• Aditi Fadnavis
• Komal Sharma

Fashion retail has increasingly shifted towards digital platforms, necessitating sophisticated marketing approaches. This paper proposes a data-driven methodology for optimizing search marketing campaigns in the fashion retail sector. By analyzing a comprehensive dataset of search keywords, ad performance metrics, and consumer behavior patterns, we developed a systematic approach to campaign structure and keyword optimization. The study achieved a 95% accuracy in keyword relevance prediction and demonstrated a 35% improvement in campaign conversion rates. Data-driven campaign structuring techniques were employed to enhance budget allocation and bidding strategies. The research provides valuable insights for digital marketers in the fashion industry, particularly for optimizing search campaigns across different product categories including menswear, womenswear, and accessories.

Fashion retail, Digital marketing, Search campaign optimization, Deep learning, Keyword analysis, Consumer behavior, Campaign structure, Bid optimization

"Automated Keyword Campaign Generation System for E-commerce", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.b334-b338, November-2024, Available :http://www.jetir.org/papers/JETIR2411142.pdf

"Automated Keyword Campaign Generation System for E-commerce", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. ppb334-b338, November-2024, Available at : http://www.jetir.org/papers/JETIR2411142.pdf