How to efficiently guide products to achieve self-propagation growth model

• As a member of the growth department, when observing the product operation data, I found that the average daily user increase did not exceed 50 for more than ten days?
• Half a month ago, the new version was launched and we cooperated with a certain platform for promotion . However, during the review process, we found that the 7-day retention rate of users coming from this channel was less than 5%?
• As a social software, the product is currently in the exploratory implementation stage and can only acquire customers by holding events. There are almost no new users during non-event periods?

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Have you ever had this kind of distress: the product itself has a good user experience and can meet user needs well in specific scenarios, but users are not willing to spread your product spontaneously and actively? In today's era where user stock is the main focus, if you want to gain the favor of users, in addition to giving users enough reasons to use your product, you also need to induce and stimulate users to spread the product spontaneously.

The essence of product operation lies in dissemination. With the rise and rapid development of social networks , a viral dissemination methodology based on social networks has gradually emerged. This has become a new way to acquire users, and thus the AARRR (Acquisition-Activation-Retention-Revenue-Refer) operation model has been formed.

AARRR Operational Model

In order to quantify the self-propagation effect of products , the industry has gradually introduced the concept of K value. In fact, the K value originated from infectious diseases, and its value is determined by two multiplied coefficients: the number of infected people carrying the virus and the number of people who eventually become ill. Abstracted to operational work, the number of infected people carrying the virus, that is, the number of users covered by each piece of information we spread, is used to derive the coverage coefficient of the information (for example, 100 users spreading the same piece of information can cover 500 new users, then the coverage coefficient is 500/100=5); the number of people who are finally sick can correspond to the number of people who convert to the information, thus deriving the conversion rate (if 300 out of 500 new users are successfully converted, the conversion rate is 300/500=60%), so we can get the K value as 5*60%, which is 3.

From the perspective of user growth , the higher the K factor, the stronger the product's ability to acquire new users. When K>1, the user base will experience explosive growth; when K<1, the user base will stop growing through self-propagation when it reaches a certain size. Therefore, when planning user growth activities, it is necessary to cover both the number of users and the number of conversions at the same time.

To increase the number of covered users , operators often use a tried and tested trick to capture current hot topics and use various holidays to create momentum. For example, during the 90th anniversary celebration of the founding of the People's Liberation Army, the H5 mini -game "My Military Uniform Photo" from the People's Daily attracted more than 410,000 visitors in one minute, with cumulative page views exceeding 820 million. For example, Hupu launched a fake news generator two years ago, which only required the input of a person's name to automatically generate fake news and take screenshots for dissemination, with a dissemination effect of over a million in just one day. Information coverage is only the first half of social communication, which means that information reaches users in various forms such as text, image, voice, and video. In this part, we need to consider whether the content and form of the information are attractive and who we want to attract. We can analyze and understand the preferences of this user group to guide us in completing this work.

Overview of Population Field Preferences

After understanding information coverage, let’s look at information conversion , which is the second half of information dissemination and also a crucial part. When users use a product, what factors will prompt them to actively spread the word? In other words, what are the transmission factors? Based on the third to fifth levels of Maslow's hierarchy of needs theory (social needs, respect needs and self-actualization needs), four communication factors are abstracted and sorted out: liking, reciprocity, satisfaction and great love.

Like , create products that users like. Once the " PlayerUnknown's Battlegrounds " game came out, it instantly became a rising star in the gaming industry. It was wildly spread among game players and even attracted a large number of users who did not play games before. In a short period of time, it occupied half of the gaming industry. League of Legends and King of Glory have lost their former limelight.

Reciprocity : Sharing products can benefit both the sharer and the sharee, such as Didi coupons, Ele.me food coupons, or invitation codes for answering questions after sharing invitations to the Summit and Cheese Superman.

Satisfaction , the satisfaction brought by gaining attention or recognition through communication, such as the Keep sports rankings , Mint Reading’s persistence in ranking, and the WeChat mini program Jump Jump that attracted major advertisers some time ago. By sharing the game results, you can invite friends to challenge, which will also create a competitive mentality and make the interaction stronger;

Great love , last year Tencent Charity launched a charity event called "Children's Gallery", which raised funds to help special people with intellectual disabilities integrate into society. As long as users pay one yuan, they can share their acts of charity, which is meaningful and can attract friends to participate, conveying the message that "you can help those in need at a very low cost."

In order to quantify the effect of information in actual social communication, we want to know what kind of products are popular with users? In what scenarios are users willing to share? ...Combined with the big data analysis tool iResearch Ark, we can start with multiple analysis models such as user retention and conversion ( retention can be used to measure the value of a product to users, and by analyzing the user's participation/activity in the product, we can see whether the user likes to use the product; the funnel can connect the user's usage steps in the product and monitor the user's conversion at each level).

Analysis of the 30-day retention of new users within a certain period of time

Create a user browsing page-sharing conversion funnel

When talking about information coverage and conversion after reaching out, one point that cannot be ignored is: how to enhance the effective reach of information? In order to allow users to receive news of their interest at a specific time, for example, when a membership on a video website is about to expire, users can be reminded to renew in time; after Weibo users allow LBS positioning to be obtained during use, local hot information will be pushed when it is detected that the user has come to a different city... Common ways to reach users include APP push, email and text messages; iResearch Ark currently supports multiple in-application push tools such as Getui, Jiguang, Baidu, etc., as well as configuring email notifications for users.

Message push configuration

Throughout the user life cycle , from acquisition to retention, we need to keep in touch with users and make them willing to interact with our products. In order to ensure a healthy growth trend in the user base, we need to do a lot, but more importantly, we need to guide users to self-propagate, which can drive the self-growth of the product under certain conditions.