1. Key points of AliExpress data analysis

AliExpress seller backend provides a “data vertical and horizontal” analysis tool. Sellers can not only analyze the data of their own stores, but also understand the status of the entire industry.

Real-time storm. You can see the real-time traffic situation of the store, which is very useful when the store is doing promotional activities.

Traffic analysis. You can see the detailed traffic sources and destinations of this store, including store traffic sources, traffic paths, new and old visitor sources, each page data and advertising data monitoring, and you can distinguish between the App side and the non-App side. . Competence Diagnosis. Through a horizontal comparison of the past data of this store and the data of other stores in the industry, various capability indicators of store operations are reflected, including comprehensive capabilities, conversion capabilities, traffic drainage capabilities, product capabilities, marketing capabilities, service capabilities and platform rule capabilities.

Real-time storm data is updated every five minutes, and other module data is updated once a day, all based on US Pacific Time.

2. Key points of Amazon data analysis

In the Amazon backend data report, business reports and inventory reports are the key data that sellers should pay attention to. The business report is the store’s sales data. The inventory report mainly contains two data: self-shipped inventory data and FBA data. FBA is the abbreviation of Fulfillment By Amazon, which refers to the dropshipping business provided by Amazon.

Amazon data analysis can refer to the market trend report, customer behavior analysis data table, geographical location data analysis table, order sales data table, store operation data table, and customer review data table. Commonly used terms in reports are as follows

·Page Views: The total number of clicks on the sales page within the selected time range.

·Page Views Percentage (specific page traffic ratio): the proportion of page traffic that has a specific view of a certain SKU/ASIN.

Sessions (number of browsing users); the number of users who have browsed the sales page within 24 hours. The same user is only counted as one user no matter how many times he clicks. It is very worthy of reference.

SalesRank (sales ranking): The Amazon ranking of the product in this category. There are many influencing factors in this ranking. What is shown here is the real-time ranking after internal calculation.

Ordered Product Sales: The total sales of the products sold in the order. Calculated as the sum of the number of sales on the order multiplied by the sales price.

Units Ordered: The number of items sold in the order. For example, in an order, a customer may buy three items, so the number of items sold is 3.

Average Offer Count (average available product pages): The average number of available product pages within the selected time range.

Order Item Session Percentage (percentage of users who place orders): the percentage of users who place orders among browsing users.

Unit Session Percentage (sales number user conversion rate): The proportion of users purchasing goods after browsing, if it can reach 7%, it is a good figure.

Average Customer Review (average product review rating): The overall average product review rating, displayed in a five-star rating.

Customer Reviews Received (number of product reviews); the total number of product reviews a product has received, regardless of whether it is a positive or negative review, is calculated together.

Negative Feedback Received: The total number of negative reviews received, that is, the total number of negative reviews.

Received Negative Feedback Rate: The proportion of negative reviews The ratio of the total number of reviews, that is, the number of negative reviews divided by the number of feedback.

A-to-z Claims Granted: The number of A-to-z claims received, preferably none.

In addition, you can also use data analysis software, such as Bestseller, a software for viewing hot-selling products, Hot New Releases, a software for discovering hot-selling products in categories, and Most Wished, a software for hot new products such as Movers and Shakers. Gift Ideas, the best-selling ranking software of the day

3. Key points of eBay data analysis

There are 10 data in the eBay store traffic report including the number of store visitors, the buyer’s stay time and other store-related data. Traffic data information about the page and how buyers get to the store and product pages.

All store pages, including custom pages, custom category pages and search results pages. ·Various forms of item listings, including auctions, fixed prices, and long-term listings of store items.

Other eBay web pages related to sellers, including “Your Other Items”, “Credit Rating Profile” and “My Profile”. Certain data changes in the eBay platform will affect product sales. Sellers need to pay attention to the following types of data.

Recent sales records (for “priced products”): The more recent sales records a product has, the more exposure it will gain. Products that are relisted for the first time also retain recent sales records

Seller Rating (DSR): including product description, communication, shipping time, and shipping costs. Products from Top Rated Sellers are generally ranked higher.

Buyer satisfaction: There are three criteria for consideration, namely the number of negative reviews, the number of DSRs of 1 and 2 points, and the number of INR/SNAD complaints

Related to the “title” of the item Degree: the degree of matching between the search keyword entered by the buyer and the title and keyword of the final transaction.

After collecting data on the eBay platform, data analysis can be carried out from the following points. ·Market Capacity Analysis

Use the total monthly transaction value of similar products to estimate your market share. ·Auction transaction ratio

Sellers can compare whether their auction transaction ratio is higher than the average among similar products. If it is lower than the average, they need to find out the reason.

The optimal auction method

Which auction method is better? Set a reserve price or use a fixed price? Analysis of promotional effects of optional special functions

Promotion has costs. Which promotion method can bring you the greatest benefits? Does it increase the transaction ratio? Does it increase the transaction price?

Optimum auction start date

Is it easier to complete a sale if the auction starts on Saturday than if it starts on Monday? Is the transaction price higher? Optimal Auction Ending Period

What time period can end the auction to achieve the highest transaction ratio or highest transaction price?

Number of days to upload the product

The number of days to upload the product is 1 days, 3 days, 5 days, 7 days, 10 days. The most commonly used one is 7 days, but is it best to choose 7 days? In fact, different products have different properties. For some popular products, choosing 1 day is enough. It is enough, but for some items such as antiques, it is better to choose 10 days.

Which category sells best

When a product can be placed in multiple catalogs, the product should be placed in the catalog with a high transaction rate. If the transaction rates of both directories are relatively high, you can use the dual directory function.

Market competition

You need to understand how many sellers are selling similar products and how much market share the top 10 sellers hold.

4. Key points of Lazada data analysis

1) Check whether the product price is competitive

When “Uncompetitively Priced” appears in the manage product option column of Lazada Seller Center ”, it means that the product price is not competitive and the price needs to be lowered. Use the “All” filter in “Product Overview” to see if the product is priced competitively.

Use the “Uncompetitively Priced” filter to focus on all items that are not priced competitively. Sellers can regularly monitor prices in Seller Center and make adjustments to product prices.

2) Increase sales from a data perspective

The number of SKUs is directly related to the exposure and traffic of the seller’s store. The greater the number of SKUs, the better it can meet customers’ shopping needs. Effectively achieve the traffic diversion effect (it is better to upload multiple SKUs for hot-selling categories). By searching for the total number of SKUs in the top categories for keywords, you can see the proportion of the entire category on the platform.

For hot-selling products, it is recommended that sellers reserve inventory and need to check and update the actual inventory quantity in real time. 3) Rating from a data perspective

In Lazada’s rating performance, seller store ratings are no longer based on evaluation, but on-time delivery rate, on-time arrival rate at the sorting center, order cancellation rate, and returns These KPI indicators are used to calculate performance ratings.