Mémoire-projet

Abstract

In an environment where organisations increasingly rely on data to guide commercial decisions, many still struggle to transform market research into actionable sales intelligence. Despite growing investments in analytics and artificial intelligence, valuable market insights often remain disconnected from daily sales and marketing operations, limiting their impact on lead generation and sales performance. This challenge is particularly pronounced in B2B, technology‑intensive contexts characterised by complex products, long sales cycles, and fragmented information flows. Against this background, this thesis explores how artificial intelligence can be leveraged to bridge the gap between market research and sales intelligence within a strategic framework aimed at supporting lead generation and sales optimisation. The central question addressed is how organisations can structure data, processes, and governance to ensure that market insights are not only produced but effectively translated into operational sales actions. To address this question, the research follows a structured approach, moving from an analysis of the organisational context and existing commercial processes to an examination of the conditions required for AI‑enabled integration between market research and sales intelligence. The study draws on academic literature, external benchmarks, and qualitative organisational insights to identify recurring challenges related to data quality, process fragmentation, governance, and human–AI interaction. The objective of the thesis is not to evaluate a specific technological implementation, but to develop a conceptual and managerial framework that helps organisations understand how AI can be embedded responsibly and effectively into commercial decision‑making processes. By focusing on foundational capabilities rather than isolated tools, the research aims to provide guidance for organisations seeking to strengthen the strategic impact of market research on sales performance.