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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM28192
Volume:
8 |
1 |
Jan 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
The role of artificial intelligence (AI) in marketing technology has forever changed the way enterprises interact with customers, shape campaigns, and create experiences across channels. In contrast, traditional marketing automation solutions were based on rule-based segmentation, static workflows, and batch execution of campaigns, which made for efficient processes but lacked two-way customer observation or adaptability to real-time behaviours. However, with changing customer demands for greater personalization and more timely, contextual interactions, the shortcomings of legacy systems are becoming increasingly pronounced. This Research addresses the evolution of marketing automation as an AIdriven, scenario-based technology that functions as a sophisticated customer-engagement and execution platform, founded on a journey-orchestration engine complementing Adobe Campaign, embedded on scalable cloud platforms. It has been reinventing next-gen marketing automation. Learn how the marketing teams are using AI algorithms, predictive analytics, and machine learning to power a change in their campaign design. With AI in Adobe Campaign’s orchestration layer, organizations can segment audiences on the fly and automatically predict next-best actions, as well as autonomously adjust marketing journeys in real-time. Cloud infrastructure enables even greater scalability, elasticity, and data processing power, allowing for the real-time orchestration of global enterprises with millions of customer profiles. The model also uses AIpowered segmentation models to cluster heterogeneous customer bases, machine learning classifiers to predict purchase propensity, and reinforcement learning agents for journey optimization. It is orchestrated with Adobe Sensei AI and the big data architecture of Adobe Experience Platform, driving contextual relevance across email, mobile, web, and social channels. This research methodologically utilizes both simulation and case-study analysis of an enterprise-scale campaign. We build data pipelines to connect our CRM, contextual, and behavioural datasets directly within the cloud-hosted Adobe Campaign instances. Historical and real-time data trains AI models using AI orchestration rules written as API-driven cloud microservices. It is gauged by engagement uplift, conversion boost, latency decrease, and operational efficiency metrics. The experimental evaluation results showed significant gains, with interaction rates increasing by 34% due to predictive personalization, sales gaining an uplift of 27% through reinforcement learning-based recommendations, and campaign execution costs reduced by approximately. 40% via automation of the previously manual workflows. The findings can also highlight three important contributions. AI-powered orchestration enables marketers to focus on strategic endeavours rather than managing segmented campaigns. Next, having Adobe Campaign on the cloud enables organizations to benefit from its built-in resiliency, elasticity, and global scale, allowing them to respond quickly to customer needs from their locations. The third enables explainable AI under orchestration to ensure ethical alignment with regulatory frameworks, such as GDPR and CCPA, which directly address the most emergent concerns around transparency and trust in AIdriven marketing. We provide a reference architecture, methodological guidelines, and performance benchmarks for rearchitecting marketing automation, informing both academic research and industry practice. This highlights the significant transformative potential of AI and cloudnative deployment in orchestrating end-to-end journeys that are not only automated but also adaptive, contextaware, and customer-centric. Combining predictive intelligence with prescriptive decision-making, alongside cloud services open to tens of millions of users, can provide agencies with best-in-class customer experiences and allocable resources. Forrester offered two ways in which the approach may transform Adobe Campaign, with its AIenabled and cloud-based deployment capabilities, into a key anchor of modern marketing ecosystems.
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Publication Date
1/28/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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