Temu Category Trend Report

Daily Temu category intelligence for brands, retailers, and agencies competing in the US market. Track which products are gaining momentum, how category pricing is shifting, and where new competition is entering — updated every day.

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Who Uses This

Brands and retailers selling in categories where Temu competes You sell on Amazon, your own site, or wholesale — and Temu operates in your category. You need to know when a new product is gaining traction on Temu, whether it's priced below your floor, and how fast it's climbing.

Concrete example: you sell home cleaning tools on Amazon. A competing product appears in Temu's top 100 at $2.99 and climbs 30 ranks in a week. You see it in hot_picks with rank_7d_delta: -30 before it starts showing up in your Amazon BSR. That's your window to respond — reprice, run a promotion, or flag it for your sourcing team.

Agencies providing market intelligence to retail and brand clients Schedule a daily run per category, pull market_signal + hot_picks into your reporting pipeline, and generate client-ready output automatically. A 5-category daily monitor runs at a fraction of your retainer.

In-house e-commerce and category management teams Pipe the data into your dashboard or Slack via Zapier or Make. When market_signal shifts to "Hot" in a category you own, alert the team. When a new product appears in hot_picks with appearances_7d >= 5, add it to the review queue.

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Supported Categories

Category ID	Category Name
25	Beauty & Health
28	Women's Clothing
36	Home & Kitchen
67	Men's Clothing
95	Women's Shoes
114	Men's Underwear & Sleepwear
178	Sports & Outdoors
202	Home Gadgets & Office
204	Toys & Games
218	Kids Fashion
248	Electronics & Accessories
259	Business, Industry & Science
320	Pet Supplies
352	Jewelry Accessories
580	Automotive
589	Women's Curve Clothing
628	Musical Instruments
731	Men's Bags & Wallets
871	Health & Household
1107	Women's Lingerie & Lounge
1167	Baby & Maternity
1232	Men's Big & Tall
1422	Smart Home
1536	Men's Shoes
1553	Kids Shoes
2640	Cell Phones & Accessories
7084	Food & Grocery
7085	Books & Media
7166	Beachwear
885	Patio, Lawn & Garden
893	Tools & Home Improvement
990	Appliances
1493	Arts, Crafts & Sewing

More categories added regularly.

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Input

{
  "category_id": "36",
  "region": "US"
}

Field	Type	Required	Default	Description
category_id	string	Yes	—	Category ID from the table above. Pass as a string (e.g. "36")
region	string	No	"US"	Market region. Currently US only

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Output

Each run delivers two outputs.

Dataset — 100 product rows, one per product in today's top 100 ranked by sales volume. Key fields per row:

Field	Description
rank	Today's rank within the category (1 = best)
momentum_status	Breakout / Rising / Stable / Declining / Fading / New — see below
rank_7d_delta	Rank change over 7 days. Negative = climbed. -30 = moved up 30 spots
price / price_str	Current price
price_7d_delta	Price change over 7 days (USD). Positive = price increase
price_vs_top100_avg	This product's price vs category average. 85.9 = 14% cheaper than average
appearances_7d	Days seen in top 100 over the last 7 collection days (max 7). Below 4 = unstable
review_count_7d_delta	New reviews added in the past 7 days
goods_url	Clean product page URL

Key-Value Store: REPORT_SUMMARY — category-level summary for the day:

Field	Description
summary.market_signal	Hot (≥75% Breakout+Rising) / Warm (≥50%) / Cooling (>40% Declining+Fading) / Neutral
summary.new_entries_today	Products appearing in top 100 for the first time today
summary.momentum_distribution	Count per momentum status
data_reliability.signal_confidence	High / Medium / Low — how much to trust momentum signals today
data_reliability.note	Plain-language interpretation of today's signal quality
price_trend_7d	7-day history of category avg price, discount rate, and momentum distribution
hot_picks	Up to 50 highest-momentum products (all Breakout + top Rising by rank delta)

Momentum Status

Value	Meaning
Breakout	Rank climbed >5 spots AND sales up in 7 days — strongest signal
Rising	Rank improving or sales growing steadily
New	First seen in this category's top 100 today
Stable	No significant movement
Declining	Rank dropping or price rising
Fading	Seen on 3 or fewer of the last 7 days — trend ending

Backtested over 6 days across 18 categories: 68.7% of Breakout products were still in the top 100 six days later.

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How to Read the Data

Start with REPORT_SUMMARY

market_signal = "Hot"     → Strong growth (≥75% Breakout+Rising) — act now
market_signal = "Warm"    → Moderate growth (≥50% Breakout+Rising)
market_signal = "Cooling" → Category losing momentum (>40% Declining+Fading)
market_signal = "Neutral" → Mixed signals, check individual products

Check data_reliability.signal_confidence before acting. Each run computes this from that day's actual data:

"data_reliability": {
  "signal_confidence": "High",
  "churn_level": "Low",
  "tracking_coverage": 0.93,
  "stable_product_ratio": 0.76,
  "note": "Momentum signals are reliable. Breakout and Rising products can be acted on directly."
}

Find what's moving

Filter hot_picks or the Dataset:

momentum_status = "Breakout"              → Strongest signal. Rank climbing + sales up.
momentum_status = "Rising"
  + rank_7d_delta < -20                   → Rising fast
  + appearances_7d >= 5                   → Consistent presence, not a one-day spike
momentum_status = "Fading" or "Declining" → Losing ground. Exiting the competitive set.

Track pricing pressure

price_trend_7d in REPORT_SUMMARY shows 7 days of category average pricing. A falling avg_price alongside rising Breakout counts is the earliest signal of margin compression in your category.

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API Integration Example

Scheduled daily run

from apify_client import ApifyClient

client = ApifyClient('YOUR_API_TOKEN')

run = client.actor('YOUR_ACTOR_ID').call(run_input={
    'category_id': '36',
    'region': 'US',
})

# Category-level signal
record = client.key_value_store(run['defaultKeyValueStoreId']).get_record('REPORT_SUMMARY')
summary = record['value']
print(f"Market signal: {summary['summary']['market_signal']}")
print(f"Signal confidence: {summary['data_reliability']['signal_confidence']}")

# Hot picks — highest-momentum products today
for p in summary['hot_picks']:
    print(f"  [{p['rank']}] {p['title']} — {p['price_str']} (rank moved {p['rank_7d_delta']})")

Filter and store product rows

const { ApifyClient } = require('apify-client');
const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('YOUR_ACTOR_ID').call({ category_id: '36', region: 'US' });

const { items } = await client.dataset(run.defaultDatasetId).listItems();

// Breakout products — flag for competitive review
const breakouts = items.filter(p => p.momentum_status === 'Breakout');

// Price movers — products cheaper than category average and climbing
const pricePressure = items.filter(p =>
  p.price_vs_top100_avg < 80 && p.rank_7d_delta < -10
);

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Data Notes

• US market only
• Top 100 ranked by sales volume at time of daily collection
• sales_7d_delta is often 0 due to Temu's bucketed display ("100K+"). Use rank_7d_delta as the primary trend signal
• disappeared_today counts cumulative exits over the 7-day window — can exceed 100
• appearances_7d and days_in_category are capped at 7. During the first 6 days of tracking a new category, Fading counts appear inflated — this normalizes automatically after day 7