.
- Chen, H. (2017). Big data analytics and marketing intelligence. Journal of Management Information Systems, 34(3), 48-52.
- Cialdini, R. B. (2009). Influence: The psychology of persuasion. New York: HarperCollins.
- Damasio, A. R. (1994). Descartes’ error: Emotion, reason, and the human brain. New York: G. P. Putnam’s Sons.
- Dooley, R. (2019). Neuromarketing 2.0: Marketing your brain. New York: Wiley.
- Floridi, L., & Cowls, J. (2018). Ethical principles in the design of AI. AI & Society, 33(4), 701-707.
- Godin, S. (1999). Permission marketing: Turning strangers into friends and friends into customers. New York: Simon & Schuster.
- Goodfellow, I., & Bengio, Y. (2016). Deep learning. Cambridge: MIT Press.
- Humbry, C. (2006). The value of information: Big data and information technologies. International Journal of Information Management, 31(1), 1-5.
- Iyengar, S. S., & Lepper, M. (2000). When choice is demotivating: Can one desire too much of a good thing? Journal of Personality and Social Psychology, 79(6), 995-1006.
- Jaime E. Sidani, & Carroll, M. (2017). Social media use and perceived social isolation in young adults in the US: An association study. American Journal of Preventive Medicine, 53(1), 1037-1044.
- Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus and Giroux.
- Kohavi, R., & Tang, D. (2014). Trustworthy online controlled experiments: A practical guide to A/B testing. Cambridge: Cambridge University Press.
- Kreiss, D. (2016). Prototype politics: The making of an algorithmic society. New York: Oxford University Press.
- Mangold, W. G., & Faulds, D. (2009). Social media: The new hybrid element of the promotion mix. Business Horizons, 52(4), 357-365.
- Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370-396.
- Morin, C. (2011). Neuromarketing: The new science of consumer behavior. Research Technology Management, 54(6), 2-4.
- Nunes, J. C., & Drèze, X. (2017). Manipulation in marketing: The limits of ethics. Harvard Business Review, 95(3), 12-14.
- Ogilvy, D. (1983). Bir reklamcının itirafları. New York: Vintage Books.
- O’Neil, C. (2016). Weapons of math destruction: How big data increases inequality and threatens democracy. New York: Crown.
- Pariser, E. (2011). The filter bubble: What the internet Is hiding from you. New York: Penguin Press.
- Pham, M. T. (1998). The role of emotion in consumer decision making: A perspective. Advances in Consumer Research, 25(1), 147-153.
- Picard, R. W. (1997). Affective computing. Cambridge: MIT Press.
- Potter, W. J. (2013). Media literacy. California: Sage Publications.
- Primack, B. A., & Carroll, M. (2017). Social media use and perceived social isolation in young adults in the US: An association study. American Journal of Preventive Medicine, 53(1), 1037-1044.
- Ramachandran, V. S., & Blakeslee, S. (1998). Phantoms in the brain: Probing the mysteries of the human mind. New York: William Morrow.
- Renvoisé, P., & Morin, C. (2007). Neuromarketing: Understanding the buy button in your customer’s brain. New York: HarperCollins.
- Rook, D. W., & Gardner, M. (1993). In the mood: Impulse buying’s affective foundations. Journal of Consumer Research, 20(1), 12-25.
- Russell, S. J., & Norvig, P. (2010). Artificial intelligence: A modern approach. New Jersey: Prentice Hall.
- Rust, R. T., & Verhoef, P. (2005). The future of customer-Centric marketing. Journal of Marketing, 69(4), 119-125.
- Siegel, D. R. (2016). Predictive analytics: The power to predict who will click, buy, lie, or die. New York: Wiley.
- Thaler, R. H., & Sunstein, C. (2008). Nudge: Improving decisions about health, wealth, and happiness. New Haven: Yale University Press.
- Turow, J. (2011). The daily you: How the new advertising industry is defining your identity and your worth. New Haven: Yale University Press.
- Union, E. (2016). General data protection regulation. Luxemburg: Publications Office of the European Union.
- Zuboff, S. (2019). The age of surveillance capitalism: The fight for a human future at the new frontier of power. New York: PublicAffairs.
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Konular | Bilim ve Teknoloji Sosyolojisi ve Sosyal Bilimler, İletişim Sosyolojisi |
| Bölüm | Derleme |
| Yazarlar | |
| Gönderilme Tarihi | 8 Haziran 2025 |
| Kabul Tarihi | 1 Ekim 2025 |
| Yayımlanma Tarihi | 31 Aralık 2025 |
| Yayımlandığı Sayı | Yıl 2025 Cilt: 9 Sayı: 2 |