Business secrets in digital mobile Internet operations in the era of big data!

After the Double Eleven shopping festival in 2015, according to the figures released by Tmall , mobile transactions accounted for 68%, exceeding last year's 49%. Reports from other e-commerce companies during the Double Eleven period also revealed that mobile transactions accounted for around 70%. Mobile Internet is becoming the entrance to all business activities. Including the financial industry, future customer competition in all industries will definitely take place on the mobile Internet and on mobile apps.

According to statistics from 2014, the average Chinese person uses their smartphone for 104 minutes a day, with mobile apps accounting for 78% of that time. This data will increase in 2015. Young people in first- and second-tier cities will use smartphones for more than 180 minutes a day. Smartphone apps are becoming the business, customer, and data entrances for all companies.

The term growth hacker became popular in Silicon Valley a few years ago and was first coined by Sean Ellis, founder and CEO of Qualaroo, in 2010. An article published by Adnrew Chen in April 2012 titled "Growth Hacker is the new VP marking" attracted everyone's attention. A book written by Fan Bing, Growth Hacker, has attracted widespread attention in China. The book has been highly praised by many mobile operation experts and has become a practical tool book for mobile operation. The book "Growth Hacker" reveals the business secrets of digital mobile app operations through many cases and data.

1. Methodology of Digital Mobile Operations

In traditional Chinese thinking, there is no order without rules. Theoretical support and methodology are the framework and guidance for business behavior. Modern management ideas and systems are basically based on methodology. The masters we often mention, such as Peter Drucker, Taylor, Michael Bolton, and Philip Kotler, are all creators of methodologies. Their methodology represents modern management thinking and leads the progress of the times.

In terms of mobile operations, the 2A3R theory is a classic methodology, which originated from the startup Pirate Metrics shared by Dave McClure. After being introduced into the field of mobile Internet operations by TalkingData, it has been gradually improved into a classic methodology for mobile Internet operations.

2A3R is composed of the abbreviations of Acquisition, Activation, Retention, Revenue, and Refer, which correspond to the five important processes in a product's life cycle, from acquiring users, to increasing activity, improving retention rate , and obtaining revenue, until finally forming viral spread.

• The 2A3R model points out two core points of mobile operations.
• Focus on users and take the complete user life cycle as the clue;

Control the overall cost/revenue relationship of the product. If the user lifetime value (LTV) is much greater than the user acquisition cost (CAC), it means the success of product operation .

1. Acquisition

Operating an App is undoubtedly about acquiring users (Acquisition), that is, promotion, and introducing more users from different places. Without users, there is no operation.

This stage is the investment period of the business: operators acquire target users through various promotion channels and in various ways; analyze new additions, total number and growth rate through different dimensions such as time, region, version, promotion channel, etc., and combine various dimensions to analyze the user acquisition effect of various marketing channels and the distribution of target users; evaluate the effects of various marketing channels to more optimize and reasonably determine the investment strategy and minimize the user acquisition cost (CAC).

2. Activation

New users are converted into active users after sedimentation. If the absolute number of active users is low, or the ratio to the total number of users is low, it means that the quality of users is not high. We should conduct in-depth analysis based on dimensions such as channels to determine whether the target user group is accurate or whether there are any problems with product usage. On the contrary, if many users are obtained through different channels such as terminal pre-installation (flashing) and advertising, and there are a high number of active users, it does not absolutely mean that the user quality is high and there are no problems with product use. In-depth analysis and judgment should be combined with other indicators. These users enter the App passively. How to convert them into active users is the first problem operators face.

3. Retention

After solving the problem of activity, another problem was discovered: "Users come and go quickly." Sometimes we also say that there is no user stickiness or retention.

We need indicators that can be used to measure user stickiness and quality, which is a means of judging whether the App can retain users and grow the number of active users in the early stages. From an operational perspective, what we need to care about is which channel will have a better effect, find the best channel, continue to invest, reduce costs as much as possible, convert more users, and reduce the number of channels from dozens to the last few. This requires a decision, and retention is one of the means.

4. Revenue

Obtaining revenue is actually the core part of operations. The factors driving revenue growth are becoming increasingly evident on the mobile side. There are three main sources of revenue for mobile apps: paid applications, in-app purchases, and advertising. In either case, revenue comes directly or indirectly from users. Therefore, the aforementioned increases in activity and retention rates are necessary foundations for generating revenue. Only when the user base is large can revenue increase.

5 Refer Self-propagation

The rise of social networks has added an aspect to operations, that is, viral dissemination based on social networks, which has become a new way to acquire users. This approach is low cost and has the potential to be very effective. The only prerequisite is that the product itself must be good enough and have a good reputation.

6 2A3R methodology upgraded to 3A3R methodology

It is difficult for traditional enterprises to successfully master the 2A3R theory when entering the field of mobile Internet operations because there is a large gap in awareness among their teams. In order to make the 2A3R methodology truly help enterprises operate apps, TalkingData expanded the 2A3R theory into the 3A3R theory. The original classic theoretical framework remains unchanged, with the addition of an A (awareness), which represents awareness or understanding of digital mobile operations. This Awareness runs through all operational links, and through data collection and analysis, it improves user management, product management, and channel management, and finally creates a closed loop of mobile digital operations.

7. Traditional enterprises need to jointly operate apps with mobile Internet companies

The awareness in 3A3R is very important to traditional enterprises. It cannot be achieved through simple theoretical training. Team members are required to participate in all aspects of 2A3R of mobile operations and learn from the experience and technology of the mobile Internet operation team. There are no mobile operators or product operators in traditional corporate organizations, and the existing teams lack practical experience in mobile Internet App operations. But they have high business acumen, are familiar with the business, and can improve their products based on data analysis . Mobile Internet operators are familiar with data analysis, understand the needs of mobile Internet users, are familiar with statistical analysis tools, and have strong practical experience. They use data analysis to understand customers and make suggestions on product management, channel management, and user management. Mobile Internet companies can help traditional companies operate apps well, improve customer experience, and activate customer transactions.

If traditional enterprises want to take the lead in mobile Internet, they should build mobile apps into their main business portal in the future to increase customer stickiness and improve customer activity and transaction volume. It is recommended to work together with mobile Internet companies to operate mobile apps, use mature tools and methodologies to analyze customer behavior, optimize digital advertising channels, improve product design, enhance customer experience, and manage customers well.

Digital mobile operations are a stage that all companies, including financial companies, must go through in the future. Jointly operating apps with mobile Internet companies that have data, tools, methodologies, data mining and analysis capabilities will become a powerful tool for many financial companies, including Internet financial companies, to gain a leading position in mobile app operations, and it is also a shortcut to win the market in a short period of time.

2. Statistical Analysis Tools for Digital Mobile Operations

Now that we have the 3A3R methodology, if companies want to create an enviable App, manage their users well, and obtain higher revenue from the App side. Businesses need to use data for customer and product analysis. Mobile app statistical analysis tools can support the implementation of the 3A3R methodology and help companies achieve a closed loop of data management.

In the PC Internet era, Google Analysis and Baidu Statistics are the mainstream tools for web page analysis. PV, UV, Traffic Source, and Flow Report are called key business indicators. These web-based statistical tools are all visit-centric, revealing website visit statistics and channel conversion status.

In the era of mobile Internet, data analysis will shift to a user-centric approach, analyzing users’ access behavior on apps. Through custom events, we can understand key indicators such as user access behavior, marketing channel conversion rate , product conversion rate, user experience, etc. DAU, MAU, retention rate, conversion rate, ARPU, sales, etc. have become key indicators of mobile operations.

Mobile app statistical analysis tools, famous ones abroad include Mixpanel, Flurry, Localytics, etc. Among them, Mixpanel focuses on user analysis, while Localytics focuses on product analysis. Well-known domestic mobile statistical analysis tools include Umeng and TalkingData. Among them, Umeng mainly serves developers and focuses on product analysis of apps. TalkingData's tools are developed based on the 2A3R theory, serving developers and mobile App operation teams, focusing on user analysis and business analysis. The functions of the two tools are not much different. Umeng has better visualization, while TalkingData has strong business analysis capabilities and is suitable for business operation analysis of mobile apps.

The statistical analysis platforms of other domestic software manufacturers were launched relatively late. Faced with the complex domestic Android environment (tens of thousands of Android device models), the SDK compatibility may not be very adaptable. In addition, there are fewer customers and the product iteration is slow. Some statistical analysis tools still bring the methodology and key operational indicators of PC Internet statistical analysis to the mobile Internet, which have little relevance to business operations.

Statistical analysis tools have a wide range of business application scenarios, and the collected data can effectively support business development and provide data support for product marketing and channel optimization. With the help of statistical analysis tool SDK tracking, enterprises can obtain a large amount of operational data and understand the key indicators of business operations. The data application scenarios that the statistical analysis platform has an impact on enterprise app operations include:

1. Optimize advertising channels and improve advertising ROI

By using data from statistical analysis platforms, companies can understand which app stores customers mainly download apps from, and can increase investment in these channels, reduce app customer acquisition costs, and improve digital advertising ROI.

In addition, by combining external data, companies can understand which channels have good traffic generation effects and high advertising ROI, and optimize their investment in mobile advertising .

2. Determine whether the problem lies in user experience or product design

The statistical analysis platform can embed points and collect data on each click page. For example, if a product requires five steps from entering the App page to purchasing, if a large number of customer churn occurs in the fifth step, it means that there is a problem with the product design and the customer decides not to buy the product at the last minute. If a large number of customers are lost in the second step, it means that there is a problem with the App user experience and customers are unwilling to learn more about the product. The reasons why users leave are also very complicated. Here we mainly judge from a probability perspective and do not include unexpected situations such as crashes.

3. Find the user group that is most valuable to the company

Companies prefer users with high loyalty and high value. High loyalty means that customers frequently purchase the company's products, and high value means that each customer creates higher value for the company.

Statistical analysis platforms can use data to help companies find customers with high activity and high transaction value. Companies need to customize products for them, market them individually, and serve them well. Referring to the Pareto 80/20 rule, companies can gain more profits from this group of customers.

The marketing cost of old customers is one-fourth of that of new customers. By using this data, companies can find more highly loyal customers, expand the proportion of their loyal customers, and tap into more high-value customers. By using old customers to promote products, the conversion rate will increase. At the same time, since they are high-value customers, the revenue they bring to the company will also be higher. This 80/20 rule applies to the financial industry.

The more high-value, high-loyalty users a company has, the easier it will be for the company to shift from operating products to operating customers, and to gain more profits by operating customers. For the other 80 percent of long-tail customers, companies need to invest less marketing expenses to maintain appropriate activity and retention rates.

4. Plan the marketing position and life cycle of products in the App

Mobile apps have a very small space, and which product is listed on the app’s homepage and in a prominent position will have a greater impact on the product’s conversion rate. The product life cycle in the App and the marketing costs invested will affect the revenue that a single product brings to the company.

By utilizing the custom events of the statistical analysis platform, companies can learn which products have high click-through rates , fast user growth, high product conversion rates, and which products create the most value for the company. Companies can arrange the columns and display times for different products within the App based on data analysis. For hot-selling products, better display positions will be provided and their display time will be extended. For products with declining conversion rates and user clicks, companies can remove them from the App and make way for other new products.

The product analysis data from the statistical analysis platform can help companies make scientific decisions and achieve refined product operations. Ensure the maximum benefits for enterprises in product operations on the mobile App side.

5. Launch promotional activities appropriately based on data analysis

The user's active time and activity level have a great impact on the effectiveness of advertising push within the advertising app. If ads are launched during a period when users are inactive, the conversion effect will not be ideal. Similarly, when users are already very active, their advertising will not significantly improve business, but will instead cause customer disgust.

The data from the statistical analysis platform can tell companies which time periods users are more active, and launching advertisements during these time periods will be very effective. The statistical analysis platform can also tell companies about the activity of the App. Once user activity decreases, the company should use the data to find the cause, launch promotional ads, and activate users.

There are many commercial application scenarios for mobile statistical analysis platforms, including A/B testing, user life cycle management, product ROI measurement, product life cycle management, channel optimization, etc. Mobile statistical analysis platforms are becoming an essential tool for digital operation apps.

3. Business secrets told to us by Growth Hacker

The digital operation of mobile Internet mainly focuses on user operation and business operation. There are many factors that affect user operations and business operations. Let’s use the data to see what business secrets Growth Hacker tells us.

The days of spending money to build up users are gone.

Last year, the activation cost of a single application in mainstream channels was 5 yuan, and the activation cost of a single application for special applications such as e-commerce and games reached dozens or even hundreds of yuan. The days when you could just spend money to increase the number of users are no longer there. All companies must rely on technology and data to manage users and use the power of technology to increase customers. Data analysis, user acquisition, product development, cultural construction, and talent recruitment have become the five key points to ensure user growth. Growth hackers are a group of people who use technology and data to achieve user growth.

Qualities and skills that a growth hacker should possess

Growth hackers are data-driven, goal-focused, detail-oriented, creative, and well-informed. Engineers and people responsible for mobile app operations are probably the people who are closest to and most likely to become growth hackers. It requires not only ideas, but also the ability to turn ideas into actions, including self-developed tools, sample collection, data analysis, and large-scale promotion. Growth hackers themselves should also be professional user researchers, moving between product, operation, R&D, design, user research and other links. They are both adhesive and lubricant. They must not only connect various links in the product development process, but also smooth out factors that cause obstacles and reduce the possibility of failure and jamming.

Growth Hacking Soft and Hard Skills

Growth hackers need to establish a "T"-shaped knowledge structure, be able to easily grasp cross-border knowledge horizontally and combine it organically, and be proficient in a certain field vertically, even reaching a depth that others can hardly achieve. Passion, intelligence, curiosity, resources, influence, open-mindedness, inner strength, and obsessive-compulsive disorder are all soft powers of growth hackers. Growth hackers must use tools and data analysis to achieve user growth, and statistical analysis tools based on user behavior become their basic tools.

How to solve the cold start problem

Cold start is a huge challenge facing App developers and product operators. Didi’s first taxi company cooperation came from ground promotion. At that time, the team did not have absolute confidence that this model would definitely work, so they talked to all the taxi companies in Beijing one by one. If no one was willing to cooperate in the end, they would give up. In the end, only a small taxi company was willing to cooperate. They seized this opportunity and quickly achieved a breakthrough in zero users for the product. In the end, like a snowball, the companies that initially rejected them also gradually cooperated. This is a story about the cold start of a product in the O2O field, but it is also an inspirational story and a true story. Circles, industry leaders, push , self-media, water army, ground promotion , disguising yourself as a customer, etc. can all be ways to cold start.

LinkedIn’s Magic Number 4

Linkedin used A/B testing to investigate the number of customers that newly registered users were willing to invite. After repeated testing, it finally determined the magic number of 4. When new users arrive at the "Invite Friends" page, if the system defaults to suggesting that users invite fewer than 4 friends, they are likely to easily ignore this step. If there are more than 4 people, it may make users feel anxious and troublesome; when there are exactly 4 people, the maximum invitation conversion rate can be achieved.

A/B testing tells us which solution customers prefer, reflects customer needs through data, and provides support for decision-making.

The importance of incentives for app activity

Didi Chuxing has an algorithm and data processing team of more than 300 people. They need to analyze and match massive amounts of user taxi data in real time every day. The daily transaction volume of orders alone is in the millions. Didi will analyze the user profiles of drivers to understand their practical behaviors, such as the places they frequently appear, the time of their shifts, and the circumstances under which they will reject orders. Didi found that in certain scenarios, drivers were reluctant to accept orders, so Didi designed an incentive system called "Di Mi". When drivers accept a job, they will increase or decrease Di Mi based on the difficulty of the order. Popular orders will have Di Mi deducted, while difficult orders will be rewarded with Di Mi. The more Di Mi a driver has, the greater the possibility that he or she will grab good orders.

Through a mechanism similar to game points, drivers are more motivated to grab orders in certain scenarios, while also meeting customers' needs to get a taxi during peak hours. The incentive mechanism plays a big role in the activity of the App.

Dormant customers are a great asset for enterprises

A survey by Bain & Company in the United States shows that in the business world, a 5% increase in customer retention means a 30% increase in company profits, and the success rate of selling products to old customers is three times that of new customers. Retaining existing customers is better than developing new customers.
The author is very worried about the dormant customer ratio of over 60% in some financial institutions! It is said that some banks have more than 80% dormant customers, which is a huge waste of customer resources.

Retention rate determines the activity rate of the App

As long as the retention rate of an e-commerce website is maintained at 20%-30%, its survival will basically not be too bad. If a social media company has a monthly retention rate of less than 80% for its first batch of users, it can basically forget about growing big. If you want the game's DAU (daily active users) to exceed 1 million, then the new user's next-day retention rate should be greater than 40%, and the 7-day retention rate and 30-day retention rate need to be greater than 20% and 10%. This is the popular 40-20-10 rule.

The three types of mobile applications with the highest retention rate are consulting and reading, social communication, and system tools, with a four-month retention rate of around 10%. It would be great if the 30-day retention rate of financial industry apps could reach 10%.

Push function is very helpful for mobile app activity

According to a survey conducted by mobile research company Ubran Airship on 2,400 applications and 500 million push notification samples, the daily launch rate of the App can be increased by 540% after the mobile push function (Push) is enabled, and sharing on social media can be increased by 30%. The average usage time of users who enter the App through push is 30% higher than that of users who enter the App normally, and the 6-month retention rate is also greatly improved.

Use the human psychology of winning a jackpot by chance to promote products

When an Internet finance company was using gift vouchers to promote its products, it found that by giving one person a 20-yuan registration gift voucher, it could get nearly 3,000 people to register within a few days, and the gift vouchers given out would be worth 60,000 yuan. If the activity was changed to after a successful registration and transaction, users would have the opportunity to win a grand prize of 10,000 yuan. It was found that more than 5,000 people registered for the transaction, and the gift vouchers finally given out were worth only 20,000 yuan. Promotion costs decreased by 60% and customers increased by 50%.

Mobile Internet users have a gambling mentality of taking chances. Most users are willing to sacrifice small benefits (20 yuan) to gain a greater profit of 10,000 yuan, just like many people are willing to spend two yuan to buy lottery tickets to win a 5 million jackpot. Mobile apps can use everyone's mentality of taking chances to promote themselves.

Note:

The introduction to 2A3R in the first part of this article comes from the book "The Art of Game Data Analysis" written by Yang, and the first 9 viewpoints in the third part come from "Growth Hacker" written by Fan Bing. These two books are both treasure troves of digital mobile operation apps and are worth reading carefully.

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