如何有效分析付費用戶(三)

作者:Vasiliy Sabirov

今天我們將談論再次消費和轉換成付費用戶的時間問題。你應該問自己怎樣的問題?

用戶是在哪一天進行首次消費?第二次消費?第三次消費?

瞭解用戶消費行爲能夠幫助你更好地規劃產品的盈利。這便是傳統的產品分析公式方法:

1.明確用戶行爲模式;

2.找到行爲與該模式相關的用戶;

3.讓這些用戶基於模式採取下一個行動。對於你來說這可能像是模式的邏輯延續,而對於用戶來說,這則是在對的時間出現的具有針對性的內容。

瞭解用戶何時進行第二次付費,如此你便能夠提前提供給他們有趣的活動(或具有針對性的內容)。

舉個例子來說,讓我們使用devtodev分析系統的報告“付費前的時期”。選擇每個用戶的首次付費時間(遊戲邦注:你也可以選擇第二次,第三次或所有付費時間,並且不用考慮序號),確定用戶註冊時間,並着眼於時間和他們首次付費的分佈規律。

period until payments(from gamasutra)

period until payments(from gamasutra)

我們發現大多數用戶的首次付費都是發生在第一天,即在他們註冊應用的那天。這意味着我們可以從用戶進入應用的第一天便開始規劃任何活動。

然而讓用戶在完成教程後馬上購買東西是不合時宜的—-這會讓用戶覺得這是隻關於消費的遊戲,並且他們會馬上離開遊戲。這也是我們會問自己如下問題的原因。

peak(from gamasutra)

peak(from gamasutra)

用戶是在第幾個關卡進行首次購買?第二次購買?以及第三次購買?

再一次地,我們又轉向“付費前的時期”這篇報告並選擇有關關卡的分佈規律。

在這裏峯值是出現在第四和第五個關卡中。

因此我們需要識別一個模式,即付費用戶主要是在註冊的第一天並且是到達第四和第五個關卡的時候開始進行首次消費。

之後我們將能夠添加一個與該模式相關的具有針對性的內容到項目中(一款遊戲或者一個訓練服務)。這將幫助我們提高用戶在第一天轉換成付費用戶的機率。

多少用戶只進行一次消費?多少用戶重複消費了?在首次消費和重複消費間的分佈情況是怎樣的?

讓我們先着眼於一個小小的建議:結合付費用戶參數(付費用戶數量)和付費用戶比例(在活躍用戶中付費用戶的比例)並關注於全新付費用戶參數,這能夠呈現出分析過程中進行首次購買的用戶數量。而如果沒有首次購買也就不用提重複購買了。

讓我們說說重複購買的重要性。Tapjoy評估了一些創造數百萬美元收益的應用並明確了他們的一些共同點。

第一個共同點是:在84%的應用中至少有1000名用戶在進入應用後的90天內至少進行了三次購買,並且它們的收益都突破了100萬美元。

爲了幫助你更好地理解基於付費用戶的消費次數的付費用戶分佈規律,我們創造了“基於交易的用戶”報告。這將幫助你明確多少用戶進行了一次交易,兩次交易等等。

users by transaction(from gamasutra)

users by transaction(from gamasutra)

第二個共同點是:

如果至少35%的用戶進行了第一次消費後又進行了第二次,第三次消費,那麼應用便有可能創造出100萬美元的收益。

第一次消費的規模通常都較小。你能在“付費用戶活動”報告中看到這點:

paying users activity(from gamasutra)

paying users activity(from gamasutra)

進行了首次消費的用戶只想測試在你的產品中花錢會有什麼好處,並且他們並未準備好馬上投入更多錢。此外,首次消費同樣也會讓他們在自己的賬號中綁定信用卡。

而最主要的盈利份額還是來自重複消費。

所以如果你想獲得最終成功,你的產品必須滿足以下條件:

1.應該讓用戶自己想起進行首次消費,但是你可以通過在適當的時候公開模式並提供有趣的內容去推動他們。

2.不要要求用戶在第一次消費時便投入許多錢。第一次消費通常都不會有太多錢。

3.應該讓用戶覺得自己的投資是有回報的,如此他們便會進行首次購買並繼續支付更多錢。

4.你的項目應該讓用戶自願支付自己想要支付的金額。每個用戶,不管是非付費用戶還是鯨魚用戶都必須真正享受你的產品。

5.長期用戶留存是出色盈利的關鍵。如果用戶是非付費用戶,那麼他留在應用中的時間越長,他們消費的可能性便會越高。如果用戶是付費用戶,他們留在應用中的時間越長,他們便有可能花費更多錢。

本文爲遊戲邦/gamerboom.com編譯,拒絕任何不保留版權的轉發,如需轉載請聯繫:遊戲邦

How to analyze paying users. Part 3. Re-payments and conversion.

by Vasiliy Sabirov

Today we are going to talk about re-payments and about the time of conversion into payment. What questions should you be asking yourself?

On what day, the user makes the first payment? The second? The third?

Understanding of user payment behavior will allow you to better plan monetization of your product. This is the usage of the traditional product analytics algorithm:

Identity the pattern of user behavior;

Find the users whose behavior initially corresponds to this pattern;

Offer these users to take next action from the pattern. For you it looks like a logical continuation of the pattern, and for the user – as a targeted offer at the right time.

Knowing when the user makes the next payment, you can get ahead of it and offer the desired campaign (or targeted offer) at the right time.

For example, let’s use the report “‘Period until payments” by devtodev analytical system. Choose the time of the very first payment (you can also choose the second, the third or all payments, regardless of the serial number), set the period of users registration, and look at the distribution of time of their first payment.

We see that the bulk of the first payments is made in the first days, even at the day of registration of the user. This means that we can safely propose any campaign from the very beginning of user’s staying in the app, even from the first day.

However, offering to buy something, for example, immediately after passing the tutorial would not be quite right – the user decides that the game is based only on donations and, quite likely to immediately leave the application. This is why we ask ourselves the following question.

At what level the user makes the first purchase? And the second? And the third?

Again, we turn to the report “Period until payments” and choose the distribution not by days, but by levels.

Aha! Here is the peak on the fourth and fifth levels.

Thus, we have identified a pattern – paying users primarily make the first purchase on the day of registration at the achievement of levels 4-5.

In the future, we will be able to build into the project (be it a game, or say, a training service) a targeted offer corresponding to this pattern. And it will help us to increase the conversion into paying user on the first day.

How many users make one payment? How many users make repeated payments? How are the sums distributed between the first and repeated payments?

Let’s begin with a little advice. Advice: par with metrics Paying Users (amount of paying users) and Paying Share (proportion of paying users among active audience) pay attention to New Paying Users metric, that shows the number of users that made their first payment during the period analyzed. Without the first payment, there would be no repeated ones.

Speaking about the importance of re-payments. Tapjoy company reviewed the applications that made a million dollars and identified a few common signs.

The first sign: 84% of applications, in which at least 1,000 users made at least three payments during the first 90 days from the date of the first entry, overcame the barrier of $ 1 million.

To help you better understand the distribution of paying users by the number of payments made by them, we, here at devtodev, developed a report “Users by transactions”. It allows you to see how many users made one transaction, two transactions and so on.

The second sign, identified by Tapjoy:

If at least 35% of users made the first payment, and then made the second and the third payments, then the application is likely to make a million dollars.

The first payment is usually small in size. You may see this in the report “Paying users activity”:

Users who make their first payment, only want to test the benefit of the paid use of your product and are not ready to immediately spend large sums. In addition, the first payment is also a reason to link the card to the account, if it wasn’t previously linked.

But the main monetary weight is contained in the re-payments.

So to have financial success, your product must meet the following conditions:

1.The user should come to making the first payment by himself, however, you may help him by revealing the pattern and making an offer at the right time.

2.Do not require a large first payment from the user. The first payment is usually small in size.

3.The user should feel the return on investment, then he would be pleased with the first purchase and willing to pay more.

4.Your product should allow a user to pay as much as he wants. Each user, whether he is a non-paying or a whale (the user with the highest check) must enjoy the use of your product.

5.Long-term retention is the key to a good monetization. If the user is non-paying, the longer he is with you, the higher the probability of the payment is. If the user is paying, the longer he is with you, the more he might pay.
At this, series of articles on the analysis of paying users is completed.

Analyze the behavior of those who are paying you, understand where your money comes from and increase your cash flow.(source:gamasutra)