Core Insights - The article emphasizes the transformative potential of AI tools like ChatGPT and Perplexity in conducting deep research, significantly reducing the time required for GTM (Go-To-Market) projects from hours to minutes [2][3]. Group 1: AI Functionality and Use Cases - Deep research is highlighted as a groundbreaking AI feature that can handle complex non-engineering tasks from planning to high-quality output generation [2]. - Despite its capabilities, the adoption of deep research tools is lower than expected, partly due to the term "research" which may deter broader usage beyond academics and investors [2][3]. - The article aims to showcase real GTM use cases to inspire creative applications of deep research tools [3]. Group 2: Best Practices for Effective Research - The quality of output from deep research tools heavily relies on the sources used; AI often misjudges the credibility of sources, leading to potential inaccuracies [3][4]. - Recommendations include specifying preferred source types in prompts and creating high-quality source lists to enhance research outcomes [4][5]. - Providing context is crucial for tailored insights; users should share relevant background information to avoid generic outputs [6][7][8]. Group 3: Structuring Research Requests - Users are encouraged to clarify their research goals and the specific context of their requests to achieve more impactful results [8][9]. - Establishing a project context can streamline future research requests, reducing the need to repeat background information [10]. - Asking for a research plan before the AI begins can help align expectations and methodologies [13][16]. Group 4: Tool Comparisons and Recommendations - ChatGPT is identified as the best general-purpose deep research tool, especially after the release of GPT-5 and Agent Mode, which enhances its capabilities [24][26]. - Gemini is noted as a strong alternative with fewer usage restrictions, while Perplexity excels in specific website-focused research [26][24]. - The article provides various use cases for deep research, including competitor analysis, marketing attribution models, and international market assessments [25][41].