# Trendjacking

> A tool for turning current trends into brand-specific ideas

- **Client**: DOKI.id
- **Date**: 2024-2025
- **Metrics**:
  - Time Saved: ↓ 1440x (From 1-5 days to just 5 minutes)
  - Trend Response Speed: ↓ 24h (Respond to trends while they're still fresh)

## Details

The team at [DOKI](https://doki.id) reached out with a problem. They work with brands like Danone Aqua, Fonterra, and Tokopedia. Their teams were spending one to five days finding trends, checking whether they fit a client, and turning them into a pitch. By then, the trend was usually over.

The useful window was short-form video: TikTok and Instagram Reels, where a trend can go from everywhere to nowhere in about 48 hours.

## Getting the data

The hard part was getting reliable data from TikTok and Instagram. Both platforms make scraping unpleasant, so I spent a lot of time reverse-engineering endpoints, rotating proxies, and dealing with rate limits. Instagram was particularly painful.

Collecting posts was only half the job. The system also had to look at the video, engagement, comments, and sentiment, then compare all of that with a brand's voice. A trend that works for Aqua may make no sense for Tokopedia.

## What it does

I built an AI recommendation engine that tags the content, watches the videos, checks engagement, and reads the comments. It turns a noisy stream of posts into a shortlist someone can work with.

Then it matches trends with specific brands. The system knows each client's voice and values, so it only suggests ideas that fit.

## What changed

The first pass now takes about five minutes instead of one to five days. That gives DOKI's creative team a chance to respond while a trend is still worth responding to.

It became part of DOKI's workflow for its larger clients. Seeing a thing that started as a rough idea turn into something people use every day was the best part.