Lei Feng network (search "Lei Feng network" public number attention) by: The author of this article GrowthIO growth team.
In the context of the lean operation of the Internet industry, data analysis has become the standard for operations. Everyone hopes to improve operational efficiency through careful analysis. With the increasing number of operational methods such as commodity spikes, explosive articles, and rapid product iterations, the past hour-level traffic monitoring has failed to meet the needs of operators. We need to record every minute, every visitor and every operation on the website platform to meet our need for real-time monitoring and rapid decision-making.
This minute level of data monitoring and analysis is the "real-time analysis" we are going to introduce today.
First, real-time analysis needs to pay attention to the three major indicatorsThere are many indicators that data operations need to pay attention to, such as PV, UV, conversion rate, retention rate, and so on. Ignoring outcome-based indicators such as retention, conversion, etc., in the minute-level real-time monitoring, operations focus on the three major types of data indicators of the website platform: 1) access to users, 2) access to sources, and 3) access behavior.
User visits, access sources, and access behaviors are important to the operation of the website platform:
Minutes of visits (module 1 in the figure below) can help us understand the trend of traffic and facilitate the timely detection of traffic anomalies.
The monitoring of the source of visits (module 2 below) facilitates us to understand the source and weight of real-time visits and prepare for channel optimization;
The real-time monitoring of the access behavior (module 3 in the figure below) helps us understand the user's access preferences and facilitate the optimization of website content in the later period.
 
In the existing SaaS (software as a service) product, the above real-time indicator modules are unified in a back-end page, so that the design is convenient for operators to understand the real-time situation at a glance.
Second, through three cases to explain real-time analysis Â1. Discover problems from abnormal traffic peaks Â
Operators are generally concerned about the PV, UV and their trends of the website platform. This is also the basic indicator of website traffic analysis. Traffic analysis in days or hours for granularity is rough and can mask traffic fluctuations on many time nodes. If we look at the traffic in minutes of granularity, what will happen?
A content community on July 16th 16:30-16:35 User traffic surged, which was about 4 times that of usual time (as shown in the circle above). The operator of the community immediately discovered this abnormal value. With the [access source], it was found that the source of the node's visit was ranked first by WeChat (mp.weixinbridge.com). However, the specific reason was not known at the time. In an article shared later in the circle of friends, it was discovered that at that time, an operating coffee company recommended the community platform in a WeChat group sharing, which contributed to the surge in traffic of the community from 16:30 to 16:35. The PR of the community decisively seized this opportunity and invited the operating coffee giant to come to the community for knowledge sharing and played a very good dissemination effect.
This is a typical case of discovering cooperation channels through a surge in traffic, which is worth thinking about for all companies. Conversely, if the traffic plummets or even drops to zero, then check the website/app immediately at this time so that the problem can be fixed in time.
2. Precise delivery: channel optimization and anti-cheating
As an operator, if products are placed on the major channels, they can monitor the advertising effectiveness of the channel at any time through the [access source], and then determine the amount and quality of access users brought by the channel.
An Internet company recently conducted a series of channel placement tests. They found that the two channels brought about very little by the [access source], and the price is very expensive, so they immediately withdrew the placement immediately after going online. At the same time real-time analysis can also be used for anti-cheating, short-term, single-channel traffic surge is likely to be the performance of brushing or traffic cheating. There were two consecutive peaks in the number of visits to the website in the morning and most of the traffic in that period came from one channel. Operators are very alert to this, after the investigation is the agents cheating, with the robot brush volume; afterwards the company decisively give up the agency channel. The above two actions saved the company a lot of losses.
3. Real-time monitoring to make product operations more efficient Â
Now, the speed of iterative Internet products is getting faster and faster. Product operations need to track new online products or functions and evaluate the product's effectiveness or market feedback.
In the area of ​​Internet finance, there are cases of fraudulent submissions (entry, ie purchase of financial products). Taking an internet finance company as an example, because the risk control will control the intensity of external propaganda, the number of daily users is basically stable. One day, the mutual gold company went online with a new financial product. The company’s operating personnel found that the number of visiting users suddenly increased through [real-time user visits], and then through the [active web page], it was found that a certain page in the product had a special visit. Gao, after checking that this is a loophole in the product, it will cause the company to lose a lot of money. They decisively take repair measures and then go online again. If you still use traditional traffic monitoring methods, it may take two or three days to find the loophole. At that time, the loss of funds may be several million.
Third, data-driven fine operation ÂFrom the initial "idea" to the final formation of a product or operation method, operators need to measure its performance and market feedback through data. At the same time, problems are discovered in the data, assumptions are made, and iterations are continuously upgraded; thus, a virtuous circle of “idea — product — data†is formed, which drives the growth of business and customers.
In the course of operations, the more timely data feedback, the faster we can iterate and the more efficient our operations will be. The 365 power of 1.01 is approximately equal to 38; in other words, continuous, rapid, small iterations can be achieved through real-time analysis, and this accumulation is operational and a huge improvement for the company.
Lei Feng Net Note: This article is authorized by GrowingIO and published by Lei Feng Net (search for “Lei Feng Net†public number). Reprint please contact us for authorization, and keep the source and the author, not to delete the content.
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