Jotr VS StackStats.app

Jotr's answer

Jotr was built around a simple problem: transcription is only useful when it becomes something you can review, edit, search, summarize, quote, publish, or export.

Many tools stop at a raw transcript. Jotr focuses on the work after transcription: listening back with timestamps, finding key moments, making notes, creating summaries, exporting captions, and turning recordings into usable writing, research, meeting, or video materials.

StackStats.app's answer:

I built StackStats because Substack's native analytics weren't cutting it. I wanted cohort data, real open rates (not bot-inflated), and a way to identify which posts were actually driving subscriber growth — but every tool I found was either cloud-based or required migrating off Substack entirely. So I built a local app that works with Substack's own CSV exports. No migration, no cloud, no subscription.

Jotr's answer

Jotr is not just a raw transcription tool. It combines free Mac transcription, local Apple Silicon processing, timestamp-linked review, notes, highlights, local AI summaries, and export workflows in one desktop app.

A key difference is the creator workflow: video editors can finish the final cut first, then drop the exported video into Jotr and generate timed SRT or VTT subtitle files that align with the finished video. That makes it useful for YouTube videos, courses, tutorials, interviews, podcasts, and social clips.

StackStats.app's answer:

StackStats runs 100% locally on your machine — your subscriber data never touches a server. It also goes far beyond what Substack shows natively: bot-filtered open rates, cohort retention, superfan identification, dead subscriber detection, and content-to-growth correlation. No subscription, no account, no cloud. Pay once, own it forever.

Jotr's answer

Choose Jotr if you want a Mac-native transcription workflow without sending every project into a cloud workspace. Jotr is built for people who already have audio or video files on their Mac and want to turn them into transcripts, captions, notes, summaries, and exports.

Compared with many web-based transcription tools, Jotr is more local-first and Mac-focused. Compared with simple transcript generators, Jotr adds timestamped review, highlights, notes, summaries, SRT/VTT subtitle export, and practical writing/editing exports.

StackStats.app's answer:

Most newsletter analytics tools are cloud-based SaaS with monthly subscriptions. StackStats is a one-time purchase that runs entirely on your device. For Substack writers who care about privacy — especially those with paid subscribers — that's a meaningful difference. You also get analytics features that don't exist anywhere else, like bot-filtered open rates and cohort retention, without having to migrate away from Substack.

Jotr's answer

Jotr is for Mac users who work with recordings: video creators, YouTubers, editors, podcasters, researchers, students, consultants, writers, meeting-heavy professionals, and anyone who needs transcripts, captions, summaries, notes, or subtitle files from audio and video.

It is especially useful for people who edit videos first and then need accurate, timed subtitle files for the final cut.

StackStats.app's answer:

Serious Substack writers who are frustrated by Substack's shallow native analytics and want real data to drive growth — without moving their subscriber data to the cloud.

Jotr's answer

Jotr is a native macOS desktop app built for Apple Silicon Macs. It uses local speech-to-text processing, local AI summary workflows, timestamp-linked playback, subtitle export formats such as SRT and VTT, and native macOS distribution through a notarized DMG.

The product is designed around local project files rather than a cloud workspace.

StackStats.app's answer:

Electron (macOS + Windows), HTML/CSS/JavaScript, Chart.js, PapaParse. Optional AI layer supports Ollama, Claude, GPT-4, Gemini, Groq, and OpenRouter. Licensing via Cloudflare Workers + D1. Payments via Gumroad.