The so-called data analysis is to think about a bunch of messy information in a logical way and extract the patterns among the hidden information.
For the AliExpress platform, data is the report card provided by the platform to sellers. Platforms with good grades will allocate more resources. At the same time, the data is also a questionnaire given to buyers by the platform, which guides the market direction of the platform based on the results. From the perspective of market analysis, every aspect of product selection, creation of popular products, express trains, marketing activities, and operations is inseparable from data. Data is the basis for sellers’ operations.
Through data analysis, the product layout, titles and related optimization strategies can be adjusted. Data analysis is also the most scientific and effective way to improve the store. What exactly does the so-called “data” refer to? How do we analyze it? Next, we will introduce it in detail.
1. Real-time Storm
Real-time storm is divided into two categories: real-time overview and real-time marketing. Through real-time storm, you can understand the changes in store traffic in a timely manner and judge the direct effects of product information optimization, marketing activities and other adjustments. You can also adjust product upload time, customer service working hours and through-train delivery time during periods of concentrated traffic.
What useful data does the real-time storm provide us? In fact, visitor access behavior is different in each industry. For example, in terms of access time, if the store sells European and American clothing, visitors will basically arrive at 9 a.m. U.S. time The number is highest between 11:00 and 11 noon. However, after consulting several sellers selling 3C and furniture and daily necessities, the number of visitors is basically the highest between 8 pm and 10 pm.
In addition, under the real-time analysis, there are also the exposure, number of visitors, number of transactions, number of shopping carts, and number of collections for each product. I think this is the core store we need to pay attention to in this column. Here are a few questions for everyone to think about:
(1) What is the reason for having exposure but no visitors?
(2) What is the reason for having visitors but not many orders? What is the reason?
(3) There are visitors, exposure, and collections, but no one places an order. What is the reason?
(4) The collection volume is very high, why is there no one? Place an order?
(5) There are many shopping carts, but why are there not many orders?
(6) What is the reason for the above problem? Have you analyzed the reason? Have you compared the products of your peers and why they are better than ours?
If you analyze these issues carefully, you will understand the reasons. It’s just that many people are inert and unwilling to make changes.
1. Business analysis
Regional distribution of visitors
The store initially focused on the regional distribution map of visitors to create a portrait of the user population and segment the customer groups. Visitor areas are distributed in the United States, Russia, Ukraine, Japan, Chile, Mexico, Israel, Spain, the Netherlands, Estonia and other countries and regions.
Because the store style is biased toward European and American countries, there are naturally more visitors from the United States. Many people do not have a clear store style, which results in the store having no characteristics. Currently, the platform advocates that the store should be small and beautiful (professional). In this way, more attention should be paid to the overall style of the store. Characteristics of grocery stores: Price competition is the main focus and visitor return rate is low. The characteristics of small but beautiful stores: brand + service, high user stickiness. The visitor geographical distribution function is mainly to facilitate sellers to monitor the customer countries of their store products. If the store style is biased toward Russian customers, the only criterion for determining the success of the store is the proportion of visitors.
2. Transaction analysis
The transaction analysis function of AliExpress stores consists of two parts: transaction overview and fluctuation analysis
(1) Transaction overview.
Store’s industry ranking: AliExpress will rank the store based on the amount of successful payment within the last 30 days among its peers and the same city.
It is worth noting that the current industry ranking has been changed to the second-level industry. In the old version of the store profile, it was a first-level industry. However, because the first-level industry is relatively broad in many cases, it is split into the second-level industry. The industry’s positioning of dimensions is relatively specific and reasonable. At the same time, the statistics of the amount of orders closed due to risk control have been adjusted to different levels, and there will not be much difference between the old and new versions.
The transaction profile is composed of a set of formulas: payment amount = number of visitors It can be derived from these three sets of data, and in this way we can know that if we want to increase the payment amount of the product, we can achieve the purpose of increasing the payment amount by increasing the number of visitors, payment conversion rate, and customer unit price.
For example, if the number of visitors to a store is increased by 20%, while the payment conversion rate remains unchanged, the payment amount will also increase by 20%. Of course, how to improve data can be determined based on the individual circumstances of each store to determine the focus of our operations. To increase the number of visitors, payment conversion rate or customer unit price, their operating strategies are different. Visitor volume, simply put, is traffic. We can attract traffic through various methods such as Facebook, P4P, and alliances. The browsing conversion rate is generally improved through marketing to old customers and issuing coupons to new customers. The general marketing method for customer unit price is to do relevant point of view marketing or corresponding coupons.
(2) Transaction fluctuation analysis.
First of all, fluctuation analysis is only needed based on a certain order volume. It is recommended to conduct fluctuation analysis when there have been more than 30 payment orders in the last 30 days. Otherwise, the fluctuation is greatly affected by a single buyer and order, and the reliability of the analysis results is not high when there is less data.
Secondly, when the fluctuation exceeds a certain range, it is necessary to guide the analysis of the reasons for the fluctuation. The overall fluctuation within 10% does not mean that there are no abnormalities. Based on the actual situation of the seller’s store, guidance will be given if a certain value fluctuates by more than 10% in each dimension. For example, if the overall fluctuation is 3%, but the US fluctuates by 15%, it is recommended to analyze the fluctuation of the country (US).
The reasons and ideas for analyzing transaction fluctuations are as follows:
Under the premise that there are fluctuations, first find the reasons for the store itself, and then consider the reasons for the entire industry. If the direction is wrong, it is easy to This leads to misunderstandings in the subsequent analysis and prevents us from making relevant operational strategy adjustments.
If the reason is the store, you can find the reasons for traffic, conversion, and customer orders through formulas. 3. Through dimensional dismantling, we can find the main reasons such as country, platform, product, etc. Generally, the ultimate goal is to find the product. You can also directly find the reason through product dimension segmentation. The specific reasons vary from store to store.
Single-dimensional dismantling analysis, using the transaction formula to find the reasons for that dimension.
Store traffic sources
Store traffic sources can view the traffic composition in the store, the traffic proportion and trend of each channel, which can help sellers understand the sources of store traffic and how to optimize and increase store traffic. Sellers can view traffic sources and distribution of traffic sources for the longest period of the last 30 days, and can view the trends of each channel in the last 30 days in detailed data reports. Sellers can also customize the time to select a day within the last 30 days to view the performance on that day, which is convenient for sellers to view the performance after performing traffic diversion operations on a certain day (for example: participating in activities, paid promotions, optimizing title keywords, etc.).
Traffic involves two words:
PV (Page View): Visits, that is, the number of visits or clicks to the page.
·UV (Unique Visitor): Independent visitor, a computer client that visits your website is a visitor.
If the site search does not rank in the top three, it means that the store is sub-healthy.
The following is a detailed introduction to the traffic sources of each channel:
(1) Direct access: Customer A bought the product in the store, was very satisfied after receiving it, and sent the product link to his friend B , Customer B purchases directly through the link.
(2) Others on the site: such as associated marketing traffic, etc. (3) On-site search: the proportion of buyers directly clicking on product pages through keyword searches. Generally, the customers who come through this method are very targeted. For example, if a buyer wants to buy a chiffon dress, he can open the AliExpress homepage and directly enter the keyword chiffon dress in the search box. If he sees a suitable dress on the first page of the page, he will place an order immediately. (Traffic source: site search)
(4) Category browsing: Most buyers browse unconsciously and have no target for the product. This type of customers have a relatively high bounce rate for stores. For this type of customers, we need to focus on optimizing product images and detail pages. For example, a buyer wants to buy himself a pair of boots but isn’t sure which one looks good. Open the homepage and select the category CATEGORIES – Bag&Shoes – Men’s boots. If you like a shoe, place an order immediately. (Traffic source: Category browsing)
(5) Activity: Buyers have nothing to do, go to AE and take a look. When you enter the homepage, you will see the activity poster saying: Super Deal, Up to 99.99% of (Super deal, discount up to 99.99%), the straw hat is priced at US$0.1 after discount, hurry up and grab it. (Traffic source: promotional activities)
(6) Through train: Pay-per-click traffic diversion method.
(7) Favorites: I have collected several products from the store a few days ago. It is almost “Double 11”, so hurry up and see if there are any discounted goods. Go to AE and click on the favorites to browse the products. . (Traffic source: Favorites)
(8) Shopping cart: The buyer visited the store and found several good products and added them to the shopping cart. When checking out, he found that the money was not enough or he was not sure yet. After placing an order, you can click on the products from the shopping cart. (Traffic source: shopping cart)
(9) Off-site totals: If you are used to using Google, you can search directly on Google. Off-site totals are usually through AliExpress affiliate marketing or your own off-site promotion, such as Facebook, EDM, etc., here you can test our off-site promotion capabilities.
Different traffic conversion rates are different. They can be sorted from high to low according to the conversion rate: Activities (cheap) >Direct visits (old customers) >Site search>Through train>Site External promotion (SNS).
4. Store decoration
To analyze the decoration effect, you can check which days in the last 30 days have been decorated, and the store’s traffic, visit depth, visit duration and Changes in the bounce rate are used to measure the effect of store decoration.
The function of decoration is only on the homepage of the store. The general visitor access habit is: enter the product page through the search function. If you are interested in the product, you may go to other product pages or the store homepage to see the next product. This cycle continues. The store decoration is a bridge from the first product to the second product in the store, which is quite important.
5. Product analysis
Through product analysis, sellers can often check product exposure, page views, number of visitors, number of shopping carts added, transaction conversion rate, number of orders, etc., and occasionally Take a look at the product collection. Sellers need to analyze, think about the problems reflected by these data, and think about the logical mapping that these data can bring.
“Product Analysis Interface”, the product performance ranking can not only be analyzed from the time and industry dimensions, but also the data can be viewed from the country dimension. The new advanced search function allows for more flexible filtering and analysis of product data, and the advanced search function is expanded.
AliExpress product traffic source and destination analysis can help sellers understand the source and destination of popular product traffic in their stores, as well as the traffic brought by product investment P4P (Proactive network Provider Participation for P2P). This function provides sellers with data analysis results for the last 15 days. Sellers can also check the source and destination of the top products with the most views in the last 30 days. At the same time, product analysis also provides data preview and download functions. Sellers can download data to local for analysis.
Through destination analysis and source details, sellers can be guided in the direction, help summarize experiences and problems, and obtain actual data support for precision marketing. Below the product analysis, there is also detailed data on each product’s exposure, number of visitors, number of orders, number of shopping carts, and number of collections. This is the core point that we need to pay attention to in this module.
3. Industry Intelligence
Industry intelligence is divided into industry overview and blue ocean industries.
1. Industry Intelligence – Industry Profile
The industry profile includes three aspects: weekly data, monthly data and quarterly data, and contains three dimensions: industry data, industry trends and industry countries. Generally, this tool is mainly used to analyze the current general trends of the entire industry. For example, what products do we need to pay attention to in summer? We can first take a look at the situation of chiffon shirts.
After selecting, click the “OK” button to see whether the entire industry is currently in an upward or downward trend. The average number of visitors in the last 90 days accounts for 20.32%. This ratio is calculated based on the product. For comparison, the category of chiffon tops is women’s clothing. In other words, chiffon shirts account for more than 20% of visitors in the entire women’s clothing industry, and one in five people wants to buy a chiffon shirt. Let’s look at other categories under women’s clothing, such as the data under the jacket/coat industry.
In the category of jackets and coats, although the proportion of visitors is about the same, various data such as transaction volume and pageviews have begun to decline. After all, it is summer. If you want To improve store data in the near future, you should choose trending products.
2. Industry Intelligence 1 – Blue Ocean Industry
Blue Ocean refers to an unknown market space that needs to be developed. Blue ocean industries refer to those industries where competition is not yet high but where buyer demand is high. Therefore, the blue ocean industry is full of new business opportunities. The platform provides us with some blue ocean industries for reference.
Under the blue ocean industry, there are also blue ocean industry subdivisions, where you can filter to find blue ocean industries in specific industries.
View Industry Details”. You can view relevant data, trends and country distribution of the industry.
3. Product Selection Expert (select products through data analysis)
Product selection experts take the industry as the dimension and provide data on hot-selling products and popular search keywords in the industry, allowing you to view a large amount of hot-selling product information and analyze the keywords searched by buyers from multiple angles. You can use the product selection experts. The provided content adjusts the products and optimizes the keyword settings.
The product selection expert is specifically divided into three sections: hot sales, hot searches, and trend trends. Among them, the trend trend platform has been temporarily cancelled. Graphics are used to mark data relationships, which is more intuitive. After determining what products are uploaded to the store, sellers can use this tool to quickly know which products are currently hot in the industry.
Click on the circle representing the industry. , you can enter the detailed sales analysis of this industry. For the blouse industry, enter the blouse sales detailed analysis interface, which includes three aspects: TOP related products, TOP hot-selling attributes and hot-selling attribute combinations. Through the analysis of these aspects, sellers can analyze the attributes based on the attributes. Select products based on combination and supply.
Through the above analysis, we can summarize that: the material is polyester, the sleeve length is full, and the regular style is the most popular product. Easily find marketable products. Similarly, through hot searches, we can also understand the keywords and attributes that customers have recently searched for.
4. Search word analysis
The key to product selection. The word method is very simple, a combination of “hot search words + soaring words + zero less words”, which can fully take into account the user’s search habits
1. Search word analysis
Search words can be used. Collected through the following channels: Data Zonghengyi-search word analysis; cross-border e-commerce websites such as Ebay, Amazon, and Wish; using tools such as Watch editem and Google Adwords; search engine word selection; platform buyer homepage and search page.
2. How to use data analysis to write titles
Sellers can download the industry’s raw data (Excel table) for the last 30 days in hot search terms, because the data in the downloaded Excel table is text For formatting, you must first convert it to a number. Select any cell with a number, press Ctrl + A to select the entire table, and then click the exclamation point in the table to convert the table to a number in Excel.
Insert a column of “Transaction Conversion Index” into the table. Multiply the search index by the transaction conversion rate to get the transaction conversion index.
Sellers can choose titles suitable for their products according to the sorting in the table. Keywords (high transaction conversion index and relatively small competition index). It is generally recommended that you focus on the search index and transaction conversion rate. The higher the search index, the better the current product market in this category. The transaction conversion can summarize the competition from the side. Number of sellers. We can try to find products with high search index but relatively low competition index.
Sellers need to pay attention to avoid “brand words” when selecting words (whether the keywords are marked Y under the original brand words). Try searching for the filtered words on the main page to see Whether the match is suitable for your product. When writing product titles, you should also pay attention to the following points:
(1) It is better to use the plural form of singular and plural words.
(2) Some words that are not English but have English letters can be placed at the end of the title as traffic words.
(3) If you don’t know what some words mean, you can search to see if they belong to the category of your product.
(4) The first half of the title should clearly express the product, otherwise it will be useless. Only the first half of the title is displayed, which affects the click-through rate.
(5) The order of various words can be adjusted, but try to make the title read smoothly.
(6) Some traffic words can be filled in the custom attributes. Related terms are explained as follows:
Exposure: refers to the number of times a product is seen by buyers on the search results list page and the browse list by category (the number of times it is displayed on the web page).
Views: refers to the number of times buyers click to enter the detailed product description page and view the product (the number of clicks on the web page).
UV: Unique Visitor, the number of unique visitors, an independent IP that visits the store is a visitor.
PV: Page View, page views or clicks. PV/UV: average visit depth will be calculated every time the user refreshes. The larger the value, the longer the buyer stays on the page and the greater the purchase intention. powerful. Search popularity: The corresponding index obtained by data processing on the number of people searching for this keyword. Search index: The corresponding index obtained after data processing of the number of searches for this keyword. Click-through rate: The number of times you click to enter the product page after searching for this keyword.
Transaction conversion rate: the transaction conversion rate brought by keywords.
Competition index: The result of indexing the supply and demand ratio.
Supply and demand ratio: the maximum number of products exposed to keywords every day during the selected time period/the average daily search popularity during the selected time period. The larger the value, the more intense the competition.