5 core steps to acquire app users

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Many startups are happy to try to find the next tipping point through channel monitoring. However, before we test the user acquisition channel, we need to ask ourselves the most important question:

How much should you spend to acquire users?

No one wants to run meaningless ads on ineffective channels. Therefore, we all need some criteria: What kind of channels are better? What methods can help us quickly understand users? What are the effective ways to acquire users? What tools and quantitative methods are worth learning from?

Step 0: Three basic questions

Before reaching conclusions on the above core issues, we need to clarify the following three concepts:

1. What is the total lifetime value of a paying customer?

The so-called lifetime value (LTV) is the total revenue generated by your product from the first day a user uses the product to the last time they log in. It can be seen as a long-term accumulation of ARPU value. Traditional LTV calculation is relatively complicated, and business intelligence startup RJ Metrics has developed a calculation tool specifically for this purpose.

But we can calculate the total value of a customer's lifetime with a simple formula:

LTV = (Average Monthly Spending of Paying Users – Gross Profit) / Churn Rate

Among them, gross profit means: the selling price of goods minus the basic cost of product sales, such as support and organizational expenses; monthly churn rate means: what proportion of users will leave, cancel their subscriptions, and stop paying, calculated on a monthly basis.

2. Proportion of paying users

Once the total lifetime value of paying customers is guaranteed to a certain extent, increasing the proportion of paying users will become an effective way to increase the company's receivables.

In the early stage of product promotion, many companies will attract customers by offering free services. Then, through value-added services, some free users will be converted into paying users to achieve revenue growth. Therefore, for us, not every registered user is paying. Therefore, it is very necessary to calculate and improve the proportion and conversion rate of paying users.

Proportion of paying users = Number of paying users / Number of registered users

3. Visitor registration success rate

Through a simple registration rate channel analysis, you can find out the registration conversion rate of users from each channel on the landing page (or the channel download conversion rate of the App):

Number of registered users/ Number of channel visitors

For marketing activities, the goal is usually to obtain some intermediate event data, such as test drive user information, sales lead data, etc. At this time, the calculation method should be as follows:

Number of leads/number of visitors or number of orders/number of leads

For e-commerce companies, since there are no free products, the calculation can be simple:

Transaction rate = number of orders / number of visitors

Now that we have calculated three values: user lifetime value, registration payment rate, and visitor registration rate, we can clearly know how much it costs to acquire a new user and how much it costs to acquire a paying user.

The next five steps will answer our initial question: What methods and tools can help us gain a deeper understanding of and acquire new users?

Step 1: Calculate the cost of user acquisition

Apart from CPS (cost per order) on e-commerce platforms, the other two core cost indicators are: CPA and CPC. CPA calculates the cost of getting a user to register, while CPC calculates the cost of getting a click to the site.

The calculation of CPA for companies that provide freemium products consists of two parts:

1. Cost of acquiring a paying customer

CPPC: Cost of acquiring a single paying user

LTV: Lifetime Value (Basic Question 1)

CPCC = LTV / 3

One-third of the customer lifetime value is the upper limit of your cost to acquire a paying customer.

This restriction doesn’t apply when testing new channels, but when you find a good channel, your optimization goal is to reduce the cost to one-fifth of the LTV.

2. How much should it cost to register a user?

CPA: Cost per user acquisition

CPPC: Cost of acquiring a single paying user

CR: paid conversion rate of registered users (Basic Question 2)

CPA = CPPC * CR

If a portion of your registrations are free or trial users, you need to take this additional factor into account when calculating how much you will earn per user registration.

Note: Some companies that provide enterprise services charge much more than self-service. In this case, the conversion rate from self-service to enterprise services needs to be taken into account. The cost formula for enterprise services is:

Self-service CPA * Enterprise service conversion rate * (Enterprise service LTV/3)

Step 2: Calculate the cost of a single inbound flow

Usually the advertising platform will let you choose a maximum bid for a word click, instead of letting you pay the advertising fee according to the actual number of registrations obtained. This is the value of the "visitor registration rate" in basic question 3, which will help you understand how much of these channel traffic can be converted into registered users.

CPC: Cost per click

CPA: Cost per user registration

CR: Registration rate (Basic question 3)

CPC = CPA * CR

This formula will tell you the cost of acquiring each user. You can use it to check the actual user acquisition cost at a glance to see whether you are making a profit or a loss.

Step 3: Optimize your channels

The above formula tells you how to spend your budget, and event tracking, analytics, and attribution tools will help you continuously optimize the user acquisition cost of the channel.

For example, the cost of bringing in users through Baidu's SEM may be higher than that through SNS promotion (Weibo, Zhihu, etc.). As a senior operator, the LTV value of registered users on each channel must be considered, which will determine the choice of channel.

With the above formula, you can easily evaluate each channel by just entering the relevant numbers. Please note that the above calculations need to have sufficient traffic as a basis for statistical significance. If you find that the user LTV value of a particular platform is too low or the acquisition cost is too high, you can abandon the channel. Or if you find a cheap channel, you might as well give it a try.

Step 4: Related Tools

1. A/B Testing

A/B testing is essentially a split-group experiment. You create a test page that may be different from the original page in terms of title, font, background color, wording, etc. Then push the two pages to all browsing users at the same time in a random manner. Then count the user conversion rates of the two pages separately, and you can clearly understand the pros and cons of the two designs/creative ideas.

In the past, the technical and resource costs of A/B testing were relatively high, but now with the emergence of a series of visualization tools, such as Optimizely, Leanplum, Taplytics, etc., A/B testing has gradually become a common method for optimizing operational strategies.

2. Marketing Automation

That is, event-driven email and notification services. Tools such as Customer.io, Outbound, Vero and Kahuna can help developers optimize the user activation process and increase the purchase rate of registered users through personalized interactive content and real-time interactive channels.

3. Attribution Analysis

If you do a lot of activities, there are many tips to monitor the conversion rate and cost of the activities. Mobile APP data tracking tools are the best tools. GA and domestic tools such as Umeng, Zhuge io, Talkingdata, etc. can easily tell you which channel performs better.

Step 5: Integrate the platform

When the team size is limited, identify a convenient and easy-to-use platform tool to obtain all the data required for the above calculations, and then distribute this data to relevant analysis tools. The advantage of these data analysis platforms is that you only need to complete the embedded development once, and you can check the data required for operations at any time and switch to different statistical analysis methods at any time. Whether it is for optimizing internal team collaboration or improving the efficiency of operational strategies, this is the most time-saving way.