How to Use Google NotebookLM for AI-Driven Social Listening and Monitoring
Introduction
Artificial intelligence has rapidly transformed how marketing professionals monitor public sentiment and brand reputation. On 18 October 2024, the School of Professional Education and Executive Development (PolyU SPEED) invited Jansen Lu, a Hong Kong–based social media strategist now based in Taipei, to share his practical experience using Google’s NotebookLM for AI-driven social listening and crisis monitoring.
Led by course leader Dr. Ken Fong, the session demonstrated how NotebookLM — powered by Google Gemini 1.5 Pro — enables marketers to integrate multiple information sources, analyze feedback trends, and summarize actionable insights efficiently within one workspace. The lecture served as both a live demonstration and a hands-on exploration of how AI reshapes brand monitoring, communication, and data-driven storytelling.
The Evolution of Social Listening
Traditional social listening often requires manually tracking comments, compiling reports, and interpreting emotional tone across multiple platforms. This approach is slow and fragmented. Jansen explained that NotebookLM elevates the process by combining AI summarization, source grounding, and audio narrative synthesis. Instead of replacing human judgment, it provides analytical structure, contextual understanding, and traceable evidence.
He emphasized: “Curation is the key when using NotebookLM — never surrender the process of thinking to Gen AI.” His point underscored that NotebookLM is not meant to decide for marketers but to reveal the insights that inform better decisions. This distinction—between automation and augmentation—set the tone for the entire workshop.
Why NotebookLM Excels for Social Listening
NotebookLM is an AI-powered research and writing assistant designed to ground every output in user-provided sources. It is built on Google Gemini 1.5 Pro, which enables long-context comprehension and multimodal processing. Jansen introduced five key features that make it uniquely valuable for marketers and analysts.
- 1. Flexible Source Upload — Import PDFs, audio, Google Docs, YouTube videos, or Google Drive files directly into a Notebook.
- 2. Smart Context Understanding — Identify patterns, contradictions, and sentiment across diverse media types.
- 3. Conversational Analysis — Engage in dialogue with your research materials, request summaries, or generate structured comparison tables.
- 4. Podcast-Style Audio Overview — Generate customisable spoken briefings that narrate key insights and sentiment changes.
- 5. Minimal Hallucination — Every answer cites its source ([S#]) for transparency and credibility.
These capabilities allow NotebookLM to consolidate fragmented data into cohesive, evidence-based narratives. For marketing professionals, this translates to faster, more accurate reporting and actionable intelligence during brand crises.
Practical Use Cases Shown in the Workshop
Case 1 — Phú Quốc Island Dating Tour Incident（富國島交友團事件）
This real-world case involved a Vietnamese travel agency’s “dating tour” that sparked complaints about hygiene and refund issues. Jansen imported a combination of news reports, participant posts, YouTube interviews, and official statements into NotebookLM. He then used a series of precise prompts to extract meaningful patterns:
- “List all complaints and corresponding official responses in a table.”
- “Identify which issues were addressed or left unresolved.”
- “Extract the most frequent terms such as ‘not as advertised,’ ‘hygiene problem,’ ‘refund dispute.’”
NotebookLM generated a clear comparison table that mapped allegations against company responses, while the Audio Overview narrated the emotional timeline of the event. Students were able to visualise when the controversy peaked and which responses failed to resolve tension. This example illustrated how AI could transform hours of manual reading into a coherent, source-based insight map within minutes.
Case 2 — Retail Giveaway Backlash: McDonald’s × Hunter × Hunter Collaboration（麥當勞 × 獵人 聯名贈品風波）
Jansen’s second case study focused on a Taiwan McDonald’s campaign promoting limited-edition Hunter × Hunter collectibles. The promotion backfired when early influencer recipients triggered frustration among loyal fans who felt excluded. Jansen collected social posts, online news, and comment screenshots, then demonstrated how to structure an AI-driven sentiment analysis workflow inside NotebookLM.
- “Categorize comments into supportive, critical, or neutral groups.”
- “Map stakeholder reactions (brand, influencers, consumers).”
- “Generate a 90-second Audio Overview summarizing sentiment trends.”
The AI produced a mind map of stakeholder reactions and a concise podcast-style narration summarizing the controversy. The result showed how negative sentiment accelerated once influencer content surfaced, and how the brand’s delayed response prolonged backlash. This exercise reinforced the potential of NotebookLM as a real-time reputation management tool that blends qualitative insight with narrative clarity.
Case 3 — KOL Reaction Tracking on AI in Marketing (mentioned but not demonstrated)
While Jansen did not present this case live, he briefly described how NotebookLM could be used to track opinion leaders’ changing attitudes toward AI tools in marketing. Such longitudinal studies could reveal how KOL sentiment shifts from skepticism to adoption, offering brands early indicators of trend acceptance. It remains a powerful example of how the same analytical framework extends beyond crisis management into strategic foresight.
Extending Social Listening to Strategy and Content
Jansen also discussed how social listening insights can evolve into proactive strategy development. By combining NotebookLM with search-intent data, marketers can identify content gaps, trending concerns, and emerging opportunities. Prompts such as “Suggest five content pillars based on current social buzz around AI marketing” enable the creation of editorial calendars and FAQ materials rooted in real user sentiment.
He highlighted that NotebookLM’s structured understanding helps teams transition seamlessly from monitoring to messaging — turning insights into communication strategies, campaign ideas, and knowledge-sharing assets. In doing so, social intelligence becomes an engine for content innovation, not just crisis prevention.
Insight — 2025 Perspective
The PolyU SPEED workshop revealed more than a new AI tool — it represented a shift in how marketing education connects research, analysis, and storytelling. NotebookLM is evolving from a static notetaker into an AI-powered thinking partner that integrates the entire process: observation → interpretation → narration → action.
From the Phú Quốc tour incident to the McDonald’s promotional backlash, the live cases demonstrated how structured AI analysis enables marketers to respond faster and with greater confidence. In 2025, NotebookLM’s enhanced multimodal reasoning and collaboration within Google Workspace will likely make such workflows standard practice across communication teams.
Since 2024, NotebookLM has evolved from a note-taking assistant to a social-intelligence studio. For marketing and PR professionals, this marks the moment when AI monitoring truly becomes strategic decision support.
Traditional Chinese Summary（繁體中文摘要）
2024 年 10 月 18 日，香港理工大學專業進修學院（PolyU SPEED）「AI-Driven Digital and Social Media Marketing 專業證書課程」邀請社交媒體專家 Jansen Lu 擔任嘉賓講者，由課程統籌 Dr. Ken FONG 主持。Jansen 以實際示範展示 Google NotebookLM 在 AI 社群監測與危機分析上的應用。
NotebookLM 由 Google Gemini 1.5 Pro 驅動，可上傳 PDF、音訊、YouTube 影片及 Google Drive 資料，系統以引用（[S#]）方式生成摘要，並提供「Podcast 式 Audio Overview」。這種「引用為本」的分析方式，讓使用者能追蹤每個洞察的來源，提升決策透明度。
案例一：富國島交友團事件 — Jansen 將新聞報導、參加者留言及主辦方回應匯入 NotebookLM，並以提示指令「列出指控與對應回應」、「分析未解決項目」、「統計常見字詞如『不符宣傳』『衞生問題』『退款糾紛』」。系統自動生成表格與 Audio Overview，協助了解情緒高峰及品牌回應的效果。
案例二：麥當勞 × 獵人 聯名贈品風波 — 以台灣 McDonald’s 推出的動漫贈品活動為例，Jansen 匯入社群貼文、媒體報導與留言截圖，要求 NotebookLM「分類情緒」、「繪製利害關係人地圖」、「生成 90 秒 Audio Overview」，結果生成思維導圖與語音摘要，快速呈現輿論變化。
案例三：KOL 對 AI 行銷的反應追蹤（僅提及，未示範） — 說明 NotebookLM 可應用於長期追蹤意見領袖對 AI 工具的態度演變，協助品牌提前掌握趨勢。
除了社群監測外，Jansen 亦指出 NotebookLM 可用於內容規劃與 SEO 研究，幫助行銷人員從「監測」走向「策略」。2025 年版本更加入 Video Overview 與多模態協作功能，讓用戶能在單一平台完成「蒐集 → 分析 → 敘事 → 行動」全流程。
自 2024 以來，NotebookLM 已從筆記工具進化為社群智慧工作室。對行銷與公關專業而言，這是 AI 監測走向策略決策的關鍵轉折點。
Author
— Dr. Ken FONG
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