Finding TikTok Shop Trending Products
Identifies products gaining momentum on TikTok Shop by analyzing creator promotion density and engagement. A product promoted by many creators simultaneously is a strong viral commerce signal.
Prerequisites
APIFY_TOKENenvironment variable set- Optional: Apify MCP server installed
Inputs
| Parameter | Type | Required | Default | Notes |
|---|---|---|---|---|
startUrls |
array | Optional | [] |
TikTok URLs — user profiles, hashtags, music pages, search, locations |
keywords |
array | Optional | [] |
Search keywords/terms to find posts |
sortType |
string | Optional | RELEVANCE |
Sort order for keyword results: RELEVANCE, MOST_LIKED, DATE_POSTED |
location |
string | Optional | — | ISO 3166-1 alpha-2 country code for regional filtering (e.g. US, GB) |
maxItems |
number | Optional | Unlimited | Maximum posts to return across the run |
includeSearchKeywords |
boolean | Optional | false |
Add the matched search keyword field to each post |
customMapFunction |
string | Optional | — | JavaScript function to transform each output object |
Workflow
Progress:
- [ ] Step 1: Search TikTok Shop hashtags for category
- [ ] Step 2: Extract products from promotional posts
- [ ] Step 3: Count creator promotion density per product
- [ ] Step 4: Score product trend momentum
- [ ] Step 5: Deliver trending product list
Step 1: Search Posts
Recommended — run_actor.js (handles waiting, output, and file saving automatically):
# Quick answer (prints table to chat)
node scripts/run_actor.js \
--actor "apidojo~tiktok-scraper" \
--input '{"param": "value"}'
# Save as CSV
node scripts/run_actor.js \
--actor "apidojo~tiktok-scraper" \
--input '{"param": "value"}' \
--output YYYY-MM-DD_results.csv --format csv
# Save as JSON
node scripts/run_actor.js \
--actor "apidojo~tiktok-scraper" \
--input '{"param": "value"}' \
--output YYYY-MM-DD_results.json --format json
APIFY_TOKENmust be set in environment or.envfile.
If Apify MCP is available:
Tool: apify:run-actor
Actor: "apidojo~tiktok-scraper"
Input:
{
"keywords": ["#tiktokshop[category]", "#[category]deals", "#tiktokmademebuyit"],
"maxItems": 300
}
REST API fallback:
curl -X POST \
"https://api.apify.com/v2/acts/apidojo~tiktok-scraper/runs?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"keywords": ["#tiktokmademebuyit", "#skincaretiktokshop"], "maxItems": 300}'
Step 2: Score Products
Group posts by product name from captions. For each product:
promotion_density = count(unique creators promoting product)
total_reach = sum(playCount for all promoting posts)
engagement_rate = sum(diggCount) / total_reach * 100
trend_score = (promotion_density / 5, max 1) * 0.35
+ (total_reach / 1000000, max 1) * 0.35
+ (engagement_rate > 3 ? 1 : engagement_rate/3) * 0.30
Trend window: 70%+ promotions in last 7 days = PEAKING; spread evenly = SUSTAINED; mostly > 7 days = FADING
Step 3: Edge Cases
- Product name extraction unreliable: Extract most specific noun phrase from caption alongside shop link
- Same product different variants: Group by product name similarity; sum reach across variants
- Saturated trend (> 50 creators): Window may be closing; flag as
LATE_STAGE - Counterfeit signals: Price far below market (e.g. < $5 for normally $30+ item) → flag
Output Format
# TikTok Shop Trending Products: [CATEGORY]
Posts analyzed: [N] | Unique products: [N] | Date: [DATE]
## Trending Now (Peak Momentum)
| Product | Creators | Total Views | Avg Eng Rate | Stage | Score |
|---------|---------|------------|-------------|-------|-------|
## Sustained Performers
| Product | Creators | Total Views | Stage |
|---------|---------|-----------|-------|
## Saturation Alert
[Products with > 30 creators — difficult to enter profitably]
Troubleshooting
Few products identified: Check bio links of top promoting creators for product page. Trend already peaked: Run every 3-4 days to catch trends early. Suspicious pricing: Flag and verify before sourcing.