Case Study
A predictive click-propensity model, trained on historical CRM data, customer interactions, and product KPIs, made it possible to identify the customers most likely to click on an offer and subsequently purchase a specific insurance product. Through the integration of data analytics and machine learning, the solution identifies the most relevant audience segments to target.
The GenAI component uses an LLM (Gemini 2.5) to analyze the textual content of campaign emails, extracting key semantic KPIs, such as offer value, urgency, clarity, visual structure, and tone of voice, and evaluating their impact on campaign performance. The solution also supports the creation of new emails with content and structures designed to have a greater impact on the target audience.
+25-35% click-through rate improvement on target segments-generated content
+12-20% conversion-rate growth in campaigns using AI
Impacts
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TEMA – Accurate Mapping and Forecasting for Emergency Management
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ARIEN: an AI platform to support the fight against illegal drug trafficking
A holistic approach based on artificial intelligence tools for monitoring the production and illegal trafficking of drugs.
QLMD: Quantum Computing for an efficient urban logistical ecosystem
Applying Quantum Computing to urban logistics to optimize routes, reduce costs and emissions, improve sustainability, and tackle complex problems with scalable solutions.
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