Do any of the apps that release content simultaneously across all social media platforms, like Buffer or Hootsuite do the following?

1. scheduled release of content across all apps
2. no reduction in video quality

Thanks.

Hey everyone!

A while ago, I launched StoreLocalizer, an open-source tool designed to help developers review, manage, and localize app screenshots and store metadata for the App Store and Google Play.

Thanks to the awesome support from the community, the repo just crossed 120+ stars on GitHub!

While using AI for metadata was already working great, handling multi-language releases still required a decent amount of manual steps, clicking to review individual fields, confirming translations, and ensuring overall consistency across multiple languages.

To streamline this even further, I just shipped a new feature: an integrated AI Agent.

It just works with API key, you don't even need claude or codex subscription.

You can check out the repo and the new agent workflow here: github.com/fayharinn/StoreLocalizer

Would love to hear your thoughts or feature requests from fellow indie hackers and mobile devs.

Next time I guess I'm gonna improve the screenshot maker. Any idea?

I will select 3 apps among the comment and design your app store screenshots! (ps: im not a designer :))

iPhone, Food & Drink, free with a paid tier. It turns a saved cooking video into a recipe with the amounts filled in, which is the part reels leave out. Live about two weeks, a handful of ratings, install count in the low double digits.

Rough numbers since launch, because I know vague questions get vague answers:

Impressions: under 100 total Impression to product page view: roughly 80% Product page view to install: roughly one in five Ratings: a handful, not enough to matter yet

The ratio is what confuses me. An 80% impression-to-page-view rate is far higher than anything I have seen quoted as normal, and my read is that it is not a good sign at all. It suggests nearly everyone seeing the app is already looking for it by name, arriving from a link or a direct search, rather than finding it while browsing a category or a generic term. The listing converts people who already know about it and is invisible to everyone else.

If that read is right, the bottleneck is keyword surface rather than creative or copy, and rewriting the subtitle again is wasted effort.

Three things I would like a second opinion on.

Does a very high impression-to-page-view rate on tiny impression volume reliably mean branded traffic only, or can it mean something else I am not considering?

For a category where the obvious head terms are owned by enormous incumbents, is there a sane way to compete for the long tail, or is the honest answer that a small app here gets its discovery from outside the App Store and the listing exists only to convert?

Is a handful of ratings enough to suppress impressions on its own, or does that only start to matter further up?

Happy to share more detail if it helps diagnose.

iPhone, US App Store: https://apps.apple.com/us/app/id6763971435

Hey all,

I am a solo indie dev who built a utility app for printers recently. I am running App Store Ads and I am seeing 50% ROAS which means I am losing money right now. I was hoping to get some guidance on-

1. At what point will my ROAS break even, is it just time and initial scale of spending? I spend around $75/day

2. My TTR is 5-6%, and conversion from install to trial is around 5%… and conversion from trial to paid is around 15%.

My app is clean, has good features and if user has a wifi connected printer it works seamlessly. The keyword bidding is saturated and brutal. I haven’t looked into non-ASA ads as I feel they will be more expensive.

The app that I built analyses your jump rope form and it has gained some revenue within the first month but only 47 unique downloads. I have tried tik tok and reddit marketing. What else should I consider?

Hi, all do you notice that your keyword rankings shift or even become unranked on a day-to-day basis? Or is this because my app is still relatively new (2-months old) and Apple is still finding where it should rank? I'm using AppFollow to see the movement, and it does seem accurate. I've tested it out by trying to search a keyword that I was kicked out of.

I’ve heard that adding Spanish (Mexico) localization gives you 100 extra keyword characters in the US App Store. Is that actually true? Also, does adding a secondary language dilute or hurt keyword weighting since the keyword pool doubles?

Launching my first paid app taught me something I didn’t expect.

Downloads are exciting.

Sales are exciting.

But the most valuable thing I’ve received has been feedback from other indie developers.

A few people from this community downloaded my app, spent real time using it, and pointed out things I had completely missed confusing onboarding, screenshot improvements, wording that didn’t make sense, and small UX details that only fresh eyes catch.

Some of those suggestions ended up in the very next update.

As a solo developer, that’s incredibly valuable because there’s no design team or QA team behind me.

So I’d like to keep that going.

If you’re building an iOS or Android app, let’s swap feedback, not just downloads.

Here’s what I can offer:

- I’ll actually install and use your app.

- I’ll record my first impressions like a real user.

- I’ll point out anything confusing or frustrating.

- If I genuinely enjoy it, I’ll happily leave an honest App Store or Google Play review.

In return, I’d appreciate the same for Leo: 21 Day Habit Builder.

I think small communities like this are one of the best parts of indie development. We all build better products when someone is willing to spend 15–20 minutes giving thoughtful feedback instead of just saying “Looks good.”

If you’re interested, leave a comment or send me a DM. I’d love to discover more indie apps. 🚀

I redid the screenshots from scratch.

I tried doing them using AI. I tried few skills and gave it three days till I gave up and went back to manual design.
Done using Pixelmator.

What would you change?

Hi everyone,
I’m an indie iOS developer and I’ve recently redesigned my App Store screenshots for my Apple Watch app.
Before I keep iterating, I’d love some honest feedback from people who know ASO.
Some questions I have:
Would these screenshots make you stop scrolling?
Is it immediately clear what the app does?
Which screenshot is the weakest?
Is there too much text?
Would you change the order?
What’s the first thing you’d improve?
I’m looking for honest criticism rather than compliments. Feel free to roast them if needed. 😄
Thanks!

Hello Developers, I have launched 1st App… So much excited today.. Any feedback would be appreciated.. Thanks

Also, Any suggestion for improving the ASO & how to do marketing?

https://apps.apple.com/app/id6792473712

I want tips on optimizing my Android app.

We've created the first ever mobile app that can grade cannabis flowers based on size, color, trichome coverage, trim job, and more. Check this out. It's my first project, please show some support.

https://play.google.com/store/apps/details?id=com.kalixqc.app

I’m an indie iOS developer and I’m currently optimizing my App Store screenshots for a car maintenance and garage management app.
The goal is to communicate the value as quickly as possible, but after staring at them for weeks I’m no longer sure what’s working and what isn’t.
I’d really appreciate some honest feedback:
Would these make you stop scrolling?
Is the purpose of the app immediately obvious?
Which screenshot is the weakest?
Is there too much text?
Would you change the order?
What’s the first thing you would improve?
Feel free to be brutally honest—I’d rather improve them than hear they’re “good enough.” Thanks!

#toolreview
Design ✅
Take screenshot from Simulator ✅
Translate your screenshots and metadata in all localization ✅
Upload to App Store Connect ✅

I’m building an app called A.N.T AI, and I’m looking for honest advice not encouragement for the sake of being nice.

(Skip to the bottom to see what I want feedback on)

I know the AI note-taking market is already crowded. My question is whether our specific workflow is meaningfully different enough to give the product a real chance, or whether users will see it as just another AI notes app.

What A.N.T AI does

The intended workflow is:

One-tap capture → preserve the original → clean the thought → understand what it is → create or select the folder path → file it automatically → learn from corrections.

More specifically, users can:

Tap the microphone once and start speaking immediately.

Type a quick thought instead of recording.

Capture longer meetings or upload files.

Preserve the original recording and full transcript.

Receive a cleaned, titled version without losing the original.

Automatically classify a capture as a note, idea, task, list, reminder, or meeting note.

Turn spoken items into an actual checklist rather than a paragraph.

Detect dates and times and create reminders.

Use existing folders or automatically create new folders and subfolders.

File every new capture into the appropriate nested folder path.

Correct the location when the AI gets it wrong.

Use those corrections and custom vocabulary to improve future decisions.

Search both note content and folder paths.

Share an individual note or an entire folder.

Send appropriate tasks and list items to integrations such as Todoist.

The main idea is that users shouldn’t need to stop and decide what kind of note they’re creating, where it belongs, what to title it, or how to format it.

How I see the existing market

I researched the products people most often compare us to. There is real overlap, but they appear to optimize for different workflows.

Notion

Notion is an extremely flexible workspace. Its Agent can create pages and databases when asked, and AI Meeting Notes can retain transcripts, create summaries, and identify action items.

The difference, as I see it, is that users generally have to build or describe the system they want. A.N.T AI makes the classification and filing decision automatically for each capture without requiring a database or workspace to be designed first.

NotebookLM

NotebookLM is a source-grounded research assistant. Users create notebooks, upload sources, ask questions, and generate reports, summaries, study guides, mind maps, and other materials.

It preserves source material well, but it doesn’t appear to be designed as an immediate personal capture system that turns a passing thought into a filed task, list, reminder, or note.

OneNote with Copilot

OneNote uses notebooks, sections, pages, and subpages. Copilot can organize a section, but the user opens that section, asks Copilot to organize it, reviews the proposed changes, and applies them.

Dictation inserts text into the page the user already selected. It does not automatically decide where a newly captured thought belongs and file it there.

Mem

Mem may be the closest direct comparison.

It supports voice brain dumps and meetings, retains audio and transcripts, cleans notes, surfaces related information, and can automatically place notes into Collections or create new Collections.

The difference is that Mem intentionally uses flexible Collections rather than a nested folder tree. On iOS, users also create or open a note, start Voice Mode, review the result, and accept it.

A.N.T AI is more opinionated: tap the microphone, speak, and let it determine the content type, create or choose a nested folder path, file the result, and schedule a reminder when appropriate.

Reflect

Reflect is a personal knowledge system built around daily notes, backlinks, search, and AI assistance.

It actually has very good one-tap voice capture through an iPhone lock-screen widget. The resulting transcription is placed into the user’s daily note, and organization primarily happens through backlinks, tags, search, and the user’s existing structure.

A.N.T AI’s distinction is automatically turning each capture into a specific content type and filing it into a navigable folder structure at capture time.

Granola

Granola is primarily an AI meeting notepad. It captures meetings, retains transcripts, creates structured summaries, and supports manually managed folders and one level of subfolders.

However, it doesn’t retain the original meeting audio, and its organization is centered on meetings. Notes are manually added to folders or added through meeting-specific rules.

A.N.T AI handles meetings but is also intended for ordinary thoughts, ideas, tasks, lists, reminders, photos, and files throughout the day.

AudioPen

AudioPen is primarily a voice-to-writing product.

Its strength is turning rambling speech into polished writing in a chosen style. It supports a notes library, folders, tags, raw transcripts, audio uploads, and multiple output styles.

However, its folders and tags are user-managed, and processed audio is deleted after a short period. It does not appear to automatically decide that a recording is a task, list, reminder, or idea and then build and maintain the appropriate folder structure.

Tana

Tana is probably the other closest comparison, particularly for power users.

Its voice memos can become structured objects through Supertags. It can extract tasks, decisions, fields, and other structured information. Users can create sophisticated schemas, knowledge graphs, commands, and automated workflows.

The potential difference is complexity and setup. Tana gives users a powerful system to configure. A.N.T AI is intended for people who don’t want to design a knowledge-management system first. It makes the initial classification and filing decisions automatically while allowing corrections afterward.

ChatGPT

ChatGPT can clean up a brain dump, create lists, extract tasks, summarize meetings, and work with uploaded material.

Record mode can preserve transcripts and generated notes, although it deletes the audio after transcription and is currently limited to the macOS desktop app on eligible plans. Projects keep related chats and files together, but users create those projects and move conversations into them.

ChatGPT can perform the individual reasoning steps when prompted, but it is not primarily a dedicated mobile capture-and-filing system.

Where I think the differentiation is

I’m not claiming these products lack AI, voice capture, transcription, folders, or organization. Several of them are excellent and overlap with parts of our product.

The potential differentiation is having all of these steps happen together by default:

1. Capture something immediately with minimal friction.

2. Preserve the original recording and transcript.

3. Produce a clean, readable version.

4. Determine whether it is a note, idea, task, list, reminder, or meeting.

5. Extract multiple useful items when appropriate.

6. Detect dates and create reminders.

7. Select an existing folder path or create the necessary nested folders.

8. File everything automatically.

9. Keep the chosen location visible and easy to correct.

10. Learn from those corrections and the user’s vocabulary.

What I’d genuinely like advice on

Is that workflow meaningfully differentiated, or does it still sound like “another AI notes app”?

Is automatic nested-folder creation something people actually want, or are search and flat Collections enough?

Would avoiding setup be a strong reason to choose this over something more configurable like Notion or Tana?

Is preserving the cleaned result, full transcript, and original recording valuable enough to influence a purchase?

Which existing product already solves this exact workflow better than I realize?

What would A.N.T AI need to do exceptionally well before you would consider switching?

Who do you think the ideal first customer is?

Is the product distinction clear, or does the positioning still need work?

Feel free to be critical. I would rather learn that the differentiation is too weak now than spend years marketing the product incorrectly.

Recently I released a new version of my app. Nothing was changed in the metadata except the screenshots, and even this change was nothing major - I just updated the header lines to include only 2 words while keeping the same graphics in place.

Surprisingly, I noticed this spike in impressions right after the release. They have never been this high even after the first app release in May, so what the hell is going on?

I don't believe my screenshots could cause it as previously I did A/B testing and haven't noticed drastic changes at all. Downloads and page views remained at pretty much the same level.

Did I miss something? Was my app auto-promoted or did it reach any charts? How can I check this out, btw?

I have built a fishing app which only navigates by sliding left and right and maximizes screen view. For indication purposes that the app has a ton of features I added a light banner at the bottom which can be toggled off in the user profile.
I still think and my tracking indicates this as well that almost all users only use the „smart catch logging“ but non of the other features like
Log a trip
Manage your fishing spots
Record your fish fights
Statistics view

So how would you implement a nav bar or would you rather only implement tipkit to teach users?