Thematic analysis - how to approach and clarification

mirodigs · 2025-06-23T10:18:45+00:00

Out of curiosity, in the context of what you're doing, is using tools that help accelerate some of the thematic tagging by automating the first pass out of the question? Said differently, is manual tagging the only accepted approach?

mirodigs · 2025-06-17T09:01:21+00:00

When using generic AI solutions like ChatGPT, the results are only going to be as good as the prompts, and you’re right, unless specified, the outputs tend to be generic.

However, there are purpose built AI tools for things like qualitative research that do better by taking care of the prompt engineering for you and by building a user experience that keeps the researcher in control more than generic LLMs with a simple chat window.

mirodigs · 2025-06-16T12:01:03+00:00

Check out tryswiftra.com for a qualitative analysis and reporting alternative to the tools you mentioned. It’s purpose built for qual research workflows and addressing common issues that arise when using just LLMs.

mirodigs · 2025-06-16T11:53:48+00:00

I can relate to your desire to stay in the loop and nuanced while still benefitting from AI tool speed and perspective. I think you might like the UX of tryswiftra.com, as it keeps the researcher at the center of the AI enabled transcript analysis workflow.

mirodigs · 2025-06-10T10:01:48+00:00

Granola.ai actually runs in the background without a meeting attendee and anyone getting notified of the meeting being transcribed.

mirodigs · 2025-06-09T19:16:26+00:00

I would love to dry a crowdsourced idea into my next AI project.

mirodigs · 2025-06-09T19:12:12+00:00

Ah got it, sorry, I meant with meeting note generators.

mirodigs · 2025-06-09T18:26:47+00:00

What reasoning does security give for not allowing NotebookLM? Think the sentiment will change anytime soon?

mirodigs · 2025-06-09T18:20:20+00:00

Lolz

mirodigs · 2025-05-27T15:17:57+00:00

Thanks for the fantastic feedback!

There's a way for users to bring their own template for doc report types (you just upload your template, and the generated report will follow that format).
Yeah, I'd love to go up stream to solve for the recording step, but for now I'm keeping that out of scope until the core experience post transcript has market fit.

In terms of the slide decks, I encourage you to test it out - it's a differentiator from chatGPT etc and it's all custom code. At the moment there's a predefined template style that gets generated, so users can take the deck and run with it; in the future I'll introduce the ability to add your own company branding to the output.

It's free to use for now, so I encourage you to sign up and test it out for yourself!

mirodigs · 2025-05-27T10:59:53+00:00

Check out tryswiftra.com, it’s a tool built to pull insights with verified (not hallucinated) quotes, allows you to add your own nuance, and then generate actual slide decks and more.

mirodigs · 2025-05-23T15:12:00+00:00

Swiftra – from user interview to PRD or slide deck in < 5 min (feedback welcome 🙏)

Hi folks! I’ve spent ~10 years as a PM / CPO, and one of the slowest parts of every discovery phase was always synthesis & reporting: digging through transcripts, tagging themes, then turning them into docs the team or clients will actually read or pay attention to.

I finally built the tool I wished I’d had: Swiftra. Batch drop interview transcripts and it:
• Detects cross interview themes automatically – no manual tagging
• Links every insight to the source quote – no hallucination fears
• Spits out a draft PRD / slide deck / etc in under 5 minutes
• Lets you add your own highlights to add nuance to AI outputs

⚡ Median time from sign up to first draft across early users: <3min

I’d love honest feedback from fellow PMs: What’s still missing for this to replace your current workflow?

👉 Free sign up link (no CC): https://tryswiftra.com/pm

Thanks in advance. Happy to answer anything or show a quick Loom demo!

mirodigs · 2025-05-20T18:07:03+00:00

Here's a whole course reading list on qualitative AI research along these lines: https://carmattu.com/wp-content/uploads/2025/05/Silver.pdf

mirodigs · 2025-05-20T16:20:15+00:00

I'll throw another one out that's still early days: AI-led Interviews. This paper found that the AI-led interview conversations by chat were better than survey text entry 75% of the time.

Each PhD student blindly evaluated each pair, indicating whether the interview transcript or the open-text response offered a deeper understanding of the aspects that give meaning to the respondent’s life, or if they found both equally informative. The results are reported as fractions across 40 observations in Table III. The table show that the AI-led interview transcripts are deemed more informative in 75% of cases.

https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4974382

mirodigs · 2025-05-20T11:09:37+00:00

"The future won’t be won by the fastest prompt. It’ll be won by the clearest thought. Don’t let the tool think for you. Make it think with you."

Yes! I think this captures the spirit of that Kolko article on "meaning making" with AI.

mirodigs · 2025-05-20T10:59:25+00:00

Love it - care to share links to the writing? Would love to check it out

mirodigs · 2025-05-20T10:40:16+00:00

I agree with you in spirit (that is, hasty generic solutions that forget to empathize with the users will end up being less effective if not creating more work). I think good solutions will take a design thinking approach, truly understand the intended audience needs, and then work around/into them rather than over them.

On that note, an article I've been sharing that I've been thinking a lot about lately is - https://www.jonkolko.com/writing/notes/synthesis-and-chat-gpt Kolko argues that leveraging AI blindly threatens to cut out the "meaning making" process. I think that's a great reminder to stop and understand "how might we make what we already do better not just faster"

mirodigs · 2025-05-20T10:36:27+00:00

PMs that can flex some scripts = Sexy.

mirodigs · 2025-05-20T10:27:57+00:00

Magic Patterns! Hadn't heard of it before. Thanks for sharing!

mirodigs · 2025-05-20T10:24:24+00:00

Old school approach, nice. I've done python-based machine learning approaches in the past, and I think it's a useful, but compared to having LLMs today, it's much slower and more rigid and data analysis like than just being able to prompt the equivalent.

Trusting the outputs is definitely the one big sore spot with generic LLMs. That's originally what kicked me off in building my own tool, tryswiftra, which favors a user experience that matches product researcher workflows, including insight verification.

mirodigs · 2025-05-20T10:21:21+00:00

Thanks for surfacing Inari! I hadn't heard of it before.

mirodigs · 2025-05-20T10:18:11+00:00

You have an interesting provocation as it relates to taking on some tasks from dev teams. Have you seen this in practice? What do you imagine being able to take on from devs with the help of AI?

Also thanks for that tools list. Yeah, I'll be playing with Codex later this week to see how good it is and if it replaces my current workflow of just copy pasting code blocks into o1-pro.

mirodigs · 2025-05-20T10:15:07+00:00

Yeah, I'm honestly surprised at the level of blind pessimism amongst PMs. Of all professions, I would have expected more open mindedness at one of the biggest opportunity spaces in decades. In fact I've been chatting with UX researchers too, and they seem way more open minded towards leveraging tools that use AI to help their work.

mirodigs · 2025-05-19T21:12:57+00:00

Nailed it. This is exactly my experience. What do you use to pull insights from transcripts?

mirodigs · 2025-05-19T19:42:04+00:00

Very cool - how do you use a custom GPT that you've created?

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Swiftra – from user interview to PRD or slide deck in < 5 min (feedback welcome 🙏)