[Snickerdoodle]

Hey everyone,

I've been working on making an AI-powered app for Tiktok that grabs user's Tiktok videos and uses components similar to Creator Search Insight and general outputs from your typical AI (Chatgpt, Gemini, Grok) to redesign and create better optimized videos. The end goal would be to increase user's SEO and help users gain more likes, views, and visibility on their content regardless of the following.

I've already setup the database, the site and the connection between Tiktok developer app to the site as well.

I'm wondering what features should I asd rhat would make it more unique and more useful than the currently existing creator search insight or people's general access to AI.

[Snickerdoodle]

Today I managed to connect it between Apple Pay, Capcut and Tiktok altogether without issues and developed a payment tier.

[dreadful.diary]

I’d focus on making the advice specific to each creator and easy to act on. Hooks and captions alone are fairly easy to get from a general AI tool. The opportunity is connecting advice to their actual videos, goals, and results.

Three features could make this more useful:

1. Specific video feedback: Instead of “improve your hook”, identify the moment and suggest a change:
“The demonstration starts at 12 seconds. Try opening with the result.” Give them a revised opening or a short editing checklist. Keep editorial suggestions separate from conclusions supported by audience data.

2. Personalised recommendations: Use their content history to suggest topics and formats worth testing. Compare similar videos and explain the reasoning behind each suggestion.
One successful post shouldn’t become a rule for their entire account. For newer creators, frame recommendations as experiments until you have enough evidence.

3. An experiment history: Remember what you suggested, what they changed, and how subsequent videos performed. Over time, help them see which approaches seem worth repeating. Be careful about claiming causation, though. More views on the next upload don’t prove that a particular edit was responsible.

And another useful touch could be remembering their voice and preferences. Let them save examples they like and reject language they would never use, so the output becomes more recognisably theirs.

For the first version, I would keep it pretty simple. Two videos, three actionable improvements per video, and a way to review the outcome.

Then test it with a small group in one creator category and watch whether they use the suggestions and return with more videos and possibly question or feedback.

[Snickerdoodle]

I’d focus on making the advice specific to each creator and easy to act on. Hooks and captions alone are fairly easy to get from a general AI tool. The opportunity is connecting advice to their actual videos, goals, and results.

Three features could make this more useful:

1. Specific video feedback: Instead of “improve your hook”, identify the moment and suggest a change:
“The demonstration starts at 12 seconds. Try opening with the result.” Give them a revised opening or a short editing checklist. Keep editorial suggestions separate from conclusions supported by audience data.

2. Personalised recommendations: Use their content history to suggest topics and formats worth testing. Compare similar videos and explain the reasoning behind each suggestion.
One successful post shouldn’t become a rule for their entire account. For newer creators, frame recommendations as experiments until you have enough evidence.

3. An experiment history: Remember what you suggested, what they changed, and how subsequent videos performed. Over time, help them see which approaches seem worth repeating. Be careful about claiming causation, though. More views on the next upload don’t prove that a particular edit was responsible.

And another useful touch could be remembering their voice and preferences. Let them save examples they like and reject language they would never use, so the output becomes more recognisably theirs.

For the first version, I would keep it pretty simple. Two videos, three actionable improvements per video, and a way to review the outcome.

Then test it with a small group in one creator category and watch whether they use the suggestions and return with more videos and possibly question or feedback.

Thank you for the support,

I was planning to take all the information as well from their videos and converting it into Sha-256 that could be understood by web3 in an attempt to boost SEO through web3 content indexing.