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Educational Administration: Theory and Practice
2023, 29(4), 4361 - 4374
ISSN: 2148-2403
https://kuey.net/ Research Article
Harnessing AI Neural Networks and Generative AI for
Advanced Customer Engagement: Insights into Loyalty
Programs, Marketing Automation, and Real-Time
Analytics
Harish Kumar Sriram*
*Lead software engineer, hariish.sriram@gmail.com, ORCID ID : 0009-0008-2611-2904
Citation: Harish Kumar Sriram, (2023). Harnessing AI Neural Networks and Generative AI for Advanced Customer Engagement: Insights
into Loyalty Programs, Marketing Automation, and Real-Time Analytics, Educational Administration: Theory and Practice, 29(4) 4361 -
4374
Doi: 10.53555/kuey.v29i4.9264
ARTICLE INFO ABSTRACT
Today, AI and generative AI neural networks can reinforce and enhance customer
engagement strategies. Traditionally, the marketing funnel describes the rigid, one-way
relationship between producers and consumers. More advanced and contemporary
frameworks consider the activity of the consumer as the legitimate beginning of a loop
that will likely return him or her to the start of the buyer's journey several times. Brands
are working with AI to predict the next most relevant advertising, customize subscription
boxes, offer more rewards for more frequent purchases, market seasonal promotions,
define omnichannel strategies, and ascertain when products are running out. This paper
extends current knowledge by promoting the benefit of using AI neural networks for
customer segmentation and generative AI for predicting the preferences of like-minded
consumers.
This essay explores how AI neural networks and generative AI can be used by brands to
augment customer engagement strategies. Our essay aims to demonstrate that modern
loyalty programs, more so than marketing automation, are about cultivating engagement
and loyalty through meaningful, tailored consumer-brand relationships. We describe
how AI neural networks can be used to extract value from unstructured data through
customer segmentation, cognizant that consumer behavior is not subject to such
categorical constraints. We also argue for the use of generative AI to foster superb
customer engagement over conventional loyalty programs, more so than the current
enthusiasm for marketing automation. We highlight the increasing use of AI by
businesses for real-time analytics and business intelligence, emphasizing the value of
these technologies. Offering practical insights, we outline how brand strategists might
seize available and emerging technologies to reframe marketing problems and align
toward necessary organizational change.
Keywords: AI, Generative AI, Neural Networks, Customer Engagement, Marketing
Funnel, Consumer Behavior, Buyer’s Journey, Advertising Prediction, Subscription
Boxes, Loyalty Programs, Marketing Automation, Customer Segmentation,
Omnichannel Strategies, Business Intelligence, Real-Time Analytics, Unstructured Data,
Brand Strategy, Organizational Change, Seasonal Promotions, Consumer Preferences.
1. Introduction
The voracity of digitally savvy users and a massive surge in social media usage have significantly transformed
and revolutionized engagement. Scrolling and sharing happy moments are preferred over long phone calls and
conversations. In light of new norms, digital marketers have adapted channel enhancement through social
platforms. However, users, devices, and technology are dynamic today, transitioning from a static informative
world to a transformative network where data and AI collectively years beyond advertised and feel the best
experiences. AI has made it easier for humans to connect through complex algorithms, big data, customer-
perceivable automation, predictive analytics, and realistic virtual appearances. This channeled technology of
the fourth industrial revolution is driven by the cloud, is collective, and is accessible by small and large players
sparking unprecedented growth in digital engagements.