Hey everyone! I'm super excited to share how I've been using NotebookLM to get ready for customer discovery calls. As someone who's still pretty new to data analytics, I often need to synthesize a ton of information from different sources before I can ask good questions, and this tool has been a game-changer for me.
Here’s my basic workflow for prepping a 30-minute call:
* First, I create a new notebook and add all my source material. This usually includes:
* The potential customer's website (especially their product/blog pages).
* Any public financial reports or news articles about them.
* Notes from previous chats or emails with the contact.
* My own internal "cheat sheet" of questions and value propositions.
* Then, I let NotebookLM summarize everything and start asking it questions like:
* "Based on these sources, what are this company's main business challenges?"
* "Can you list any potential data-related pain points they might have?"
* "Generate 5-10 open-ended questions tailored to this company's industry."
The best part is the "cite sources" feature. When it gives me an insight, I can see exactly which document it came from, which helps me feel way more confident. It’s like having a super-organized, instant research assistant.
Has anyone else tried using it for similar prep work? I'd love to hear if you have any tips for structuring the source documents or prompts that have worked really well for you. Also, I'm curious if folks have compared this to other methods for organizing qualitative data before analysis.