This truly sounds like a game changer tool, because people in different timezones have different hours and being someone who has worked as a content creator before, can't agree more with you on the kind of pain, one feels when hours of editing go in vain. All because of, bad upload time.
Best Time to Post on Social Media Tool
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This is a solid niche tool. Time zone math for posting is one of those small problems that ends up wasting way more time than it should, so a quick utility like this actually saves people from messy spreadsheets they keep getting wrong.
I’m curious about the data side though. How are you determining peak activity hours for each platform? Most platforms don’t really expose great public data for that, and a lot of the aggregated studies tend to be biased toward the audience of whatever tool ran them.
Are you pulling from a third party dataset, inferring patterns, or just letting users rely on their own analytics?
I ask because I work on Made4Founders, an AI social posting tool, and we ran into the same issue. We ended up leaning into user specific data, letting the AI suggest timing based on their own historical engagement instead of generic benchmarks. That avoids the whole “Tuesday at 10am” cliché.
Curious what led you to focus on timezone conversion instead of going deeper into timing optimization.
@[Joshua R. Gutierrez] Thanks so much, Joshua! That genuinely means a lot — timezone math sounds simple but it's one of those silent time-killers that trips up even experienced creators, so I'm glad the tool is solving a real pain point.
You've asked exactly the right questions! Right now I'm using aggregated benchmark data from studies (Sprout Social, HubSpot, etc.) as the baseline — totally honest that it has the "generic audience bias" problem you mentioned. But the vision is to evolve it into something more personalized, where users can layer in their own analytics on top of the timezone conversion.
What you've built at Made4Founders sounds like the smarter long-term approach — user-specific historical data beats any generic benchmark every time. The "Tuesday at 10am" advice honestly stopped being useful years ago.
My focus on timezone conversion first was intentional: it's the foundation layer — you can't even begin to optimize timing if your converted time is wrong. But timing intelligence based on personal data is absolutely the next level I want to reach.
Would love to connect and exchange notes on how you handled the analytics API side — always better to learn from builders who've already solved the hard parts!
I appreciate the thoughtful response. The analytics API side is genuinely the messy part. Every platform has its own auth flow, rate limits, and data shape.
Three things hurt us more than expected:
Most platforms don’t expose follower-side timezone data. You can pull when posts performed, but not where the audience was when they engaged. We ended up inferring from server-side timestamps plus the engager’s account location when the API exposes it. LinkedIn does, X kind of does, Mastodon does not on most instances.
The cold start for new accounts is a real problem. No history means no signal. We fall back to a hybrid of platform and vertical benchmarks, then slowly weight toward user-specific data as it accumulates. It takes about 20 to 30 posts before personalization meaningfully outperforms the benchmark.
The Mastodon decentralization tax is real. You cannot query engagement on other instances easily, so we treat it as a special case.
I am happy to share more on any of these. You can drop me a DM if you want to dig in.
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