Analyzing competitors before entering overseas markets through SNS and e-commerce crawling.

Learn about the methods and importance of analyzing competitors using SNS and e-commerce crawling for overseas market entry. Accurately understanding the market through data is crucial for success.

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Analyzing competitors before entering overseas markets through SNS and e-commerce crawling.

New Market, Would You Enter Without Data?

I want to enter the North American market, but I don't know what local consumers want.


If you are preparing to enter the overseas market, you must have had this concern. Entering without information such as local consumer preferences, strengths and weaknesses of competitors' products, and market trends is no different from gambling based on intuition.


There are limitations to the conventional methods:

  • Commissioning market research companies costs millions of won

  • Received reports lack specific insights tailored to our products

  • Want to directly check local SNS or community reactions but face language barriers

  • Reading reviews of competitors' products one by one is overwhelming


Ultimately, you will end up making decisions based on limited information or spending excessive costs.



Directly Acquire Market Data through SNS + E-commerce Crawling

By using Hashscraper, you can directly collect market data from overseas SNS and e-commerce channels. By securing primary data, you can analyze what consumers are actually talking about and how they react to competitor products.


Example of Actual Crawling Data - Reddit Posts

{
  "Channel": "Reddit",
  "Subreddit": "r/Cooking",
  "Post Title": "Air fryer recommendations for a family of 4?",
  "Post Body": "Looking for an air fryer that can handle larger portions. Budget is around $150. What features should I prioritize?",
  "Author": "user_****",
  "Upvotes": "187",
  "Comments": "64",
  "Post Date": "2025-01-03"
}


Example of Actual Crawling Data - Amazon Competitor Reviews

{
  "Channel": "Amazon US",
  "Product Name": "Ninja Foodi 6-in-1 Air Fryer",
  "Brand": "Ninja",
  "Price": "$149.99",
  "Rating": "4.6",
  "Review Title": "Love it but takes up counter space",
  "Review Body": "Cooks everything perfectly and the basket is easy to clean. Only downside is it's bigger than expected. Make sure you have the counter space.",
  "Review Date": "2025-01-02",
  "Verified Purchase": "Yes"
}


From SNS, you can collect honest opinions and purchase considerations of consumers, and from e-commerce, you can gather information on competitor products' prices, features, and customer evaluations.



Use Case: Entry into the North American Small Kitchen Appliances Market by a Home Appliance Company

A domestic home appliance company was preparing to enter the North American small kitchen appliances market. In a fiercely competitive market for products like air fryers and blenders, it was crucial to accurately understand the needs of local consumers and the competitive environment.


Crawling Settings

  • SNS Channels: Facebook, YouTube, Reddit

  • E-commerce Channels: Amazon, Walmart, Costco, Target, Best Buy, Home Depot

  • Data Collection Period: Accumulated data over 3 years

  • Items Collected: Posts, comments, product information, reviews


Analyzed Items from Crawling Data

| 분석 항목 | 인사이트 |
|-----------|----------|
| SNS 대화 주제 | 소비자들이 중요하게 생각하는 기능, 구매 시 고려 요인 |
| 경쟁사 제품 비교 | 브랜드별 가격대, 주요 기능, 포지셔닝 |
| 리뷰 감정 분석 | 경쟁사 제품의 만족 요인과 불만 요인 |
| 구매 결정 요인 | 가격, 용량, 청소 편의성, 다기능 여부 등 우선순위 |
| 사용 패턴 | 북미 가정에서 실제로 어떻게 활용하는지 |


Quantitative Results

| 항목 | 수치 |
|------|------|
| 수집 데이터 | 수십만 건 |
| 채널 커버리지 | SNS 3개 + 이커머스 6개 |
| 시장 조사 비용 | 외주 대비 **75% 절감** |
| 분석 기간 | 3년치 소비자 트렌드 |


We were able to derive specific insights tailored to our product while significantly reducing costs compared to outsourcing market research.



Extracting Insights from Massive Data through AI Analysis

It is impossible for humans to read and analyze tens of thousands of reviews and social data manually. Hashscraper uses AI models to automatically analyze the collected data.


Example of AI Analysis Data - Review Analysis

{
  "Channel": "Amazon US",
  "Product Name": "Ninja Foodi 6-in-1 Air Fryer",
  "Review Body": "Cooks everything perfectly and the basket is easy to clean. Only downside is it's bigger than expected.",
  "Sentiment": "Positive",
  "Keywords": ["cooking performance", "easy to clean", "size"],
  "Categories": [
    {"category": "Performance", "subcategory": "Cooking Quality", "type": "Positive"},
    {"category": "Usability", "subcategory": "Cleaning", "type": "Positive"},
    {"category": "Design", "subcategory": "Size", "type": "Negative"}
  ]
}


Example of AI Analysis Data - Social Data Analysis

{
  "Channel": "Reddit",
  "Subreddit": "r/Cooking",
  "Post Body": "Looking for an air fryer that can handle larger portions. Budget is around $150.",
  "Sentiment": "Neutral",
  "Keywords": ["capacity", "budget", "family size"],
  "Categories": [
    {"category": "Purchase Intent", "subcategory": "Capacity", "type": "Primary"},
    {"category": "Purchase Intent", "subcategory": "Price", "type": "Secondary"}
  ]
}


AI Analysis Items

| 분석 항목 | 활용 방법 |
|-----------|-----------|
| 감정 분석 | 긍정/부정/중립 비율로 전반적인 시장 반응 파악 |
| 키워드 추출 | 소비자들이 자주 언급하는 기능, 불만 사항, 관심사 도출 |
| 카테고리 분류 | 성능, 디자인, 가격, 편의성 등 주제별 자동 분류 |
| 트렌드 분석 | 기간별 키워드 변화로 시장 트렌드 추적 |


If dissatisfaction with "cleaning convenience" is repeatedly mentioned in tens of thousands of reviews, that could be a point where our product can differentiate itself. Through AI analysis, such patterns can be quickly identified.



Other Use Cases


Entry into New Categories

When launching a product that didn't exist before, you can pre-assess consumer reactions to similar products or substitutes.


Monitoring Competitors' New Products

When competitors launch new products, you can quickly collect initial consumer feedback and formulate response strategies.


Localization Strategy Development

Consumer priorities vary by country. By comparing and analyzing crawling data by country, you can identify localization points.



Data Integration Methods

The collected data is provided in raw data format, and you can choose the integration method according to the situation.

  • Excel Download

  • Email Sending

  • API Integration — Integration with internal databases

  • DB Integration — Internal storage and long-term analysis of large data



Conclusion

Entering overseas markets is a battle of data. Companies that first secure information on what local consumers want and the strengths and weaknesses of competitors have an advantage.

Hashscraper handles crawler operation, maintenance, and monitoring. Even in cases of policy changes on overseas platforms or data collection errors, there is no need for direct response from the client.

Once set up, data will be collected regularly. By allocating part of the outsourcing market research cost, you can establish a continuous market monitoring system.



Start Now

With Hashscraper, you can automatically collect market data from overseas SNS and e-commerce channels.


If you need crawling from other overseas channels (Reddit, YouTube, Walmart, etc.), please contact us.


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