Background
hidol APP is a fan-tracking application. One year after launch, it pivoted to let users freely post “moments” documenting their fan activities. However, due to the product structure, user content was highly fragmented — difficult to generate engagement or be indexed by search engines.
The product team was already fully committed to new feature development, so I proactively volunteered to lead the research and prototype proposal.
Challenges
- User-generated content was highly fragmented; individual posts couldn’t stand alone as valuable content
- The product team had no spare resources for SEO or content strategy
- Needed to continuously produce quality content without adding headcount
Actions
After aligning with my manager on requirements, I planned two approaches: automated news reposting for continuous content flow, and aggregating popular in-app hashtag content into SEO articles.
For implementation, I used n8n + AppScript to pull data from external news sites, ran it through AI for rewriting, then posted back to the APP via API. Simultaneously, I queried BigQuery for all moments under trending hashtags — including images, content, and geo-coordinates — feeding them to AI for content synthesis and rewriting.
Results
Completed auto-posting from designated news sources to the APP within the first week. The scheduled pipeline ran for 2 weeks validating technical feasibility.
Manually extracted trending hashtag articles from the APP, rewrote them into high-quality SEO articles. Created “fan pilgrimage map” content using geo-coordinates, and submitted to the product team for further review.
- Validated that operations staff can independently build AI automation prototypes
- From concept to demonstrable prototype in just 2 weeks