Where are our products being sold and at what price on which channels?
Online sales channels for brands are not limited to one. Our products are listed on dozens of platforms simultaneously, from open markets and department store malls to outlets, curated shops, and home shopping networks. The issue is that prices and selling locations vary for each channel.
- Prices differ for the same product code across channels, making it hard to identify the lowest price at a glance.
- Unsourced sellers offer products at lower prices, undercutting the lowest price.
- With thousands of channels and product codes, it is impossible for a person to check daily.
Checking channels one by one means it's already too late when you notice prices have dropped.
Collecting product, price, and seller information by product code per channel
By utilizing Hashscraper, you can collect our products from various sales channels daily based on product codes (SKUs). You can gather channel-specific selling prices, discount rates, and information on actual sellers.
Example of actual crawling data - Open market products
{
"SKU": "AB1234",
"Product Name": "스포츠 브랜드 여성 트랙탑",
"Channel": "오픈마켓 A",
"List Price": 119000,
"Sale Price": 81310,
"Discount Rate": "-32%",
"Seller": "○○아이앤",
"Business Number": "***-**-*****",
"Free Delivery": "Y",
"Product URL": "https://...",
"Collected At": "2026-07-06 14:35"
}
By comparing prices and discount rates across channels, you can identify who is selling the products based on the seller's name and business registration number. If an unsanctioned seller appears, you can detect it immediately.
Use Case: Monitoring a Global Sports Brand's Marketplaces
A global sports brand had its products listed on over 30 online channels in the domestic market. With prices varying across channels and unofficial sellers mixed in, they needed a way to manage the entire marketplace at a glance.
Crawling Setup
- Targets: Over 30 channels including open markets, department store malls, outlets, curated shops, and home shopping networks
- Data collected: Product code, product name, regular price, selling price, discount rate, seller (name, business registration number), shipping conditions
- Crawling frequency: Daily (regular collection per channel)
Analyzable data from crawling
| Analysis Item | Utilization |
|---|---|
| Lowest price per channel | Daily check on which channel offers the lowest price based on product codes |
| Price policy violations | Identifying channels and sellers selling below the Minimum Advertised Price (MAP) |
| Detection of unofficial sellers | Identifying the name and business registration number of sellers not in the official distribution network |
| Price discrepancies between channels | Monitoring price differences and trends across channels |
Quantitative Results
| Item | Figures |
|---|---|
| Channels collected | Over 30 online channels |
| Monthly collection volume | Hundreds of thousands of entries |
| Collection frequency | Daily |
With channel information consolidated by product code, they could immediately identify channels with reduced prices and unfamiliar sellers.
Consolidating Different Product Names per Channel Using AI Mapping
Product names vary across channels. The same product may be listed with different names like "W SST Loose Track Top" or "Women's Original Jersey SST." Hashscraper uses AI to map these varied listings to the same product code (SKU).
What AI mapping does
| Process | Description |
|---|---|
| Product code mapping | Consolidating different product names from each channel under the same product code (SKU) |
| Industry filtering | Automatically excluding unrelated products from other brands mixed in search results |
| Seller normalization | Consolidating different representations of the same seller into one |
With data organized in this way, channels can be accurately compared based on "our product standards."
Receiving data and 'viewing' that data are different tasks
Raw data is not a finished product in itself. To effectively utilize the data on channel prices and sellers collected daily, it ultimately needs to be processed within the company. Running Excel pivots, creating graphs, and compiling weekly reports are tasks left to the responsible personnel. Even with automation in data collection, the task of 'presenting it nicely' still falls on humans.
There is hidden pressure on the responsible personnel. Receiving data and turning that data into weekly visual materials are separate tasks, and the time spent on the latter is significant. Even if BI tools are implemented, understanding the data structure and designing dashboards require additional resources.
Hashscraper can assist up to this final stage. The collected price and seller data is structured into visual dashboards that show channel-specific price trends, notify about unofficial sellers, and provide summaries by product code. By also collecting reviews (VOC) from the same channels and adding sentiment and keyword analysis, you can see "at what price products are being sold" and "how they are being evaluated" on a single screen. Operational departments can simply open the organized screen daily without the need to reprocess the data.
(The brand in the example currently utilizes raw data collection. Visualizing the dashboard is the next step based on the same data.)
- Product and price monitoring dashboard: Price & Product Monitoring
- Review and VOC analysis dashboard: Review & VOC Data
It can also be utilized in these cases
New product launch monitoring — Track where and when new products are listed and at what prices.
Parallel import and gray channel monitoring — Identify quantities and sellers operating outside the official distribution network.
Comparing prices of competing brands — Collect price ranges of competitor products in the same category across channels.
Conclusion
A brand's online prices move not only on their own platform but simultaneously across dozens of channels. By integrating data on who is selling at what price on which channel, you can establish a basis for pricing policies and distribution management. By extending this to visualization, the threshold for utilization is lowered.
Hashscraper handles crawler operation, maintenance, and monitoring. If there are changes in channel policies or data collection errors, the client does not need to respond directly. Once set up, data from dozens of channels is organized by product code daily.
Get Started Now
With Hashscraper, you can automatically collect data on our products, prices, and sellers from various sales channels daily and expand to include review analysis and visualization dashboards.
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