Today, I will talk about which indicators e-commerce should focus on, and how to analyze these indicators.
Generally speaking, in the operation module, what needs to be focused on is the drainage and conversion of new users, as well as the activation, retention, repurchase, and loss of old users.
01 drainage
Simply put, drainage is to attract people who have never bought our products to buy our products.
1. Weekly distribution of user page views
The main purpose of analyzing this indicator is to find out the traffic rules of different dates and time periods, and to adjust corporate services and promotion activities accordingly.
For Internet companies, traffic data is often related to work weeks. In this regard, we can first macroscopically calculate the comparison of the total platform traffic histogram data from Monday to Sunday. First of all, we can carefully observe the data on working days and non-working days, and find that the platform traffic on weekends is higher than that on working days, which is a relatively common phenomenon in the Internet industry.
After mastering the weekly distribution of user traffic, we have a general promotion direction. The user group is larger during weekend breaks. User is active.
Then we can proceed to the next step of thinking, how to formulate the promotion time of our activities on weekdays and weekends?
Some students may think that activities throughout the day are fine, and there is no need to pay attention to the specific activity time. However, for the Internet industry, the promotion fee for each time period is relatively expensive. We can completely analyze the user traffic trends on weekdays and weekends, carry out targeted time period investment promotion, and obtain to more users.
The first is the statistical distribution of traffic during the time period of the working day. We use the FineBI tool to draw a map by time period to obtain the traffic distribution diagram shown below. It can be seen that the traffic on weekdays is mainly integrated at 9:00 (working time), 13:00 (lunch time), and 20:00 (evening entertainment break time), so after obtaining such user traffic rules, you can During these peak periods of user activity, we will carry out more targeted product promotion activities for white-collar groups, so as to achieve the minimum time cost and promotion cost to maximize the user drainage effect.
Let’s look at the traffic distribution trends in various time periods on weekends. The difference from weekdays is that the morning peak period of traffic on weekends is delayed to 10 o’clock. What time do you get up), in addition, the peak ebb and flow of traffic at night is also delayed. In view of the characteristics of user traffic distribution on weekends, Internet companies can appropriately postpone the start time and end time of activities on weekends. At this time, the activity time plan formulated on weekdays can no longer be applied, because it conforms to the routine of user groups Promotional activities can achieve better results.
2. Traffic distribution of promotion channels
There are three main channels for e-commerce promotion: online channels (Google, Baidu, etc.), offline channels (events, conferences, etc.), and new media marketing (WeChat, Xiaohongshu, etc.).
By analyzing the traffic of different promotion channels, we can clearly see the difference in the proportion of value brought by each channel to the enterprise, which is convenient for formulating targeted marketing strategies.
As shown in the figure above, since the promotion channels are multi-level, it is perfect for us to analyze and count the data through the multi-layer pie chart of the FineBI tool. Analyzing the data in the figure below, we can see that, first of all, the main combat power of the first-tier channels comes from new media marketing. In today’s era of social media communities such as WeChat and Zhihu, the audience is extensive and the user group is very large. The company needs to invest the main cost to carry out Promoted. Secondly, the effect of online channels cannot be ignored. For Internet companies, it is also a very important part of the work to do a good job in SEO search engine keyword promotion such as Baidu and Google. Compared with online channels and new media marketing, offline channels require more funds, time, and labor costs, and the audience is relatively small, so such activities are often operated only for core fans.
3. Distribution of deep access user groups
This involves the concept of bounce rate, that is, the ratio of the number of visits that customers enter through the corresponding entrance and leave after visiting only one page to the total number of visits to the page. Bounce rate = Bounces/Visits. The lower the bounce rate, the more in-depth the user's visit.
As shown in the figure above, we use BI tools to conduct in-depth analysis and statistics on the access of VIP users, old users, and new users of the enterprise in different time periods. Generally speaking, it can be found that the access depth of VIP users on the platform is slightly higher than that of old users and new users, but it is not too obvious, indicating that the activity of the VIP group operated by the platform needs to be improved.
At the same time, the access depth of old users on the platform is almost the same as that of new users. The company obviously needs to work hard on the active operation of users. It is recommended to form some old users with high loyalty on the platform as VIP users to jointly build the platform ecology Circle, increase the overall user activity. It is also possible to implement some preferential policies for old users and VIP users, such as targeted product discounts, and special promotions for favorite products based on user portraits.
4. Comparison of trends in core indicators
The main emphasis is on the dynamic changes of core indicators. So what are the "core indicators" mentioned here?
Whether it is e-commerce or other Internet industries, it is often necessary to pay attention to the following indicators:
- Views-PV;
- Number of visits - Visits;
- Number of Visitors - UV;
- Average Depth of Visit (total pageviews/number of visits),
- average dwell time (total dwell time/total pageviews),
- Bounce rate (bounces/visits).
Among them, the first three indicators are often used to measure the quantity of traffic data, while the latter three indicators are mostly used to measure the quality of traffic indicators. Through the dynamic analysis of these indicators, we can well evaluate the effect of marketing strategies launched in a certain period of time.
For example, if we carefully analyze the platform traffic indicators in the figure above, we can find that October is the peak traffic period for the whole year of 2017, which should be related to the promotion and drainage activities conducted by the company during the National Day golden holiday. The number of page views, number of bounces, and number of visits were 4941, 1290, and 2182 respectively. By comparison, the bounce rate was 59.12%, which was significantly lower than the bounce rate in other time periods, indicating that the campaign effect in October was not bad. It can serve as a reference for future marketing promotion.
02 transformation
After attracting the attention of new users through drainage, it is often necessary to adopt a series of operational strategies to realize the conversion of users, that is, let users search for products-browse products-order products-transaction payment. In the conversion stage, the indicators that need to be focused on are: order conversion rate, event conversion rate, service conversion rate and return rate.
1. Order conversion rate
For the platform operators, we hope that once user traffic enters the platform website, they can proceed step by step according to the series of requirements set by our platform operation, and finally complete the transaction payment operation. Then, for Internet operators, it is necessary to do a good job in user conversion operations in membership registration, product collection, shopping cart addition, transaction payment and other links. For such platform operations that require step-by-step transformation, we can first use the funnel diagram to conduct a macroscopic process transformation data analysis to find out the operation links that need to be optimized most at the current stage, effectively carry out targeted governance, and ultimately improve the overall platform user order conversion Rate.
Take the information presented by the funnel above as an example:
First of all, look at the conversion of users from the behavior of browsing products to the behavior of adding shopping carts. Through the funnel diagram, it can be quickly seen that the conversion rate is 50.77%, which reflects that the product introduction and picture description of the platform have a strong influence on users. attraction.
Next, continue to look at the conversion rate from adding a shopping cart to placing an order. It can be seen that the conversion rate is as high as 99.66%, which is very good. Later, I saw that the conversion rate of order-to-payment was only 50%. This is a conversion node worthy of reflection. Through data analysis, it is guessed that the payment channel of the store on the platform is not perfect. It is necessary to increase the fast payment channels such as Alipay and WeChat, and reduce the platform because there is no Provide the user's habitual payment channel and cause the probability of the user giving up the purchase behavior.
2. Event conversion rate
The event conversion rate usually refers to the additional value brought by a platform or store through a series of operational promotion activities and the impact of public events. This indicator is extremely important for platform operation evaluation and guidance for marketing operations, such as overall SEO keyword placement for online marketing, discount promotions, email marketing, and other effect tracking. Regarding the data analysis of event conversion rate, we can usually focus on indicators such as marketing channel conversion rate, member conversion rate, store traffic conversion rate, and order conversion rate to evaluate the promotion and marketing effect of activities.
Using BI tools, first analyze the conversion rate ring rose distribution diagram of each marketing promotion channel. It can be seen that the channels with the highest conversion rate of the current platform are mainly the basic online work, SEO keyword promotion, WeChat promotion, and brand promotion. At the same time, when we want to check the conversion rate data corresponding to each channel, the data automatic linkage filtering function provided by the BI tool allows users to perform all associated data linkage without any settings.
In addition to the above channel marketing strategies, for platform stores, appropriate related product recommendations can also increase the user's purchase rate of related products. For example, users can push shoes and other products to him after buying clothes. In addition, regarding the event conversion rate, since seasonality and public events will also affect the order conversion rate of products, the purchase marketing of products that are more popular in different periods can often achieve the greatest profit.
3. Service conversion rate
In terms of service conversion rate, when users usually buy goods online, they need to know some details about the quality of the goods, delivery channels and speed, etc. So good service can naturally increase the purchase rate of customers. For the customer personnel of the platform, we can count the conversion rate of the node from consultation to order, and use the conversion rate index from consultation to order as one of the KPI indicators to evaluate customer service staff performance.
As shown in the figure below, through the data analysis and statistics of the conversion rate bar chart of customer service consultation through BI tools, it can be found that the conversion rates of the five customer service representatives on the platform, Blanche, Henry, Christian, Hank, and Betty, are relatively good, and all When the conversion rate of other customer service employees is above 10%, the conversion rate of other customer service employees is relatively low. Therefore, in this respect, Blanche customer service staff with the best conversion rate can give service training to other customer service staff, so as to improve the service level of the platform as a whole, and then improve the user's next level. single conversion rate.
4. Return rate
For users, the reasons for returning goods can usually be divided into two categories. One is to apply for a return due to the quality of the purchased product, and the other is to apply for a return due to the user's own reasons. The platform side often needs to pay more attention to the first category of products that apply for return due to product quality problems. Through the statistical analysis of historical product quality reasons for return data, it is necessary to give timely feedback to the supplier for products that do have quality problems. The quality is too high. If it is serious, you can consider the return of such goods and the supplier's negotiated inventory.
03 retention
After the new users are successfully converted and become old users, we need to focus on the retention issue. In short, we need to focus on how to retain the hearts of customers.
We can define the retained users of the platform from a macro perspective: In the Internet industry, users who start using the application within a certain period of time and continue to use the application after a period of time are considered retained users. We often hope that the more users we retain, the better.
Generally speaking, in terms of retention, you need to pay attention to the following indicators:
1. Next day/7th/30th day
That is, among the newly added users on a certain day, the proportion that is still "active" (such as browsing behaviors, collection behaviors, purchasing behaviors, etc.) the next day/7 days/30 days later.
The retention rate analysis of different durations can reflect different problems. Generally speaking, analyzing the retention rate of the next day is conducive to grasping product quality changes and channel advantages; the 7-day retention rate can reflect the user retention after a relatively complete cycle; the 30-day retention rate can reflect product or channel iterations The final stability helps to judge the rationality of the evolution direction.
2. Channel retention
The user quality of different channels is often not the same. While considering the retention rate, compared with the retention channel, higher-quality advertising can be carried out.
