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Easily compare the costs of newsletter platforms

Hacker News

Easily compare the costs of newsletter platforms

I've been writing on Substack for the last year, and from the beginning I've been aware that I might want to migrate to a different platform at some point. I've been looking into the various alternatives to Substack for a while, and always found it difficult to compare costs across the different platforms. There's just too many variables that factor into the cost, and each platform has a slightly different pricing scheme. I've also been looking for the chance to try Streamlit, a Python library for making dashboards. Getting started with Streamlit was even easier than I imagined, so I ended up making a dashboard for comparing the costs of hosting a newsletter on each of five platforms: Ghost Pro, Buttondown, beehiiv, Substack, and ConvertKit. You can input the number of subscribers you need to support, the percentage of subscribers with a paid subscription, and the average annual revenue per paid subscriber. If anyone here is thinking of starting a newsletter, or migrating to a different platform, you might find it helpful. If you've been curious about Streamlit, you might be interested as well. There's a link to the GitHub issue tracker, so if you find anything broken or inaccurate feel free to comment here or open an issue. One thing that's interesting to see is how differently some of the pricing schemes behave at lower subscriber numbers, and lower annual revenue amounts. Someone with a large following and a large revenue base has a much different set of choices than someone with a small subscriber base and a lower ratio of paid subscribers. https://nl-compare.streamlit.app

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
60%60% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: way · Missing: mobile apps, ios, personal
59%59% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntOn track for Day 1 leaderboard · Strong signals: beehiiv, new, open · Missing: mac, agents, macos
51%51% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host · Missing: plus, intuitive, reviews
36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: revenue, subscription, subscribers · Missing: arr, mrr, profit
24%24% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: paid · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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