What is Seahawks data? Seahawks data review

Basic Introduction

The company behind Haiying Data is Shenzhen Youlin Information Technology, which currently mainly provides big data product selection, data monitoring and other data analysis services to sellers on the four major cross-border e-commerce platforms: Amazon, Wish, EBAY and SHOPEE .

The biggest advantage of Seahawk is that almost all its functions are free, and a lot of data can be viewed without logging in, which is one of the main reasons why it attracts sellers.

Of course, the ultimate goal of the platform is definitely to make a profit. Haiying Data also has paid members, and the functions are definitely more than those of ordinary members. Paid members can view Viewing now (wish product traffic, small flame) data. Sellers can judge the hot sales and surge of products by accessing the average and increase of Viewing now.

Function Introduction

1. Product selection on Haiying Data Wish platform

Haiying Data is very popular among Wish sellers. Currently, the data captured by Haiying Data on the Wish platform is the most comprehensive among these platforms, and the data analysis is also more detailed and specific.

Haiying Data analyzes wish data mainly from three dimensions: product analysis, store analysis, and category analysis.

The product analysis column is divided into 8 categories, namely, hot-selling products, soaring products, hot-selling new products, soaring new products, and hot-selling and soaring products in overseas warehouses. For example, in the hot-selling product column, wish sellers can set the following parameters to accurately search for the data they need.

The store analysis page includes four subcategories: Store Hot Sales, Store Soaring Sales, Hot New Stores, and Soaring New Stores.

2. Amazon

1. Crawling scope: Clothing, Shoes & Jewelry category of the US site, top 40,000; categories of all other sites, top 20,000.

2. Special products: ASINs in branch categories are not captured; ASINs without first-level rankings are not captured. Only products with first-level category rankings in leaf categories are captured.

3. Capture effect: 80-95% of the variant ASINs within the capture range of each level 1 category can be successfully captured.

4. Crawl frequency: about once every 2 days.

5. Exception handling: If multiple crawls are actually performed on a certain day, the latest value will be used; if no crawls are performed on that day, the last actual crawl value will be used.

6. Product search can only query and display the variant ASIN data actually captured in the previous 7 days. (Assume that today is the 27th, and the previous 7 days are the 20th, 21st, 22nd, 23rd, 24th, 25th, and 26th.)

7. Text search, not case sensitive.

8. Search matching: title search, partial match; asin search, exact match; brand search, exact match; store search, exact match.

9. Add ASIN: If the ASIN is not recorded, use the ASIN to search directly, the system will automatically record the ASIN, and the data of the ASIN will appear within 2 days. If the first-level category ranking of the ASIN falls below 50,000, it will be automatically abandoned and no records will be captured.

* Shelf time: 50% of the ASINs on Amazon US have no shelf time. It is recommended not to use this function!

3. Ebay

1. Crawl scope: New, Buy It Now

2. Query scope: meet both conditions (Sold>0; not removed from shelves)

3. Crawl frequency: If Sold>0, crawl once a day; if Sold=0, crawl once every 2-3 days; all products of all stores are crawled once every 7 days.

4. Text search, not case sensitive.

5. Search matching: partial matching (title, item location, listing area search); complete matching (product ID, store/user name search).

6. Total number of units sold (sold), including offer sales; sales statistics and sales trend charts, excluding offer sales.

7. Sales data is calculated based on the natural day of the country where the site is located.

8. Assume that today is the 10th, the day before is the 7th, the 3 days before are the 5th, 6th, and 7th, and the 7 days before are the 1st to the 7th.

9. The category structure is based on the mobile app.

4. Shopee

1. Only products with sales volume greater than 0 in the previous 30 days or total sales volume greater than 0 can be queried and displayed

2. Sales data for the previous 30 days: real-time data, no lag. Provided by Shopee official API interface, timely and accurate. At some times, there will be no changes for several consecutive days (1-3 weeks).

3. Total number of units sold: This is the data after the buyer receives the goods and completes the order, which lags behind by about 10-15 days.

4. Text search, not case sensitive.

5. Search by product title, partial match; search by product ID, exact match; search by store name/merchant name, exact match.

6. Daily sales trend chart, sales forecast based on inventory changes. If the merchant changes the inventory, it will cause sales forecast errors, for reference only.

References