The business analysis function analyzes the data of this store and can help sellers review and understand the business situation of this store. Identify problems and correct them.
Global Consumption Time
As a global platform, AliExpress uses Pacific Time (GMT-8). We need to understand the traffic distribution time.
AliExpress time (GMT-8)AM11:00=BeiJing(GMT+8)AM3:00.
AliExpress time (GMT-8)AM11:00=Moscow (GMT+4)PM11:00.
AliExpress time (GMT-8)AM11:00=Rio de Janeiro (GMT-3)AM6:00.
In every big sale, from 3 am to 8 am Beijing time is the rest time for the on-duty staff. At this time, the Russian buyers have gone to bed and the Brazilian buyers have not yet gotten up. For global consumption time, you can refer to the time zone station.
Store profile analysis
1. Volume conversion profile
Data query and analysis are the main methods for sellers to understand store operations, especially to understand traffic and conversion data. , can help sellers respond to market changes in a timely manner.
2. Store transaction overview
The most important data to pay attention to in the store transaction overview is the number of successfully paid orders.
3. Store traffic source analysis
To analyze store traffic sources, you can check the traffic composition in the store. Analyze the proportion and trend of traffic from different channels to help sellers understand and optimize store traffic sources and increase store traffic.
3.1 “Others on the site” and “Activities” traffic sources
There are many sources of store traffic. Here we mainly analyze the two major traffic sources of “Others on the site” and “Activities”. “Other on-site” traffic cannot simply be understood as the traffic brought by related promotions. It includes in-site searches, category browsing, and store homepage visits for Russian sites and cat-Portuguese (referred to as cat-language) sites (second-level domain names). flow. The top 7 traffic sources of “Others within the site” are divided into two groups: Mandarin site search, Portuguese site category, and the homepage of this store. This store group page, Portuguese site keyword search, Russian site category Russian site recommended keyword search (non-natural search)
The source of associated promotional traffic does not appear in the TOP10 source ranking of “Others in the site”. Because its traffic sources are too scattered. “Huo: Guan Nei is a major source of store traffic, which is divided into activities that require registration and activities automatically recommended by the system, as well as activities recommended by some category channels
3.2 The influence of each traffic source channel on the store Contribution
Generally speaking, it is healthy when search and category traffic account for more than 60% of all store traffic. Since there is no distinction between search and category traffic for each store and general store, most sellers see The proportion of traffic coming from “others on the site” is very high, especially in small languages, with the exception of the wig industry.
Usually, events and through trains bring the highest proportion of new visitors, and are a powerful tool for attracting traffic to the store. .
From the perspective of average visit depth and bounce rate, visitors from natural search and category browsing are more likely to return due to different purchasing purposes. The depth of Yu Funtong is slightly insufficient, and the bounce rate is also high. Generally speaking, it is better than the traffic from activities and through trains.
If you want to analyze the decoration effects, you can check the ones in the last 30 days. We have done store renovations every day, and the changes in store traffic, visit depth, visit duration and bounce rate after the renovation are used to measure the effect of store decoration.
The average visit depth is explained below.
The average number of pages visited by visitors in the store each time, that is, the number of pages visited per person.
The average visit depth within a period of time is equal to the average daily visit depth, that is, The average visit depth per day.
Average visit time
The visit time is the length of time a visitor browses the store page in one visit. The average visit time is the average visit time of all users. Value.
Bounce rate
The bounce rate is the ratio of the number of visits to the store to the total number of visits per day. The daily average bounce rate is the average daily bounce rate.
Purchase rate
The purchase rate is equal to the number of visitors who visited the page who placed orders on that day. The total number of visitors to the page.
1. Own product analysis indicators
Exposure: refers to the number of search exposures, that is, the number of exposures of the product under search or category browsing.
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Views: refers to the number of times the product has been viewed by visitors
Search click-through rate: the proportion of the product being clicked after being exposed in a search or category, that is, the number of views divided by the number of impressions.
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Number of visitors: the total number of visitors who visited the product
Number of completed orders: refers to the number of successfully paid orders for the product within the selected time range and the number of risk control closures within the selected time range. The difference in the number of orders.
The number of buyers who successfully purchased the product within the selected time range.
The transaction amount: refers to the number of buyers who successfully purchased the product during the selected time. The transaction volume generated within the range.
The number of inquiries: refers to the number of times a visitor clicks on the product through the WantWant website.
The transaction conversion rate: refers to the buyers who successfully purchase the product. The ratio of the number to the total number of visitors is the number of buyers divided by the number of visitors.
Average residence time: refers to the average residence time of visitors browsing all detail pages of the product.
Number of times added to shopping cart: refers to the number of times the product has been added to the shopping cart by visitors.
The number of times added to favorites: refers to the number of times the product has been collected by visitors
No-Pay ratio: refers to the number of unsuccessfully paid orders for the product within the selected time range and the number of successfully created orders. The ratio of the number of orders.
2. Key points of product analysis
Product analysis refers to identifying defects in the products in the store based on various indicators and proposing solutions.
There are two main aspects of product analysis in own stores: hot product analysis and long tail analysis. Hot item analysis is a method of comprehensive and detailed analysis of products with the purpose of creating hot items; long-tail analysis is a method of using Excel functions to analyze all products except hot items.
3. Analysis case of potentially explosive products
Creating explosive products is a compulsory course for sellers. Sellers need to constantly optimize the basic factors that affect sales to attract consumers to purchase goods. To create a hit product, you need to at least improve the price advantage of the product, take high-quality and clear product pictures, and optimize the title description.
5. Analysis of traffic sources of popular products
For potential popular products, more exposure and more PV are the biggest needs. At this time, it is necessary to analyze the traffic sources of single products. , increase the traffic of each channel. Figure 8-37 shows the traffic sources of a certain style of military multi-pocket pants in the last 30 days: category browsing accounts for 35.16%, others on the site account for 30.69%, site searches account for 13.64%, direct access accounts for 9.85%, and favorites account for 4.18% % Shopping cart accounts for 3.08%, activities account for 2.19%, and total off-site accounts for 1.20%
The only thing missing here is the paid traffic P4P through train. This is an operational error and the seller needs to adjust. When the traffic of popular items is insufficient, the proportion of through traffic should reach about 30% to bring new customers to the store. The on-site search provides a good source of TOP10 keywords. These keywords can be added to the through list, which can also make up for the lack of search traffic sources for this product.
Participating in events is also a powerful way to create hot sales, but it varies by product and time. It is a good choice to participate in a Russian group purchase of products in the early stage. It can increase hundreds of orders at one time, create enough trust among customers, and win a relatively good search ranking. However, during the product growth stage, do not blindly participate in group purchases. The product will have a long lock-in period and a low probability of going online, which will shorten the product optimization time and even cause a reduction in various indicators.
6. Do you want to analyze the direction of traffic?
In fact, the direction of traffic from various sources is basically in a fixed proportion, that is, the bounce rate of natural traffic is relatively low, and the traffic direction goes to other places in the shopping cart. The proportion of pages, favorites, and order pages is relatively high. From the previous analysis of store traffic sources, it can be seen that the “other within the site” traffic sources are worthy of attention. The traffic of the two major sub-stations in Russia and Brazil is hidden here. If the “+” button does not appear in the “Others on Site” section, the time you can select is the last day.
If a popular product is not developed for people in a specific country, the country source of visitors to the single product should be consistent with the country source of visitors to the store.
7. Product long-tail analysis
The long-tail is relative to the hot-selling products. In addition to the traffic-draining products and hot-selling products, all products in a store can be called long-tail products. . Long-tail products can be analyzed by exporting all product data in batches. Each key indicator cannot refer to the key indicators of the top 10 in the industry because there is no comparability. The average of the top 10 long-tail products needs to be selected as a reference indicator.