All Collections
Case studies
๐Ÿ‡น๐Ÿ‡ญ Size consumer interest for skincare products in Thailand
๐Ÿ‡น๐Ÿ‡ญ Size consumer interest for skincare products in Thailand
Matthieu Danielou avatar
Written by Matthieu Danielou
Updated over a week ago

Goal is to understand trending beauty brands & product categories in Thailand:

  1. Commonly searched health and beauty products categories in Thailand

  2. Top 10-15 trending products in each category

  3. Trending brands in Health and Beauty category

  4. Trending Korean beauty products in Thailand

Get lists of product categories from chatGPT suggestions

Prompt your request such as 20 categories of skincare, in thai.

It could be also 20 categories of pharma products, in thai.

Request Google suggests for each category

Each category found with chatGPT can be augmented with additional search queries provided by Google. This suggestion method gives you very close search queries in terms of semantics.

Please make sure that attach a label to your queries before importing them into your project.

Once imported, each query suggested by Google should get a label. These labels can also be stored in any column - like Products, Categories or any other you want to create.

Get lists of brands from chatGPT suggestions

Use another prompt like top 30 skincare brands in Thailand, in thai.

This could be also top 50 skincare brands sold in retail, in Thailand, in thai.

Make sure to fetch brand names in English as well

Concatenate brand & product queries with Combine

Combining brand names & unbranded queries is a great way to test associations between brands and specific categories, in consumers' mind. Like testing which brand between Estee Lauder & L'Orรฉal is the most linked to 'beauty serum' by US consumers.

You can do the same thing by combining list of product categories (column A) and list of brands (column B).

Add labels automatically by selecting 'Show rules'.

When selected, all combined expressions will be attached to labels referring to the brand or the category they were made of;

Once added, these 1040 queries are properly labeled.

Detect trending brands & products at national scale

Go to Insights module from the left-side panel to get access to trends in space & time.

Share of volume tells you which brands or categories are top-of-mind in online searches.

Trending topics provides lists of brands or products that are much more searched in 2023 compared to previous years.

Spot Thai regions with outliers in consumer expectations

The local search section tells you whether consumers think the same way in all major states (or regions, or cities).

Local affinity is a metric revealing search volume for 100k local population. It is a great method to detect local markets with different consumer behavior.

In this specific example, Oriental Princess is the leading brand mentioned in online searches. But Kiehl's is a brand with much higher awareness (given the population) in states such as Nonthaburi or Samut Prakan.

Did this answer your question?