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In our mission to empower businesses and GTM operation teams with AI-driven insights without the need for advanced data science expertise, Forwrd.AI is excited to unveil one of our most significant updates yet: LLM-powered enrichment and predictor summaries.
Our new feature transforms how businesses analyze data, offering automated categories and detailed explanations for each predictor used in AI models. By simplifying the interpretation process, users can now build smarter, more accurate, and robust predictive models while making better decisions faster.
Forwrd's new feature leverages advanced Large Language Models (LLMs) to enhance the insights generated during the AI modeling process. With every analysis you run in Forwrd.AI, the platform now:
For instance, if "Marketing Emails Sent" falls under Marketing Activity, the system might provide insights such as:
"A higher frequency of marketing emails sent correlates with a 20% higher likelihood of conversion, suggesting a strong link between outreach and customer engagement."
The ability to classify predictors into meaningful categories and enrich them with detailed explanations is a game-changer for businesses. It reduces the cognitive load required to interpret technical outputs, allowing teams to focus on crafting strategies based on clear, actionable insights.
Whether you're analyzing lead scoring, churn prediction, or customer segmentation, these categories help you quickly identify key factors that drive success. For example, understanding how Engagement influences churn or how Firmographics relate to your ICP can lead to more targeted and impactful actions.