In the digital age, user growth has become the core of business competition. In this article, we will take a deep look at the concepts and strategies of user growth, and analyze how Huawei uses a series of products and services to build a user growth operation plan. Let's demystify user growth and discover the secret to sustained growth.
They are all talking about user growth, what is user growth, how to do user growth, and what is the correspondence between user growth and data products?
From the perspective of the book "Growth Hacking", user growth is to attract new users, promote activation, retention, and fission, and the book is written to form a user growth team to achieve growth by creating amazing Aha products and testing the effects of different groups of people and different materials through continuous AB experiments.
And there are a lot of people who study user growth who are not professional user growth teams, not professional user growth product managers. More likely to be business products, business operations, the business line is in the stage of requiring traffic growth, the boss makes a decision, and the DAU will grow from 100w to 200w.
At this time, product operation students need to find growth points, quickly polish high-quality products and services through user growth AB experiments, and match the corresponding user growth operation plan.
For data product managers, as a tool provider, we need to think about how to provide a complete set of user growth operation services.
Under this opportunity, we conducted a survey on Huawei's user growth operation solution to explore how Huawei builds user growth solutions from the tool level.
1. Huawei's user growth operations
Huawei's User Growth Operation Solution uses Huawei Analytics to deeply analyze in-app user behavior data, and combines contextual intelligent push (SMS, push, and in-app messages) to intelligently push users for different user segments and scenarios, so as to implement operation scenarios such as user acquisition, activation, payment conversion, and churn recall.
The solution consists of 11 products, as shown in the figure below, including Huawei analytics, prediction services, intelligent operations, AB testing, and other capabilities such as app linking, in-app messaging, SMS service, event management, serial login activities, and remote configuration.
The application scenarios of the growth plan are mainly five scenarios, including: fission to attract new users, improve retention, churn recall, paid conversion, and scenario-based recommendation. This splits the different stages of growth hacking, and each application scenario has a corresponding product service:
In the fission new user attraction scenario, make a link to the activity through APP linking, and inform users of the activity through push/SMS, and encourage users to spread the word on social media or invite friends to download, or plan and install prizes or gift packages to increase the number of downloads. In terms of product capabilities, it corresponds to APP linking, in-app messaging, Huawei analytics, SMS service, and activity management.
Improve retention scenarios, create user retention activities for users who may lose through prediction services to avoid user churn, plan activities such as consecutive registration prizes to be exposed in the app market, and increase user stickiness through coupons and other benefits, and use in-app messages or push notifications to plan daily drainage activities to improve user retention.
There are also churn recall, paid conversion, and scenario-based recommendation scenarios, and the tools and services provided are similar.
Many people will have some doubts when they see this, Huawei's user growth operation solution has assembled 11 products and services, which is dazzling. And for the average enterprise, does the user growth operation tool need to be so complex and so huge?
I don't think so.
At the heart of the growth strategy lies in user-content-touchpoint.
For people in different life cycles (introduction period, growth period, maturity stage, dormant stage, attrition stage)
Reach different content (new acquisition campaigns, prize login campaigns, coupon benefits, invite friends to download campaigns)
Use diverse touchpoints (push, SMS, in-app messaging, social media).
Next, the intelligent operation, predictive service, AB test, and Huawei analysis in the solution are analyzed.
2. Intelligent operation
Intelligent operation is an intelligent operation platform that integrates target setting, user screening, reaching content, reaching channels, and effect analysis. It is mainly used for operation and promotion, helping enterprises to efficiently implement scenario-based operation activities, release operation manpower, and improve the effect of activities.
Capabilities include viewing activity effect data, creating operational activities, audience management, push/SMS template management, system configuration: anti-disturbing, approval, etc. A follow-up article will be introduced, and you can pay attention to the album first.
Products such as in-app messaging, SMS services, campaign management, streak campaigns, churn recalls, and AB testing in the user growth solution can all be used as part of the intelligent operation product service.
3. Forecasting services
Segmentation of user groups is the basis for personalized operation and user growth, and our common user portrait platform/CDP platform will provide the ability to segment users.
It is usually a way to tag users, and users are layered through tag combinations. It is divided into facts, rules/statistics, and algorithms, and can be found in the Label System for details.
Huawei's prediction service mainly makes algorithmic tags and recommends algorithmic people. Based on the user behavior data and attributes reported by Huawei Analytics and combined with machine learning technology, the prediction service predicts specific target groups, including churned users, user payment potential, and repeat users.
As shown in the figure above, the underlying prediction service relies on the buried data analyzed by Huawei, and the key behavioral characteristics of users are obtained for model training.
The main functions of service forecasting include managing forecasting tasks, evaluating data quality, and predicting user distribution analysis/TGI analysis. It mainly predicts three types of users: churned users, user payment potential, and repeat users.
4. A/B testing
A/B testing is an important tool in growth experiments, providing users with different features through comparative testing, testing the click effect of different copy, and selecting the group with better conversion effect from quantitative numbers.
Huawei A/B testing allows you to create one or more comparison experiments, obtain key comparison data through the experiments, and select user interfaces, copywriting, product features, or marketing activities that better meet user needs, improving the accuracy of decision-making. The main capabilities include configuring AB experiments and viewing experiment reports.
Common use cases for A/B testing include the design of visual interfaces, testing different visual effects for the same scene, and monitoring data performance metrics. In addition, there are many applications of copywriting testing, where operators use push notifications to improve daily activity, and they will rack their brains to come up with several push copywriting, and they need to test which copywriting has better CTR conversion. There is also a test of the function, which is used more by the product manager of the module, and AB test is carried out for the new iteration of the function.
5. Huawei Analysis
Data analysis is indispensable for growth experiments, including analyzing the overall market data, fluctuation data of users in each life cycle, and monitoring the effectiveness of growth experiments or event marketing.
Huawei Analytics integrates data access, data analysis, user lifecycle, and data management capabilities to drive enterprises to achieve targeted new acquisition, product optimization, lean operations, and business growth.
In terms of capabilities, Huawei Analytics is similar to Sensors Analytics in that it supports event data access and management, event analysis/funnel analysis, and other event analysis models. However, Huawei's ability to directly generate audience packs after analysis is more special, and it realizes the connection between the analysis, grouping, and operation application paths.
Sixth, say at the end
Huawei's User Growth Operation Solution is a user growth operation tool composed of 11 products and services, with core components including operation, forecasting, analysis, and AB.
Intelligent operation is a relatively standardized operation platform on the market, the prediction service provides three algorithms for crowd prediction, AB tools based on AB experiments, and Huawei Analytics, which is an analysis tool similar to Shence Analytics.
In terms of product composition and application scenarios, Huawei's user growth operation solution is similar to the growth framework of mobile applications mentioned in the "Silicon Valley Growth Hacking Practical Notes". As shown in the figure below:
1) Technology is the foundation at the bottom, including AB test architecture, automated marketing SDK, attribution SDK, etc
2) Analytics and insights are fundamental to guiding growth strategies, and it is necessary to analyze the performance data after delivering specific campaign content to the user group
3) User acquisition, engagement and retention, and monetization are the three main stages of the user lifecycle
4) The use of specific channels spans different life cycles of users, such as push, in-app messaging, SMS, email, advertising, etc
In terms of Huawei's financial and human resources, many enterprises cannot reach it, and the growth operation solution alone includes 11 products, each of which has a corresponding R&D team behind it.
Columnist
Straw hat boy, public account: a data person's own place, everyone is a product manager columnist. Author of the book "The Road to Big Data Practice: Data Middle Platform + Data Analysis + Product Application", focusing on the field of user portraits.
This article was originally published on Everyone is a Product Manager. Reproduction without permission is prohibited
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