Background of the Study
In recent years, artificial intelligence (AI) has gained significant traction as a tool for enhancing marketing efforts. By leveraging AI, companies can automate and optimize various marketing processes, leading to improved customer targeting, personalized campaigns, and better decision-making (Sharma & Singh, 2024). AI-driven marketing automation tools allow businesses to analyze consumer behavior, segment markets more effectively, and deliver tailored messaging through platforms such as email, social media, and digital ads. These technologies are essential for businesses that wish to scale their operations while maintaining effective customer engagement.
Konga, one of Nigeria’s leading e-commerce platforms, has incorporated AI into its marketing efforts to automate customer interactions and improve operational efficiency. In Jigawa State, where e-commerce adoption is growing, Konga’s use of AI in marketing automation could significantly enhance its customer experience, improve conversion rates, and increase brand loyalty. This study aims to assess the effectiveness of AI-based marketing automation in driving business growth and consumer engagement for Konga in Jigawa State.
Statement of the Problem
While AI and marketing automation are increasingly popular, their effectiveness in specific regional markets such as Jigawa State remains under-explored. Despite the promise of AI-driven tools in enhancing marketing efficiency, many businesses, including Konga, face challenges in maximizing the impact of AI technologies, especially in emerging markets with distinct consumer behaviors (Olusola & Okoro, 2023). This study will investigate the extent to which Konga’s use of AI in marketing automation impacts its business performance in Jigawa State.
Objectives of the Study
Research Questions
Research Hypotheses
Scope and Limitations of the Study
This study focuses on Konga’s use of AI-driven marketing automation in Jigawa State. Limitations include potential challenges in measuring AI’s impact on long-term consumer behavior and reliance on secondary data sources.
Definitions of Terms
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