Korean Search & Shopping Trends - NAVER DataLab

What Korea is searching for, and who is buying what. NAVER holds the dominant share of Korean search, and DataLab is its official trend data. This actor turns it into rows you can chart, model or feed into a dashboard.

Two datasets in one run: keyword search trends and shopping demand insights broken down by category, keyword, gender, age band and device.

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What you get

Search trends - one row per keyword group per period

Field	Example
group	AI
keywords	AI, 인공지능
period	2026-06-01
ratio	100 (index, peak in your window = 100)
timeUnit	month

Shopping insights - one row per segment per period

dimension	segment values	what it tells you
category	overall	how demand for a whole category moves
keyword	your product keywords	which products are pulling demand
gender	female, male	who buys the category
age	10-19, 20-29, 30-39, 40-49, 50-59, 60+	which age bands drive it
device	mobile, pc	where they shop from

Real example from a single run on Korean fashion: 40-49 age band indexes highest, women index 3x men, mobile indexes 7x PC. That is a targeting brief in three rows.

Export as JSON, CSV or Excel, or pull from the API.

What people use it for

Market entry sizing - Before launching in Korea, see whether interest in your category is rising or falling, and who the actual buyer is by age and gender.

Ad targeting briefs - Age, gender and device splits per category tell you where to put budget without guessing.

SEO and content planning - Keyword seasonality by month or week, so you publish before the peak, not after.

Product and merchandising decisions - Compare keyword demand inside a category to see which product lines are heating up.

Competitive tracking - Put competitor brand names in as keyword groups and watch relative interest shift over time.

How to use it

1. Get a free NAVER API HUB credential at https://www.ncloud.com (Services > Application Services > NAVER API HUB) and enable the Data Lab APIs
2. Set start date, end date and interval (daily, weekly, monthly)
3. For search trends: add keyword groups. Each group can bundle synonyms that count as one line, e.g. {"groupName": "AI", "keywords": ["AI", "인공지능"]}
4. For shopping: add shopping categories by code, optionally shopping keywords, and pick which breakdowns you want
5. Run it, or schedule it monthly to build a demand history

Finding a category code - open any category on NAVER Shopping and copy the cat_id value from the URL. 50000000 is fashion apparel, 50000003 is digital and appliances.

Reading the numbers

DataLab returns a relative index, not absolute volume. Within each requested window the peak point is 100 and everything else is scaled to it. That means:

• Comparisons inside one run are meaningful (this month vs last month, women vs men)
• Comparisons across separate runs with different date ranges are not directly comparable
• To build a long time series, run one long window rather than stitching short ones

This is how NAVER publishes the data, and this actor passes it through without inventing precision that is not there.

Pairs with

Korean Price Comparison Scraper (what things cost) plus this actor (what people want) is a complete Korean e-commerce demand picture. Also works with NAVER Search Scraper for the qualitative side - what people are actually saying about a keyword.

FAQ

Do I need my own credential? Yes, and it is free. Your usage runs under your own quota.

How far back does data go? Search trends from 2016-01-01, shopping insights from 2017-08-01.

Why is the current month low? A partial month indexes low because it is not finished yet. Use complete periods for analysis.

Will it stay free? NAVER API HUB is currently free and states that a move to paid pricing will be announced in advance. Check the terms when you register.

Support

Need another breakdown or dataset? Open an issue on the actor page - issues are answered within 3 business days.