I Built a Tiny YouTube Tool That Reached $500/Month — Here’s What I Learned

I didn't build a startup. I didn't raise funding. I didn't have a team of engineers. I simply built a small tool to solve a problem I personally had. And eventually, that little project started making money. **YTtoText reached $500/month.** Here's what happened. ## The Problem Was Almost Too Simple The original idea behind YTtoText was extremely simple. I was working with YouTube videos and constantly needed to find specific information inside long videos. Watching an entire 60-minute video just to find one sentence is incredibly inefficient. Then there was another problem. Copying subtitles manually is annoying. Downloading captions isn't always straightforward. And if you want to search through a long interview, podcast, tutorial, or lecture, the video itself isn't always the best format. I thought: **What if I could just turn the YouTube video into searchable text?** That became YTtoText. ## I Started With a Very Small MVP The first versi...

如何拉取appsflyer的投放数据?Pull API raw data和Pull API aggregate data提供了便利。

今日金句  学学半者,上学为教,下学者谓习也。

今日分享一下,如何拉取appsflyer的投放数据。

其实appsflyer提供了api接口,方便我们可以利用程序化去拉取并汇总报表数据。总体来说主要是两个窗口:Pull API raw data和Pull API aggregate data。

理论上只要上游开放了对应数据板块的权限,那我们就可以拉取到对应的数据。

需要注意的是,agency账户是可以拉取api数据的,ad network是没有权限的。

具体全局阅读可以参考:

https://support.appsflyer.com/hc/en-us/articles/360007530258-Pull-API-raw-data

https://support.appsflyer.com/hc/en-us/articles/207034346-Pull-API-aggregate-data

具体接口:
1. Pull API raw data

https://dev.appsflyer.com/hc/reference/overview-6 

2. Pull API aggregate data

https://dev.appsflyer.com/hc/reference/overview-5

3. 报告拉取限额(频次限制)

https://support.appsflyer.com/hc/zh-cn/articles/207034366

ok, 入口和参考文档已经齐活,接下来就是实际操作了。

希望今天的分享对你有所帮助!

评论

  1. 其实ad network也是可以拉取的。只要有api token就可以

    例如https://dev.appsflyer.com/hc/reference/get_app-id-daily-report-v5-1

    回复删除

发表评论

此博客中的热门博文

保姆级教程,教你如何在手机端使用Ghelper的VPN网络节点。

科学上网工具Ghelper的详细设置教程,看这一篇就够了。

appsflyer里的audience, AMS(all media sources)以及supported features的简单解读!