Managing becomes difficult as the number of stores increases
When the number of stores exceeds 50, it becomes difficult to check the sales and reviews of each store individually.
Running a franchise headquarters leads to such concerns. Checking the sales and reviews of each store on platforms like Baedal Minjok, Coupang Eats, and Yogiyo by going into the admin page, reading reviews, and organizing them in Excel. As the number of stores increases, the time spent on this simple repetitive task also increases.
As a result, the following problems arise:
- It is difficult to grasp the sales status of each store at a glance
- Customer complaints may go unnoticed until later
- Unable to compare which stores are doing well and which ones have issues
- Lack of data to provide feedback to franchisees from the headquarters
When the number of stores is small, it can be done manually, but as the scale grows, a system is needed.
Automatically collect data from all stores through delivery platform crawling
By using Hashscraper, you can automatically collect sales and review data for each store from the delivery platform admin page.
Actual Crawling Data Example - Sales Data
{
"Platform": "배달의민족",
"Store Name": "OO점",
"Date": "2025-01-06",
"Order Count": "127",
"Sales Amount": "1,847,000",
"Avg Order Value": "14,543",
"Cancel Count": "3",
"Cancel Rate": "2.3%"
}
Actual Crawling Data Example - Review Data
{
"Platform": "배달의민족",
"Store Name": "OO점",
"Rating": "4",
"Review Body": "맛은 좋은데 배달이 좀 늦었어요. 40분 걸렸습니다.",
"Menu": "닭꼬치 세트",
"Review Date": "2025-01-06",
"Owner Reply": null
}
The sales and reviews for each platform and store are organized in the same format, allowing the headquarters to grasp the overall situation at a glance.
Use case: Integrated management of F&B franchise headquarters' stores
A domestic F&B franchise headquarters was operating dozens of stores nationwide. By manually aggregating sales and reviews for each store from three delivery platforms, the staff spent a considerable amount of time on simple tasks throughout the day.
Crawling Settings
- Target Platforms: Baedal Minjok, Coupang Eats, Yogiyo
- Items to Collect: Store sales, order quantity, cancellation rate, reviews
- Crawling Frequency: Once a day
- Target Stores: All stores
Analyzed Items from Crawling Data
| 분석 항목 | 활용 방법 |
|-----------|-----------|
| 매장별 매출 비교 | 실적 우수 매장과 부진 매장 식별 |
| 일별·주별 매출 추이 | 매출 증감 요인 분석, 프로모션 효과 측정 |
| 취소율 모니터링 | 취소율 높은 매장 조기 발견 및 원인 파악 |
| 리뷰 감정 분석 | 고객 불만 요소 파악, 매장별 서비스 품질 비교 |
| 사장님 댓글 현황 | 리뷰 응대율 체크, 미응대 매장 알림 |
Example of AI Analysis Data
{
"Platform": "배달의민족",
"Store Name": "OO점",
"Review Body": "맛은 좋은데 배달이 좀 늦었어요. 40분 걸렸습니다.",
"Sentiment": "Neutral",
"Keywords": ["맛", "배달 지연", "시간"],
"Categories": [
{"category": "Food Quality", "subcategory": "Taste", "type": "Positive"},
{"category": "Delivery", "subcategory": "Speed", "type": "Negative"}
]
}
Achievements
- Significant time savings in aggregating sales and reviews
- Securing grounds for feedback from the headquarters through store performance comparisons
- Improvement in service enhancement speed by early detection of customer complaints
The collected data is summarized into weekly reports to share with franchisees, and support from the headquarters is provided to underperforming stores.
Other use cases
Monitoring response to new menu items
By analyzing the frequency and response of mentions of new menu items in reviews after their release, decisions on whether to adopt them as regular menu items can be made based on data.
Measuring promotion effectiveness
Comparing sales changes by store during discount or coupon event periods can help identify which promotions are effective.
Monitoring competitor brands
Collecting reviews from competitor brand stores can help identify factors that satisfy or dissatisfy customers and establish differentiation strategies.
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
- DB integration
Summary
As the number of stores increases, manually managing delivery platform data has its limitations. By setting up crawling, the sales and reviews of all stores are automatically collected daily.
Hashscraper handles crawler operation, maintenance, and monitoring. There is no need for the headquarters to directly respond to platform policy changes or collection errors.
Managing stores based on data allows for early problem detection and rapid response.
Start now
With Hashscraper, you can automatically collect and analyze delivery platform sales and review data.
Go to Baedal Minjok Review Collection Bot
If you need sales data collection or crawling for other delivery platforms, please inquire.
