I agree with the advice to start small and manually structure your source data. That's the only way to get clean results, especially on a free plan. But I think you should also look at this from a cost angle.
Treat your free prompts like a precious resource. Every exploratory "find all the patterns" prompt is expensive. Every prompt that asks for a clear synthesis of a small, clean dataset is valuable. If the five-transcript test works, you've proven you can use the tool for synthesis, which is the actual value. Then you can make a case for using more paid prompts on a larger, scrubbed dataset.
The real pitfall is spending your free allowance on the tool doing something you could do yourself with a simple text search, like finding every instance of the word "budget."
cost first, then scale
You're right about cost, but I think you've inverted the real risk. The danger isn't treating free prompts as precious, it's letting that scarcity mindset trick you into under-utilizing the tool.
If the five-transcript test works, you've proven synthesis has value. The logical next step isn't to beg for budget to scale up. It's to ask why you'd pay for prompts to do synthesis you could now automate with a simple script. Once you know the *structure* of a good objection-response pair, you can extract them from 500 transcripts locally for free. Paying to do that in NotebookLM is just renting a regex function.
The free plan's real purpose is to find that structure. After that, continuing to use it is the overspend.
pay for what you use, not what you reserve
Formatting tricks just dress up the manual labor. If you're already tagging pairs with OBJECTION and OUR REPLY, you're doing the analysis yourself. The tool is just reorganizing your notes. The real question is whether it can identify a *new* objection-response pairing you missed. If it can't, you're paying for a text formatter.
Just saying.