The essence of data analysis is actually to do data comparison analysis. Without data comparison, it is often difficult to use single indicator statistics to play the value of data. In this post, I will use the Internet industry as the background for data business analysis, and I hope to share some of my experience in traffic analysis.

In short, in terms of Internet traffic data analysis, there are four general data analysis methods.

• Compare and analyze the traffic patterns, adjusting the enterprise service and promotion activities for different time periods.
• Compare and analyze the structure and proportion, guiding the marketing of target groups.
• Compare and analyze abnormal situations, finding the problem to adjust the strategy in time.
• Compare and track the activity flow changes, summarizing the experience of activities to make subsequent pointed adjustments.

Next, we use FineReport to create the traffic data analysis templates. And then, we try to do some comparative analysis on the data.

1. Weekly Distribution of User Views

For Internet companies, traffic data is often analyzed by workweek. In this regard, we can macroscopically calculate the total platform traffic data from Monday to Sunday. First, we carefully observe the data of working days and non-working days. We find that the traffic on the weekend is higher than the traffic on the working day, which is a common phenomenon in the Internet industry.

After clarifying the weekly distribution of user traffic, we have a general promotion direction. At the weekend, the user base is larger, so compared to the workday, we can invest more promotional activities on the weekend to guide new users and maintain the activity of old users. 

Then we think about the next step: how do we schedule our event promotion time on weekdays and weekends? 

We can analyze the trend of user traffic on weekdays and weekends, and we carry out the promotion in the specific time period, so that we can obtain more user inflows at a lower cost.

Let’s first count the time distribution of traffic over each working day. We use FineReport to make the following traffic distribution graph. It can be seen that the traffic on the working day is mainly concentrated at 9:00, 13:00 and 20:00 every day. So after getting the user traffic rule, we can do more product promotion during the peak period of user activity to achieve the lowest cost and attract the most traffic.

Unlike the working day, the peak of the traffic on the weekend starts after 10:00. In response to the characteristics of user traffic distribution over the weekend, Internet companies should delay the promotion time.

2. Promotion Channel Traffic Distribution

The promotion channels for the Internet industry are mainly divided into three types: online channels, offline channels, and new media. Compare and analyze the value of each channel to the enterprise to develop a targeted marketing strategy. 

As shown in the above figure, since the promotion channels are multi-level, we use the multi-layer pie chart of FineReport to count the data. From the data in the figure below, we can see that the main combat power of the first-level channel comes from the new media marketing. Today’s social media like Facebook and Twitter have a wide audience and a huge user base. Companies need to invest in major promotion costs in these channels. 

Secondly, the effect of online channels cannot be ignored. It is also an important part of doing a good job of search engine optimization (SEO). Compared with online channels and new media marketing, offline channels require more funds, time, and labor costs, and their audiences are relatively small, so such activities are often run against core fans.

3. Monthly Indicator Trend Comparison

Before analyzing the data of monthly indicators, we briefly introduce some commonly used indicators of Internet marketing reporting:

• Page View
• Visit
• Unique visitor

We use the above three basic indicators to measure the amount of traffic data. In addition, the average visit depth (total pageviews/visits), average time on site (total time on site/total pageviews), and bounce rate (bounces/visits)can be used to measure the pros and cons of traffic metrics.

When analyzing the traffic indicators in the above figure, we can find that October is the peak of the traffic of 2017, which should be related to the promotions made by the company during the holidays. The views, bounces, and visits are 4941, 1290, and 2182, respectively. By calculation we get a bounce rate of 59.12%, which is significantly lower than the bounce rate of other time periods. Therefore, we can learn from the promotion activities in October.

Finally, we analyze the user’s visit depth (bounce rate=bounces/visits). We use FineReport to analyze the statistics of VIP users, old users, and new users of the enterprise in different time periods. 

Overall, the visit depth of VIP users is slightly higher than that of the old users and the new users, but it is not too obvious, indicating that the activity of the VIP group has yet to be improved. At the same time, the visit depth of old users is almost the same as that of new users. The company obviously needs to invest more in the operation of user activity. It is recommended to combine old users with higher loyalty and VIP users to build a platform ecosystem. And some preferential policies can be implemented for old users and VIP users, such as targeted product discounts, and preferential merchandise pushes based on user images.

Well, all the above is some of my traffic analysis experience. I will continue to share tips on conversion, consumption, and retention in Internet operations. Welcome everyone to exchange Internet data analysis methods.