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Today, I will talk to you about the accurate attribution of how to achieve App user growth, which may not be well understood by many people. in order to make you understand better, the editor has summarized the following content for you. I hope you can get something according to this article.

In order to achieve the rapid growth of users, online advertising aimed at promoting App is an important way for many platforms to obtain new users. With the development of mobile Internet, the channels of App promotion are becoming more and more abundant. In addition to WAP sites and third-party App, HTML5 has become another main battlefield of App promotion.

The appropriate promotion platform has been selected, and the budget (in theory) has also been put in place. As an important part of facing users directly, if we do not do a good job in tracing and evaluating the effectiveness of the launch, it will directly affect the whole process of user growth and fall short of previous efforts.

App activation refers to the behavior of a new user opening App for the first time. After a round of advertising, the attribution analysis of the App activation channel is one of the main ways to locate the user source, effect evaluation and promotion cost accounting.

Traditional App Activation Channel Attribution

At present, the common attributions of App activation include device number attribution, channel number attribution, IP+UA attribution and so on. The following are briefly introduced.

1. Equipment number attribution

Device number attribution is mainly applied to the promotion of third-party App, and the application scenario is mainly information flow advertising.

In most cases, the third-party App can obtain the device number of the user's mobile terminal, such as the IDFA of the device under the iOS system and the IMEI of the Android device. Therefore, in advertisements such as information flow, the click data fed back to advertisers by third-party platforms usually contains the user's device number information. When the user completes the activation of downloading the App, the obtained device number can be matched with the device number fed back by the third-party advertising platform to evaluate the delivery effect.

The attribution in this way is relatively accurate. However, it is important to note that in order to get more accurate analysis conclusions, we will use multiple attribution methods at the same time, generally speaking, the device number attribution has a higher priority. This creates a problem, and activation through other forms of promotion is likely to match the device number attribution in the first place. For example, after clicking on the information flow advertisement, the user does not have the desire to download App, but then clicks on the HTML5 advertisement and urges it to complete the behavior of downloading and activating App.

According to the calculation of Last Click (last click) commonly used in the industry, it should actually be attributed to HTML5 advertising. However, the HTML5 channel is unable to obtain the user's device number information, so this behavior is likely to be attributed to the higher priority form of information flow, resulting in errors.

two。 Channel number attribution

"Channel number" means the channel ID written to the installation package. Generally speaking, the channel number will be written into the APK installation package in advance and then distributed to different channels. The channel number will accompany the entire life cycle of the installation package. After the user activates App, the channel number identification information can be obtained from the installation package for matching, so it is also a relatively accurate attribution in theory.

However, this method will be intercepted by mobile application manufacturers, and it is also easy to be cheated by bad channels, so it is impossible to effectively evaluate the real effect of online promotion.

3. IP+UA attribution

IP+UA refers to the attribution analysis by associating the IP and User-Agent (UA for short, which is used to extract the user's operating system, version number, mobile phone model, etc.) information when the user clicks on the advertisement with the activated IP and UA. Generally speaking, short chains are used to collect these two information. The advantage is user-friendly, convenient management, convenient information collection and setting.

IP+UA attribution is mainly used in Web site diversion, SEM promotion and some advertising scenarios that can not be attributed by device number and channel number, such as HTML5 advertising, WAP advertising and so on. Therefore, although IP + UA is also a main attribution, it is essentially a kind of fuzzy matching attribution, because this method can not directly obtain accurate information such as the device number of the user client, and the user's IP and UA parameters are easy to change and repeat with the environment, so the priority of use is low.

For example, in the office environment network, when multiple users use the same IP, or multiple users who activate App use the same mobile phone brand and model, it is difficult to achieve accurate attribution. To make matters worse, the IP of the user clicking on the advertisement is likely to be inconsistent with the IP when it is activated. For example, the user clicks and downloads the App in the Wi-Fi environment, but it is activated in the 4G environment. Due to the change of the network environment, the IP address will change accordingly. For example, IP is the same in the same network environment, A user clicks on the advertisement but does not download it, B user does not see the advertisement, but directly downloads App through the application market is activated, and the two users' mobile phone brand and model are exactly the same, that is, the UA is the same, in these cases the attribution of IP+UA is completely invalid.

Due to these problems in IP+UA, the priority of using this method is low, but it will cause the above-mentioned HTML5 advertising promotion to be matched to the information flow advertising channel.

Summary

To sum up, it is very important to improve the accuracy of different channel attributions and reduce the possibility of analysis errors.

In the process of investigation, we found that some existing schemes have been optimized on the basis of IP+UA, such as attribution by calculating the correlation degree between registered users and short-chain nodes, and changing the matching algorithm on the basis of the existing IP+UA to achieve the purpose of attribution. However, these methods are basically tuned around the two parameters of IP and UA, and the problem of attribution errors in the case of IP changes or the same effective information of UA mentioned above can not be avoided.

User unique identity Attribution Analysis based on Clipboard

In order to deal with the failure to obtain the device number (for example, users turn off advertising tracking), or the low accuracy of using IP+UA in HTML5 or WAP advertising scenarios, we design a scheme based on "clipboard" attribution to improve the accuracy of channel attribution.

The characteristic of using clipboard for attribution analysis is that it can improve the attribution accuracy in HTML5, WAP and other advertising scenarios where the device number can not be obtained, and reduce the noise caused by device number matching.

1. Realization process

The specific process is shown in the following figure:

(1) in HTML5, WAP and other advertisements, when the user clicks on the advertisement, a unique logo is written to the clipboard.

(2) when it is written to the system clipboard, it is uniquely identified by the server record user

(3) after the user downloads App and activates, the App reads the clipboard information that conforms to the rules and reports it to the server.

(4) the unique identification recorded when the server is associated with the click and the unique identity reported after App activation are attributed.

two。 Main advantages (1) users have unique certainty

The main problems mentioned above in short chain matching of IP+UA include:

The change between the IP address and the active IP address of the data clicked by the user cannot be attributed at all, and it is common for users to switch in the network environment.

Attribution errors caused by the same network environment (same IP), different users but the same device type (same UA)

In the way of clipboard attribution, when the user triggers the click, a tag in the shape of special character + random string + characteristic character is written to the user's different operating system (Android, iOS) clipboard, such as $f803489a $), forming the unique identity of the user of the current click advertising information. When the user downloads App for activation, the client will read the unique ID in the clipboard and report it to the server. After receiving the information, the server verifies and stores the rules, and performs the association matching of the unique identity when App is activated, so as to achieve accurate attribution, which effectively solves the problem of attribution error through IP+UA in HTML5, WAP and other delivery scenarios.

(2) it is commonly used in Android and iOS systems, and it is easy to obtain data.

The clipboard can be used in Android and iOS systems. It is easy to read and obtain data, and effectively builds a bridge between advertising such as HTML5, WAP and client App. And since IMEI (Android device number) will not be available after the Android Q version, clipboard attribution will likely be applied to more scenarios.

(3) the rules for generating identification information are flexible.

The unique identification information written to the clipboard can be generated according to any rules, as long as the content that can be distinguished from other clipboards can be used to uniquely indicate the source of an advertisement click. At the same time, the identification information of the delivery site can be added to the identification, so that App can carry out preliminary verification of channel information when reading clipboard information, so as to reduce the reporting of useless information.

3. Application

At present, in the attribution analysis of hornet cell user growth activation, after the application of clipboard attribution, the overall attribution accuracy is improved by more than 11%.

In the attribution analysis, because the unique identification can identify the channel source of the user, we can give priority to the clipboard attribution, and then use IP+UA as an auxiliary verification means to improve the accuracy of attribution analysis. It is suggested that the unique identification attribution based on the clipboard can be matched with the device number attribution at the same priority. For example, when using the Last Click determination form, the most recent click of the device information can be found according to the device number, and the time can be compared with the advertisement click corresponding to the unique identification, and the click with the nearest time distance can be taken as the promotion source, so as to achieve the purpose of reducing the equipment number attribution error.

Summary

Accurate attribution is very important in App promotion. For example, the current cost of promoting a tourism App ranges from a few yuan to dozens of yuan, and the analysis error caused by traditional attribution is likely to cause double losses. More importantly, if we cannot accurately analyze which channel brings users, we cannot accurately evaluate the promotion effect, and the continuous optimization of user growth is out of the question.

Accurate attribution analysis is the cutting edge of fine operation, and the hornet cell user growth team will continue to explore as many neglected scenarios as possible to tap those valuable traffic and new entrances.

After reading the above, do you have any further understanding of how to achieve accurate attribution of App user growth? If you want to know more knowledge or related content, please follow the industry information channel, thank you for your support.

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