International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 8 Issue 3
May-June 2026
Indexing Partners
A Structured Large Language Model Approach to Market Intelligence and Creative Content Generation
| Author(s) | Mrs. Rajitha V, Ms. Kavyashree K L |
|---|---|
| Country | India |
| Abstract | The rapid growth of mobile applications and Direct-to-Consumer (D2C) marketing systems has created large and varied datasets spread across many digital platforms. Marketing analysts and product strategists face ongoing challenges when trying to extract structured and usable insights from these complex and unstructured sources. This paper introduces an AI-powered Cross-Platform Market Intelligence System that uses a Structured Output Approach for strategic synthesis with Google Gemini 2.5 Flash. The framework combines data ingestion, preprocessing, and insight generation through Large Language Models (LLMs), merging data from the Google Play Store (Kaggle dataset), Apple App Store (through RapidAPI), and synthetic D2C campaign datasets to create a unified intelligence layer. By utilizing Gemini’s structured reasoning skills, the system delivers machine-validated insights with confidence scores and offers data-driven marketing recommendations. It also automates the creation of marketing materials, such as advertisement headlines, SEO meta descriptions, and product content, while analyzing D2C funnel metrics like Cost per Acquisition (CAC) and Return on Ad Spend (ROAS). Experimental results show a 70% reduction in manual analytical time, demonstrating the system’s scalability, clarity, and contribution to progress in Generative AI and Intelligent Automation for Industry. This work lays the groundwork for incorporating Generative AI into clear business intelligence processes. |
| Keywords | Artificial Intelligence, Structured Insights, Creative Content, Google Gemini 2.5 Flash. |
| Field | Computer Applications |
| Published In | Volume 8, Issue 3, May-June 2026 |
| Published On | 2026-05-26 |
| DOI | https://doi.org/10.36948/ijfmr.2026.v08i03.79586 |
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E-ISSN 2582-2160
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