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Marketing strategies have altered dramatically in recent years to meet ever-changing consumer demand in the digital era. There's unprecedented demand for real-time data analysis among enterprises that stand to benefit from more agile decision-making.
What is real-time analysis?
Real-time analysis is a feature in HUAWEI Analytics Kit that helps collect, process, and analyze app data with nearly zero latency. It is capable of conducting event analysis, user trend analysis, hot event composition analysis, as well as location-, model-, and app version-based top N analysis for the most recent 30 minutes. This provides crucial insights into real-time user behavior and empowers you to adjust product operation policies to adapt to real world conditions.
What benefits does real-time analysis offer?
With real-time analysis, product operations personnel are able to determine the stability of user behaviors by monitoring changing trends for key indicators, and fully leveraging this vast range of information to perform multi-dimensional analysis. This in turn enables them to propose marketing policies that are tailored to different regions and device models.
When is real-time analysis most effective?
Scenario 1: A shopping mall plans to launch a sales promotion, and has partnered with a travel app with the goal of guiding more customers to the shopping mall during the promotional period.
Travel app operations personnel can determine the points in time when users are most active, based on user and event count trends over the previous 30 minutes, as well as longer term fluctuations. They can send push or in-app messages related to the promotion to users at specific time points. This can result in higher message click-through and conversion rates.
Summary: In this scenario, real-time analysis supports high-precision marketing and promotional activities, by providing accurate time-based data for operations personnel to send push or in-app messages.
Scenario 2: After a new version of a fresh food app is released in gray mode, operations personnel can determine how popular the new version is by observing how it is being used.
Operations personnel can monitor real-time trends for hot events, and draw a diagram to compare hot events from multiple dimensions, including by event, location, device model, and app version, to determine the popularity of the new app version.
They can also analyze the locations, device models, and app versions of hot events over the previous 30 minutes, to get a better grasp of user features, and adjust the gray release policies accordingly.
Summary: In this scenario, real-time analysis provides for optimal gray release policies, by enabling operations personnel access to determine the popularity of the new app version by region and by device model.
Visit the Huawei Developers website to learn more about HUAWEI Analytics Kit.
Good examples of scenarios where this would be really useful.
Lots of apps these days are finding it difficult to maintain user growth. The main reasons for this are that the demographic dividend for users has gradually subsided, user bases and growth rates are decreasing, and some apps even have negative user growth. Also, competition in app categories such as e-commerce, lifestyle, and gaming is on the rise, while the retention rate of new users is dropping. Low user acquisition and retention rates have been long-standing challenges for app operators.
So how do app operators resolve this pressing issue?
One obvious solution is to leverage data to search for growth opportunities in the entire user lifecycle, and to maintain growth through refined operations.
The first step of refined operations is to divide users into different phases of the user lifecycle. With HUAWEI Analytics Kit, the lifecycle of a user can be divided into the following phases: beginner, growing, mature, inactive, and lost.
For beginner users, growth plans should be made based on maximizing return on investment (ROI) and user activation to ensure that you can quickly acquire the users you want and then convert them into growing users.
For growing and mature users, the key areas of focus is to improve retention and conversion rates. It is very important to maximize the value of these users and make them more active and stable.
For inactive and lost users, prevent user churn, try to win back lost users, analyze the causes of churn, and optimize user activation promotion plans.
1．For Beginner Users: Reduce the User Acquisition Cost, and Promote User Activation and Growth
How can HUAWEI Analytics Kit help you reduce user acquisition costs in the beginner phase? It does so by providing you with various analysis capabilities such as event analysis and comparison analysis, which allow you to view event trends and the distribution of event-generating device models and operating systems. Then, we can use the filter to perform comparison tests of different types of events and select the optimal channel to place services.
How to promote activation and growth of beginner users? This can be done by guiding users to complete key operations based on their interests. For example, for video apps, guide users to watch videos for a certain period of time or purchase membership; for game apps, help users pass early levels; and for e-commerce apps, enable users to place the first order within a short period of time. Then, perform funnel analysis and attribution analysis to analyze the conversion rates of users based on their behavior at key nodes when using apps, so that you can optimize the process, improve the provisioning mode, and UI design of individual nodes.
The app delivered ads to acquire new users in various ways. However, the problem was that the contribution rate of each channel cannot be accurately calculated, and the user churn rate was high.
By using the attribution analysis model of HUAWEI Analytics Kit, operations personnel of the app defined the target conversion event as "new download and use", and the to-be-attributed event as "ad clicks on each channel". According to the generated report, channel A had the highest contribution rate, while channel B had the lowest. So they shifted their marketing budget from channel B to channel A. After three months of optimization, their user acquisition costs decreased by 26% and the new user retention rate increased by 15%.
2.For Growing and Mature Users: Promote User Activation and Retention, and Increase the User Conversion Rate
In addition to user activation and retention, we must also focus on the user conversion rate. How to retain and convert users is a common challenge for most apps. For retention, perform path analysis to detect the actual behavioral paths of users when they are using apps, then check whether the paths are different from the designed ones. If not, we can guide users to the designed paths by operational means. In addition, funnel analysis can also be performed which will give you an intuitive picture of the conversion rate and churn rate of each phase, which facilitates app optimization. For conversion, use both the filter and behavior analysis model to analyze users by segment, and to know the behavior characteristics of different users. After that, use audience analysis model to segment users for precise services based on the analysis result, thereby increasing the user conversion rate.
The operations personnel of the app found that the user retention rate and purchase conversion rate in the last two months had decreased. How did they quickly solve the problem? Operations personnel first segmented users based on user attributes (such as the gender, age, region, and phone brand) and user behavior (such as browsing products, adding to cart, and purchasing). Then they figured out different behavior characteristics through path analysis and funnel analysis models according to the segmented users. It was then discovered that the churn rate from submitting an order to make a payment was the highest. Moreover, inactive users commonly made fewer than three purchases, and functional areas on the homepage were not clearly divided. Based on these findings, the app's operations personnel formulated an optimization solution to improve the purchase conversion rate.
3.For Inactive and Lost Users: Prevent User Churn, Wake Up Inactive Users, and Summarize Experience
Inactive and lost users operations personnel want to see.
For inactive users, the key is to prevent user churn and precisely choose which inactive users to wake up. We can formulate operations policies in advance to avoid user churn based on the predicted user groups that had churn risks or winback potential in each phase based on the user lifecycle analysis model of HUAWEI Analytics Kit. In addition, behavior analysis can help to detect users whether they have the value and possibility to be woken up, as well as to send them messages to try to wake them up. For lost users, it is more difficult to win them back than to acquire new users. Therefore, it is recommended that we focus more on summarizing experience and optimization to avoid churn of active users. For example, figure out the characteristics of lost users, enhance the detection capability before the churn, use data from lost users to help optimize the promotion of current users, and increase the activation and loyalty of active users to avoid user churn by improving operations policies based on funnel analysis, behavior analysis, and comparison analysis.
Let's take a look at how the operations personnel of this game app woke up inactive users. The operations personnel first selected the inactive users who were worthy of and likely to be waken up by performing behavior and audience analysis. It was determined that such users were users who had made at least three in-app payments and passed more than five in-game levels. The operations personnel then designed specific plans for waking up inactive users. The user lifecycle analysis model provided the predicted user groups that had churn risks. Therefore, they avoided user churn by improving user experience and giving users benefits through in-app messaging or push messages. Also, a detailed analysis of the behavioral attributes of churned users was carried out. It turned out that such users had less than 5 friends in-game, and most have complained about the game freezing. The operations personnel then tested and determined the causes of user churn, and optimized their app and operation policies accordingly. Such in-app improvements included providing a multi-channel account sign-in feature, a one-touch friend adding feature, and optimizations to the interaction logic. After optimization, the app successfully decreased the inactive user rate by 12%, and the user churn rate by nearly 8%.(*Source: Developer feedback)
Lastly, let's recap on how to increase the number of users of the entire user lifecycle through the use of the HUAWEI Analytics Kit.
Once you integrate the HMS Core Analytics SDK (Android, iOS, and JavaScript), you can upload user attributes and behavior data, so that the actual behavior of users at a specific time can be displayed, giving you the basis of data analysis. HUAWEI Analytics Kit supports the automatic collection of 11 user attributes and 27 events, as well as customized user attributes and 500 customized events, making your optimizations easier and providing more data for refined operations.
Moreover, it provides abundant analysis models based on the atomic data, such as events, behavior, funnels, audience, lifecycle, and attribution, enabling you to learn about user growth, user behavior, and product functions. Backed by these models, the filter can be used to perform segmentation analysis of app types, user attributes, and audiences. More importantly, it supports various types of apps, including iOS, Android and Web apps to meet your cross-platform analysis needs. You can complete the integration and release your apps in half a day. HUAWEI Analytics Kit has become one of the most popular services globally due to its quick development speed and powerful analysis capabilities. Integrate HUAWEI Analytics Kit today, and explore its myriad of enriching features.
Official website of Huawei Developers
Development Guide
HMS Core official community on Reddit
When it comes to app operations, wouldn't it be great if we could find out where new users come from, check the day-2, day-7, and day-30 retention rates of new users acquired from each channel, find out whether the payment conversion rates of new users vary according to the channel, and what can be done to improve the payment rate, repurchase rate, and other key conversion rates?
Analytics Kit 5.2.0 provides answers to all of the aforementioned questions and more, as well as offering solutions to enhance the conversion rates of new users, thanks to functions such as channel tracking and evaluation of channel resource delivery effects.
Status of channel resource delivery
With the fast-paced development of the mobile Internet and increasingly fierce industry competition, app promotion methods are becoming more diversified, and the cost of obtaining traffic keeps soaring. How to select the best channel and precisely acquire target users has become one of the top challenges.
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The app promotion process consists of six steps, of which the last two are of great significance, as they can tell us which marketing channels and media are most effective in acquiring new users every day, which marketing tasks attract the largest number of users, which types of ads attract the most users, and the top channels in terms of user retention.
Install attribution, which is a new feature in Analytics Kit 5.2.0, can analyze user sources, help operations personnel evaluate ad delivery effects, and enhance ROI, allowing you to perform precise user acquisition.
How to use install attribution
In order to use install attribution, you'll need to design a promotional link based on the requirements outlined by HUAWEI AppGallery or HUAWEI Ads Kit, customize the UTM parameters (for tracking channel traffic), and configure the UTM parameters in AppGallery Connect, before ultimately placing the link on the desired platforms. When a user taps the link to download the app, and launches it for the first time, the Analytics SDK will automatically call the API of HUAWEI AppGallery or Ads Kit to query the UTM parameters, and obtain the marketing channel, type of media, and task used to acquire this user. An install attribution report is then generated.
The detailed process is described as follows:
1. Create an app promotional link according to the requirements of HUAWEI AppGallery or Ads Kit and add UTM parameters.
The following link uses HUAWEI AppGallery as an example:
https://appgallery.cloud.huawei.com/appDetail?pkgName=pkgName&channelId=facebook&referrer=utm_source%3Dsocial%26utm_medium%3Dlink3%26utm_campaign%3DPR%0A&detailType=0&calltype=AGDLINK
2. Go to HUAWEI Analytics > Management > Install referrer in AppGallery Connect and configure your custom UTM parameters.
* Configuration example
3. When a user taps the link, the app download page is displayed. In this case, HUAWEI AppGallery or Ads Kit will record the user's UTM parameters.
4. When a user downloads the app through this link and launches it for the first time, the Analytics SDK will call the API of HUAWEI AppGallery or Ads Kit to obtain the user's UTM parameters and send them to the server for matching.
5. If the matching is successful, an install attribution report will be generated.
* Example of the install attribution report
Install attribution can distinguish between paid traffic and organic traffic, and precisely track sources of new users who install your app. It enables you to view the number and proportion of users acquired by each marketing channel, type of media, and marketing task, providing a foundation for tailoring marketing strategies and enhancing user retention.
Evaluating channel quality
In addition to the number of users acquired, the quality of traffic that a channel attracts is also highly important.
Traffic quality is evaluated in two aspects: retention and conversion. Analytics Kit is equipped with retention analysis for you to compare the retention rates of each channel, for example, day-2 or day-30 retention, so that you can clearly check whether the users acquired by each channel are your target users. As for conversion, if a channel stands out with a payment conversion rate higher than the average in spite of a small amount of traffic, you can decide to invest more resources in this channel. On the contrary, for channels with a large amount of traffic but a payment conversion rate lower than the average, you are advised to reduce the resource investment if the situation does not improve after a period of time, since these channels deliver a poor performance in terms of traffic quality.
* Data for reference only
Install attribution can be used in conjunction with other functions for you to achieve user growth and at the same time ensure high conversion rates.
1. Design a conversion funnel to locate the root cause of churn.
To enhance user loyalty and engagement, it is necessary to design reasonable marketing activities that cater to them. Clear knowledge of users' behavioral characteristics is indispensable in this process.
Analytics Kit supports both session path analysis and a filter function, allowing you to compare the path differences among users from various locations, using different phone brands, and acquired from different channels. This provides a way for you to check whether the actual user behavior path is consistent with the app design.
* Example of the session path analysis report
In the session path analysis report, select a key conversion event and observe the flow direction in previous and subsequent steps of the event to gain an insight into user conversion. If the conversion rate is lower than expected, save the corresponding event path as a funnel and conduct drill-down analysis using the filter in dimensions such as version number, location, device model, channel, and audience. By doing this, you can discover the factors that affect user conversion and design an optimization solution.
* Funnel analysis process
* Example of the funnel analysis report
2. Utilize the attribution model to analyze conversion contributions.
Apart from using the session path analysis and funnel analysis models to locate factors that affect the conversion rate, you can also analyze the contribution rate of each ad slot, marketing activity, and push notification to the target conversion event, summarize the most effective operations strategy for improving the conversion rate, and continuously adjust the operations strategy to promote user conversion.
Let's take an e-commerce app as an example. Its operations personnel adopt multiple methods (such as sending SMS messages, push notifications, and in-app messages) and a wide range of ad slots (including banners, splash screens, pop-up windows, and message bars) to enhance impressions. Users, however, may access the activity page through different entrances. Therefore, what method can be used to find out the most effective measures in promoting transactions?
Analytics Kit's event attribution analysis model can help you find out. Set the Purchase product event as the target conversion event, set events including Tap banner, Tap push notification, Tap pop-up window, and Tap splash screen as the to-be-attributed events, and set Attribution model to either First event attribution or Last event attribution. Once you have done this, the system will intelligently generate a visualized attribution analysis report.
The report paints a picture of the contribution of each to-be-attributed event to the target conversion event. With such data at hand, you'll be able to properly plan ad slot configuration and optimize your operations strategies accordingly, therefore continuously improving the user conversion rate.
About Analytics Kit:
Analytics Kit is a one-stop user behavior analysis platform for products such as mobile apps, web apps, and quick apps. It offers scenario-specific data collection, management, analysis, and usage, helping enterprises achieve effective user acquisition, product optimization, precise operations, and business growth.
For more details, you can go to:
Our official website
Demo of Analytics Kit
Android SDK integration documentation
iOS SDK integration documentation
Web SDK integration documentation
Quick app SDK integration documentation
Original Source
When it comes to app operations, wouldn't it be great if we could find out where new users come from, check the day-2, day-3, day-7, and day-30 retention rates of new users acquired from each channel, find out whether the payment conversion rates of new users vary according to the channel, and what can be done to improve the payment rate, repurchase rate, and other key conversion rates?
Analytics Kit 5.2.0 provides answers to all of the aforementioned questions and more, as well as offering solutions to enhance the conversion rates of new users, thanks to functions such as channel tracking and evaluation of channel resource delivery effects.
Status of channel resource delivery
With the fast-paced development of the mobile Internet and increasingly fierce industry competition, app promotion methods are becoming more diversified, and the cost of obtaining traffic keeps soaring. How to select the best channel and precisely acquire target users has become one of the top challenges.
The app promotion process consists of six steps, of which the last two are of great significance, as they can tell us which marketing channels and media are most effective in acquiring new users every day, which marketing tasks attract the largest number of users, which types of ads attract the most users, and the top channels in terms of user retention.
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"lightbox_download": "Download",
"lightbox_share": "Share",
"lightbox_zoom": "Zoom",
"lightbox_new_window": "New window",
"lightbox_toggle_sidebar": "Toggle sidebar"
}
Install attribution, which is a new feature in Analytics Kit 5.2.0, can analyze user sources, help operations personnel evaluate ad delivery effects, and enhance ROI, allowing you to perform precise user acquisition.
How to use install attribution
In order to use install attribution, you'll need to design a promotional link based on the requirements outlined by HUAWEI AppGallery or HUAWEI Ads Kit, customize the UTM parameters (for tracking channel traffic), and configure the UTM parameters in AppGallery Connect, before ultimately placing the link on the desired platforms. When a user taps the link to download the app, and launches it for the first time, the Analytics SDK will automatically call the API of HUAWEI AppGallery or Ads Kit to query the UTM parameters, and obtain the marketing channel, type of media, and task used to acquire this user. An install attribution report is then generated.
The detailed process is described as follows:
1. Create an app promotional link according to the requirements of HUAWEI AppGallery or Ads Kit and add UTM parameters. The following link uses HUAWEI AppGallery as an example:
https://appgallery.cloud.huawei.com/appDetail?pkgName=pkgName&channelId=facebook&referrer=utm_source%3Dsocial%26utm_medium%3Dlink3%26utm_campaign%3DPR%0A&detailType=0&calltype=AGDLINK
2. Go to HUAWEI Analytics > Management > Install referrer in AppGallery Connect and configure your custom UTM parameters.
* Configuration example
3. When a user taps the link, the app download page is displayed. In this case, HUAWEI AppGallery or Ads Kit will record the user's UTM parameters.
4. When a user downloads the app through this link and launches it for the first time, the Analytics SDK will call the API of HUAWEI AppGallery or Ads Kit to obtain the user's UTM parameters and send them to the server for matching.
5. If the matching is successful, an install attribution report will be generated.
* Example of the install attribution report
Install attribution can distinguish between paid traffic and organic traffic, and precisely track sources of new users who install your app. It enables you to view the number and proportion of users acquired by each marketing channel, type of media, and marketing task, providing a foundation for tailoring marketing strategies and enhancing user retention.
Evaluating channel quality
In addition to the number of users acquired, the quality of traffic that a channel attracts is also highly important.
Traffic quality is evaluated in two aspects: retention and conversion. Analytics Kit is equipped with retention analysis for you to compare the retention rates of each channel, for example, day-2 or day-30 retention, so that you can clearly check whether the users acquired by each channel are your target users. As for conversion, if a channel stands out with a payment conversion rate higher than the average in spite of a small amount of traffic, you can decide to invest more resources in this channel. On the contrary, for channels with a large amount of traffic but a payment conversion rate lower than the average, you are advised to reduce the resource investment if the situation does not improve after a period of time, since these channels deliver a poor performance in terms of traffic quality.
* Data for reference only
Install attribution can be used in conjunction with other functions for you to achieve user growth and at the same time ensure high conversion rates.
1. Design a conversion funnel to locate the root cause of churn.
To enhance user loyalty and engagement, it is necessary to design reasonable marketing activities that cater to them. Clear knowledge of users' behavioral characteristics is indispensable in this process.
Analytics Kit supports both session path analysis and a filter function, allowing you to compare the path differences among users from various locations, using different phone brands, and acquired from different channels. This provides a way for you to check whether the actual user behavior path is consistent with the app design.
* Example of the session path analysis report
In the session path analysis report, select a key conversion event and observe the flow direction in previous and subsequent steps of the event to gain an insight into user conversion. If the conversion rate is lower than expected, save the corresponding event path as a funnel and conduct drill-down analysis using the filter in dimensions such as version number, location, device model, channel, and audience. By doing this, you can discover the factors that affect user conversion and design an optimization solution.
* Funnel analysis process
* Example of the funnel analysis report
2. Utilize the attribution model to analyze conversion contributions.
Apart from using session path analysis and funnel analysis to locate factors that affect the conversion rate, you can also analyze the contribution rate of each ad slot, marketing activity, and push notification to the target conversion event, summarize the most effective operations strategy for improving the conversion rate, and continuously adjust the operations strategy to promote user conversion.
Let's take an e-commerce app as an example. Its operations personnel adopt multiple methods (such as sending SMS messages, push notifications, and in-app messages) and a wide range of ad slots (including banners, splash screens, pop-up windows, and message bars) to enhance impressions. Users can access the activity page multiple times through different entrances. Therefore, what method can be used to find out the most effective measures in promoting transactions?
Analytics Kit's event attribution analysis model can help you find out. Set the Purchase product event as the target conversion event, set events including Tap banner, Tap push notification, Tap pop-up window, and Tap splash screen as the to-be-attributed events, and set Attribution model to either First event attribution or Last event attribution. Once you have done this, the system will intelligently generate a visualized attribution analysis report.
The report paints a picture of the contribution of each to-be-attributed event to the target conversion event. With such data at hand, you'll be able to properly plan ad slot configuration and optimize your operations strategies accordingly, therefore continuously improving the user conversion rate.
About Analytics Kit:
Analytics Kit is a one-stop user behavior analysis platform for products such as mobile apps, web apps, and quick apps. It offers scenario-specific data management, analysis, and usage, helping enterprises achieve effective user acquisition, product optimization, precise operations, and business growth.
For more details, you can go to:
Our official website
Demo of Analytics Kit
Android SDK integration documentation
iOS SDK integration documentation
Web SDK integration documentation
Quick app SDK integration documentation
How is the sales conversion rate? Which categories of products are most popular? How can we boost the gross merchandise volume (GMV)? These are just a few of the tough questions that operations personnel are facing these days. As e-commerce has flourished, it is increasingly important to collect a wide range of user-related data, from basic user behavior analysis, such as the numbers of new users and active users, to payment information, including product sales amount and categories. That's why accessing a comprehensive analysis report on the e-commerce sector can be so valuable.
And now, Analytics Kit 6.2.0 is ready to help. It offers e-commerce analysis reports, which display key indicators for e-commerce apps, from dimensions like data overview, payment analysis, user analysis, product sales analysis, and product category analysis, giving operations personnel high-level insight on precision marketing and product strategies. In addition, the intelligent data access function provides event tracking templates and sample code, which spur greater efficiency across the board.
1. Overview of Core Indicators
Data overview can display your app's real-time usage and payment information, such as the number of online users, number of paying users, and payment amount. You can add filter criteria to filter data by platform, app, user attribute, or audience. Such a broad range of data gives you an accurate glimpse at the basic running status of your app.
* For reference only
2. Payment Analysis Indicators, Revealing Business Growth Trends
For the e-commerce industry, payment is a direct indicator for measuring product operations status. With Payment analysis, you can view the payment amount, number of users who have made a payment, average payment amount per user, and other indicators. You can also filter user groups based on the configured filter criteria and time period. For example, to view the payment data of active users in your e-commerce app, click Add filter, and then Audience, before selecting Active users.
* For reference only
* For reference only
3. User Analysis in 10 Dimensions, Providing Key Insight on User Behavior
User analysis shows user growth and behavior through broad-ranging indicators, including the numbers of new and active users, sign-in time segments of active users, number of daily won-back users, average usage duration per user, average usage duration per sign-in, and retention of new and active users. You can compare the appeal of different sharing channels and promotional assets, based on indicators like sharing channels and operations slot clicks.
* For reference only
* For reference only
4. Product Sales and Category Analysis, Helping You Pursue Growth-oriented Strategies
It is important to track sales volumes and the allocation of sales by product category, in order to implement effective marketing schemes.
The Product sales analysis tab page presents a comprehensive overview of sales data, including the GMV, numbers of orders, and product details. The GMV trend card, for instance, clearly shows the recent revenue status. But success is dependent on far more than just overall revenue. In e-commerce, a number of conversion rates, such as the payment conversion rate and the order conversion rate, are critical to success. An increase in the payment conversion rate means that users find your products or marketing activities appealing. To better analyze the conversion rate, you can create a conversion funnel to perform drill-down analysis using the funnel analysis function provided by Analytics Kit.
* For reference only
* For reference only
Product category analysis gives you a breakdown for the allocation of each product category in terms of total sales revenue, with indicators like the number of purchasers and the sales volume. Furthermore, indicators like the percentages of categories with canceled orders, returns, and favorites allow you to see which products are popular, so that you can invest resources in an optimal manner. On the contrary, for products with a large number of canceled orders and returns, it may indicate that they are not popular with users.
* For reference only
* For reference only
As if that were not enough, you can also perform comprehensive and refined analysis on users via the audience analysis, user lifecycle analysis, and funnel analysis functions provided by Analytics Kit.
To learn more, click here to get the free trial for the demo, or visit our official website to access the development documents for Android, iOS, Web, and Quick App.