Looking at the WeChat Open Class H5 that has been all over the circle of friends from an operational perspective, do you really know how to do a year-end inventory?

Looking at the WeChat Open Class H5 that has been all over the circle of friends from an operational perspective, do you really know how to do a year-end inventory?
WeChat was officially released on January 21, 2011; the Moments feature was launched on April 19, 2012; the public platform was launched on August 23, 2012; Airplane Wars and WeChat Pay were launched on August 5, 2013; in 2015, the number of active WeChat users exceeded 650 million… Today, the h5 page "My Story with WeChat" developed by WeChat Open Class instantly set off a wave of friends, with netizens rushing to show off their own WeChat data. When did you start using WeChat? Who was your first best friend? How many likes did your Moments receive? How many red envelopes have you sent out?... Every piece of data piqued the curiosity of users. Of course, I couldn't resist the temptation and gave it a test. 

 H5 has been popular in the circle of friends since 2014. According to the content type, common H5 can be divided into game type, conference type, interactive type, pure display type, shopping guide type, inventory type, etc. "My Story with WeChat" helps you take stock of the moment you started using WeChat, "Who was your first WeChat friend? Where have you been? How many friends do you have? How many Moments have you posted? How many likes have you received? How many marathons have you run..." Yes, it is undoubtedly an inventory-type h5, and it has won a point in the battle for various h5s to be popular in the circle of friends. Of course, for those who stick to their own operations , they can use it not only to bring a sense of superiority as old WeChat users, but more importantly, through this h5 that has gone viral in the circle of friends, they can focus on discussing how to make an inventory-type h5 for products at the end of the year from the perspective of operations. What types of inventory h5 can be made The essence of inventory-type H5 is still inventory, but the operator displays the content obtained from the inventory in the form of H5. According to the logic of inventory, it can be divided into time-based inventory h5, content-based inventory h5, and pure data-based inventory h5. At the same time, I found two very good cases for each type of inventory h5. Time-based inventory h5 

(Be capricious and look at the good things JD has done this year)

(Coca-Cola, happy 128 years of analysis) Content inventory h5 

(Douban, 2015 annual list)

(2015 Entertainment Industry Pictorial Biography) Data inventory h5 

(My commute to work in 2014)

(My Red Envelope Year) Therefore, before making an inventory-based h5, you can first think about which type of inventory logic to use. In this process, you need to consider the following factors: ① Whether the product features can be reflected ② Whether the data can be obtained ③ How to inventory the competing products ④ Whether users will be interested How to make a data inventory h5 Among the inventory-type h5s, judging from the situation that has been all over our circle of friends in the past two years, the data-type inventory is the most widely spread. In fact, "My Story with WeChat" is also a data-type inventory, so here I will focus on my understanding of data-type h5. If we take the data type inventory h5, further subdivision can include report type data, user type data, and product type data. Similarly, in order to more intuitively illustrate the differences between these three types of data inventory h5, I have collected three representative h5 pages. You can scan the QR code to experience it. 

Report data: Report on mobile Internet users after h5/00 

User data/My Footprints 

Product data/Lufax Similar to "My Story with WeChat" this time is "Alipay 10-Year Bill", which was also popular on the entire Internet at the end of 2014 and set the highest login record for Alipay wallet. 

 It can be seen that among these three data types, user-type data inventory is most likely to cause users to share. When it comes to selecting user data, you only need to take advantage of people’s hysterical psychology and satisfy their need to show off, and it will basically go viral. After all, these data are closely related to themselves. However, these user data do not come with the product! The “10-year bill of Alipay” went viral on WeChat Moments at the end of 2014. At that time, I was working in content operations at Tieba, and I wanted to do a similar user data inventory on Tieba. I listed some basic user data such as “when did they join, how many bars they followed, how many posts they made, how many likes they received”, and excitedly ran to the data group to submit data requests. The result was ~~~~ the data was incomplete, and only the user’s data for the past four years could be obtained, so this plan failed. Therefore, here is a suggestion for startups . When deploying data statistics for products, remember to compile basic user portraits. It is also good to use this portrait for publicity once a year. Can’t we do a user-type data inventory without user data? Baidu Map’s h5 “My Route to Work in 2014” which has gone viral on WeChat Moments tells us that this is not the case. If rough data calculations are acceptable, better communication effects can be achieved by using the data submitted by users and some product-specific algorithms to generate exclusive data reports for users. In terms of the popularity of the three types of h5, report data, user data, and product data, report data ranks after user data. It is also more diversified in data acquisition. In addition to using product data, it can also be obtained through user surveys and reference to other literature. Product data basically belongs to the brand-level communication, and the probability of it going viral in the circle of friends is very small, unless it is a brand like WeChat, Taobao, Alipay, QQ, Tieba, Baidu, and the product report has become an IP. There is hope of dissemination because, except for internal industry practitioners, users who have not used your product basically will not care about your product data. Content Operation in Data-Based Inventory How can I say that I want to teach you how to make a cool data inventory h5? I don’t even believe this statement myself. It may be related to my experience in content operation. I hope to analyze some experiences worth reusing when doing the year-end inventory based on the data (content) in these inventories that have gone viral on WeChat Moments. 1. Content mining This focus refers to data mining, which is the original reference data for content displayed to the outside world. In this stage, we need to explore what types of data are needed to make operational decisions. Specifically, the following types of data may be included. 1) Basic user data Zodiac sign, age, gender, registration time, location, relationship status, income, industry, number of times the product is used, peak product usage, and other basic user data with product characteristics. 2) Interaction data includes posts, comments, replies, likes, searches, followers, geographic location check-ins, clock-ins, purchases, and other product-specific interaction data. 3) Product data: gender ratio, total number of users and growth, geographical distribution, function usage time, DAU/MAU, keyword frequency, transaction volume and growth, comparison of mobile/PC terminals in terms of users and revenue, and other interactive data with product characteristics. 2. Content organization The data mined in the first stage are scattered and have no specific themes. Sometimes operations need to analyze these data to find data themes that can arouse users' interest, determine some interesting dimensions based on the themes to support it, and distribute the mined data to these dimensions as much as possible. Taking the theme of “My Story with WeChat” in WeChat Open Class as an example, its dimensions include acquaintance with WeChat, me on WeChat, and us on WeChat. These three dimensions contain the following data respectively. 

 Compared with the "WeChat.Life" product report released in October, the WeChat user data h5 this time has fewer dimensions. Perhaps this is the difference between report-type data and user-type data. After all, user-type data has a very large number of data requests and consumes a lot of server resources. 3. Content packaging Content packaging mainly refers to the packaging of data. Currently common packaging includes proportion, accumulation, average, trend, distribution, comparison, and simulation. Of course, there are also data that are very meaningful in themselves and do not need to be packaged, such as who is the first user you added as a friend. I won’t go into details here, but in general the principle is to present the most interesting data to users. I'd like to recommend two data inventory h5s that I made. I personally feel they are pretty good and you can refer to them. 

 4. Content dissemination Now that the data has been mined, organized and packaged, can it be disseminated? Nonono! It is also necessary to check whether the key path data statistics of each page have been completed, monitor the traffic of each module of the page, and make real-time adjustments to the topic content based on data analysis . In terms of content reaching users, operations are mainly responsible for on-site promotion. Basically, interesting user data inventories will cause on-site users to spontaneously participate in the dissemination. Off-site communication relies on the market and channels. Another thing that needs attention is the content display form of user data inventory in off-site communication. It is recommended to use the data of well-known big Vs and other users to spread the information, which is more likely to arouse the curiosity of new users and then use the product. Finally, let’s go back to this h5 “My Story with WeChat” and talk about my thoughts on this h5 at other levels. In terms of branding, it is more valuable for WeChat Open Class, but for WeChat as a whole, it is not as valuable as the WeChat Life Big Data released in the last October press conference. Currently, the media is talking about the rumors about the insecurity of WeChat payment derived from this h5. In terms of relevance, I suddenly feel that it has a low relevance to WeChat Open Courses. My understanding of WeChat Open Courses is that big names share how to obtain new business opportunities through WeChat, which is not something that ordinary WeChat users have much contact with.

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The author of this article @陈维贤 is compiled and published by (APP Top Promotion). Reprinting this article must be approved by Top Promotion , and please attach the link to this article!

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