What is ADintel?
ADintel offers a comprehensive AI-driven solution designed to enhance the entire marketing research process. By leveraging Generative AI, the platform helps businesses gather profound customer insights through improved planning, execution, and analysis of research activities. It aims to transform raw customer feedback into actionable business intelligence, enabling companies to make more informed strategic decisions.
The platform integrates three key AI components: AI Consultant for research planning, AI Moderator for conducting dynamic customer interviews, and AI Analyst for deciphering qualitative data. These components work together seamlessly, utilising techniques like domain-specific instruction tuning, human-aligned fine-tuning (RLHF), and retrieval-augmented generation to ensure precision, adaptability, and depth in uncovering customer sentiments, needs, and perceptions.
Features
- AI Consultant: Assists in defining research objectives, crafting interview questions, and developing effective research plans.
- AI Moderator: Conducts dynamic, human-like customer interviews combining structured surveys and in-depth discussions, adapting follow-up questions based on responses.
- AI Analyst: Performs semantic analysis on qualitative data, identifies patterns, sentiments, and trends, and generates actionable recommendations.
- Contextual Customization: Integrates brand assets (product info, messaging) for consistent brand voice during interviews.
- Domain-Specific AI Training: Utilizes LLMs trained on marketing journals, industry reports, and research studies for specialized knowledge.
- Human-Aligned Fine-Tuning (RLHF): Ensures AI interaction aligns with human values and preferences for better user experience.
- Retrieval Augmented Generation (RAG): Accesses external databases for up-to-date market insights and deeper reasoning.
- Test-Run Feature: Allows review of research plans before launching.
- Template Saving: Enables saving perfected research plans for future use.
Use Cases
- Streamlining marketing research planning for new product development.
- Conducting effective customer interviews to gauge customer satisfaction.
- Analyzing qualitative data to understand brand perception among consumers.
- Identifying new market opportunities through customer insights.
- Optimizing marketing campaigns based on customer feedback analysis.
- Refining brand identities and product strategies.
