4 common user growth solutions

Designing solutions based on the problems reflected in the data is a method often used by data product managers when working with data growth. What are the specific plans? The author of this article combines his own customer acquisition practices to share common growth plans for everyone to learn and refer to.

Compared with traditional product managers, the solutions of data product managers are more focused on whether there is data support. In the past, traditional product managers only created functions based on demand. In contrast, data product managers are more focused on how to make solutions based on the problems reflected in the data.

For example, when a user raises a demand, an ordinary product manager will wonder whether this demand is worth doing. This is a subjective and emotional thinking. A data product manager will think about what problem the demand solves for the product and whether there are any abnormalities in the data of the product in this area that need to be addressed at this stage. This is more of an objective and rational thinking.

So how do data product managers achieve growth? Let’s first look at the core formula of modern enterprises: Revenue = Traffic x Payment Rate x ARPU

The most common types of traffic include social traffic (communities, WeChat public accounts, mini-programs), search traffic (ASO, SEO), information traffic (TikTok, Toutiao, Xiaohongshu), delivery traffic (Baidu, major mainstream stores, Toutiao), and offline traffic. These traffic often determine the size of a company's audience. Judging from the current market environment, TikTok's daily active users are already catching up with WeChat, and the two are also in a fierce battle for user time.

In terms of conversion rate, some platforms rely on their unique content SKUs, such as precise push (such as Douyin), improving content quality (such as product managers), and content richness (such as iQiyi, Bilibili and other video platforms).

This includes the well-known and popular video account function recently launched by WeChat. In the content ecology of WeChat, the video account is not like the long content such as the official account, which has a creation threshold. It is a short content that meets the original intention that everyone can create, making WeChat more sound in content ecology. At the same time, the content recommendation strategy adopts the push of multiple red dots to increase the user's opening frequency. For now, in order to pursue content quality in the early stage, the video account did not use head traffic to suppress traditional traffic. Everyone has the opportunity to obtain traffic through content.

Other platforms, such as e-commerce, rely on pricing, such as promotions, flash sales, discounts, and more importantly, they use high-quality supply chains to highlight low costs to conduct online marketing and increase user conversion rates. This is the process of converting passers-by into fans, relying on the advantages of the platform to gain the favor of users.

ARPU is the process of monetizing fans, such as advertising, sales, rewards, live broadcasts, memberships, games, peripherals, etc.

For this, there is a sales funnel that everyone is familiar with, the AARRR model:

I won’t go into too much detail about this funnel. I’ve also written an article on the ARGO and AARRR models before. This article mainly explains the growth plans we can choose in the customer acquisition stage. I think there are about four common growth plans:

01 Resource-based growth

Resource-based growth means relying on our own industry channels to achieve growth. For example, if I am a magazine APP, I can consider cooperating with relevant newspapers and magazines to grow my own products through their audience size. This is also the best way to cold start. I can quickly find my core seed users and achieve the goal of equity appreciation through cross-border cooperation and mutual volume washing. Before doing this growth we need to ask ourselves the following questions

• What are the upstream and downstream of your industry (returning value to the upstream and releasing value to the downstream)
• Who will be your potential partner?
• How to reach your partners (approach your target audience)
• How to establish a cooperative relationship (how to establish a consensus mechanism)

The most important thing for resource-based growth is retention. We have acquired core users, but users do not necessarily like our products. Therefore, data product managers need to focus on whether there are problems with our own product retention data. If it is incorrect, we need to analyze and solve the problem based on the product data. In terms of indicators, we need to pay attention to the average of new additions, the arithmetic mean of retention, the average number of people retained per time, and the geometric mean of retention per time (excluding abnormal data).

02 Investment-based growth

Investment-based growth is a type of scale growth. Its cost is often very high, but it can bring in a large number of users. For example, Hongguo Novels grew its entire product DAU from 0 to 5 million in just three months.

When doing advertising growth, we need to pay attention to the fact that a perfect advertising must satisfy the requirement of spending the least money and getting the most users. Here, we take advertising as an example. That is to say, our new users must satisfy the requirement of LTV (customer life cycle value = number of days a new user visits * value generated per day) > CPC (advertising cost / new advertising + new brand). For example, if our customer acquisition cost is 3 yuan, but the value brought by the user is 5 yuan, then we will consider doing advertising quickly.

The value of this intermediate customer is determined by the product features, but we can focus on changing the CPC (cost per click) of the ad. First, let's look at how the CPC is calculated: CPC = ad budget / ad clicks, that is, CPC = ECPM / 1000 / CTR. In this process, we need to focus on the logic of ad delivery:

In this process, I believe many people have paid attention to the issue of business lines. There is no doubt that we need to choose business lines with higher ROI, and ROI = LTV/CAC. At this time, we need to establish an evaluation indicator system for daily business lines. In terms of delivery efficiency, we need to pay attention to consumption costs, clicks, exposure, click-through rate, CPM, CPC. In terms of conversion efficiency, we must pay attention to conversion rate, new costs, secondary traffic, next-day retention rate, LTV30, and finally get ROI. For those with low ROI, we must immediately abandon this business line to prevent unnecessary costs.

03 Platform-based growth

In short, platform growth means standing on the shoulders of giants. We can strengthen the IP of our own products on some platforms with large traffic and enter our

The psychology of the target users, that is to say, this process pays more attention to operations:

Take Douyin, which has a high daily active user base, for example. We can build our own storyline to highlight the features of our product. But before that, we need to understand the recommendation mechanisms of major platforms. For example, the recommendation rule of Douyin is: Recommendation volume = cold start volume + a*watching time + b*like rate + c*playthrough rate + d*shares + e*personal center page time

Knowing these points, we can then make our own strategies, such as the length of time on the page.

We can see from the above page that the number of likes and fans are unchangeable variables, but we can change the cover image. However, general linear regression analysis is difficult to process images. At this time, we have to use a special nonlinear regression of deep learning, which reduces the data dimension through pooling, extracts large features, and finds out which images have which features and have a higher click-through rate. In this way, we can make our own cover to increase the user click-through rate, thereby affecting the length of personal center and increasing the recommendation volume of Douyin.

04 Fission Growth

Fission growth is a growth method that uses users as channels and pays more attention to the user relationship chain. Here is a very interesting small program that you can learn from, which is Xiao Nian Gao. It is a tool-type product that eventually transformed into a UGC community. By using WeChat traffic to trigger sharing, it brought tens of millions of growth and matched users through content operations.

It has to be said that Xiao Nian Gao’s user positioning is very special, even reaching a special group like those born after 1960. Even WeChat PMs are saying that Xiao Nian Gao’s existence has broadened WeChat’s user boundaries. We can also look at the daily activity growth brought about by Xiao Nian Gao’s fission:

How do we evaluate the fission effect of our own products? First of all, we need to make it clear that the viral coefficient = return rate/sharing rate. Only when this coefficient is > 1 can it continue to grow. So where does the new fission come from? It can be roughly equal to DAU x sharing rate x return rate. The product of these three indicators gives us our return volume.

Author: Love Operation

Source: Aiyunyingorg (ID: iyunyingorg)

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