User growth is the top concern for us. In order to realize this goal, we often promote our app through paid channels. This, however, is not a straightforward decision as we need to consider a number of things, such as:
Which channel offers the best traffic?
Which channel offers more traffic even with less resources?
And, how do we maximize the return on investment (ROI) by optimizing resource allocation among channels?
The release of the paid traffic analysis function in Analytics Kit helps tackle these questions. It provides basic information about paid traffic and how it is converted, as well as comprehensively and accurately evaluating paid traffic. This helps facilitate paid traffic, thereby boosting user growth.
1. Gaining Insights into Paid Traffic
Compared with organic traffic, paid traffic takes more to gain — it's logical to expect the latter to bring more value, but the question is how can traffic be accurately measured and its value increase?
This information is available in the paid traffic analysis function of Analytics Kit. The paid traffic report displays paid traffic-related indicators in a specified period, including the numbers of new and active users from paid traffic. Furthermore, the report also includes indicators such as the number/proportion of paying users from paid traffic and average revenue generated by each active user from paid traffic (ARPU), helping you evaluate the quality and value of paid traffic.
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* *For reference only
From this figure, it can be seen that the number of users acquired from paid traffic increased while their payment amount decreased. This consequently led to a drop in ARPU, causing the value of paid traffic to fall.
2. Analyzing the Value of Paid Traffic Channels
The quality of paid traffic varies according to the channel, which is why it is necessary to design differentiated strategies for each channel for controlling operations costs. Now, with paid traffic analysis, you will be able to evaluate the value of each channel for precise strategy optimization.
With the filter, you can view paid traffic data by channel, including the number of users and payment amount. The comparison analysis function is also available for you to compare the performance of different channels in different dimensions.
3. Enhancing Paid Traffic Conversion
Insights gained from the paid traffic analysis report can pave the way for user conversion increase.
On the Paid traffic page, click New user retention, and click the highest 7-day retention rate to save its users as an audience. After that, utilize audience analysis to explore the characteristics of this audience, select audiences with the same characteristics, and then push notifications about activities to enhance user retention and conversion. In addition to new users, this process can also be applied to active users.
Analytics Kit simplifies analyzing user attributes and behavior characteristics in multiple dimensions, helping you identify the most appropriate channel for the best paid traffic, and thereby helping you enhance ROI and achieve sustainable development.
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.
Related
To survive in the market, an app must be optimized and updated on an ongoing basis, in order to remain attractive to users. By frequently improving app design and providing users with new functions and experience, we can maximize user loyalty and extract greater benefits.
However, evaluating the effects of an app update is not an easy task. These include user attitudes regarding updates, feature popularity, and contributions of the app update to the key path conversion rate. Fortunately, Analytics Kit has you covered, giving you access to a wealth of user behavioral data, which is indispensable for performing such evaluations.
1. Comparing adoption rates between different versions
An app may crash after a new version is released, so monitoring its quality is crucial to ensuring an optimal user experience. Real-time analysis of version distribution gives you a sense of how each app version is performing, such as the corresponding numbers of users, events, and crashes, so that you can locate and solve problems in a timely manner.
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The app version adoption rates reveal the versions adopted by all, active, and new users, offering insight on whether the number of users adopting the new version is increasing as expected. App version details are also at your disposal, enabling you to perform drill-down analysis.
2. Verifying app update effects in retention growth
Retention rate is one of the most significant indicators for evaluating app update effects. You can use the filter function to compare new user retentions between old and new versions. If the retention rate of the new version has surpassed that of the old version, we can conclude that the app update is effective for bolstering user retention.
3. Leveraging the funnel model to track the key path conversion rates
In many cases, app functions or UIs are optimized with the aim of enhancing the conversion rate of key paths. For example, adding a banner at the top of the app UI to attract users to the details page can boost the click-through and purchase rates. Let's use an e-commerce app as an example. A typical conversion path consists of five steps: searching for products, viewing details, adding a product to the shopping cart, submitting an order, and paying for the product. With funnel analysis, you'll be able to observe the conversion rate of each step in the purchasing process. If you have made certain changes on the product details page according to user survey results, you can focus on conversions from users viewing product details to adding products to the shopping cart. Please note that a new funnel must be created if the key path steps have changed due to feature updates.
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.
To learn more, please visit:
HUAWEI Developers official website
Development Guide
Reddit to join developer discussions
GitHub or Gitee to download the demo and sample code
Stack Overflow to solve integration problems
Original Source
Core Value
Real-time overview provides real-time data feedback and analysis, which are significant to improve the efficiency of product operations. For key marketing scenarios related to user attraction, such as online operations activities, new version releases, and abnormal traffic warnings, its low-latency data feedback can benefit your agile business decision-making.
Application Scenarios
Scenario 1: Real-Time Evaluation of Activity Traffic
In most cases, after a new user acquisition activity is rolled out online, traffic is monitored hourly or daily. This makes it difficult for operations personnel to accurately locate the root cause of an exception and make timely adjustments, which may hinder the effectiveness of the activity.
Luckily, real-time overview can analyze traffic by the minute and present real-time fluctuations of new users in an app accurately, indicating when the best activity effect is achieved and how to optimize subsequent activities.
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* Test environment data is for reference only.
Scenario 2: Optimization of New Versions
Operations personnel require real-time data to measure the performance and acceptance of new versions, in the face of fast product iterations driven by ever-changing user requirements.
For example, after a game update is released, how the players respond to the new content directly impacts the game's revenue.
To understand how users respond to the update and mitigate its problems, real-time overview can be used as a reference. By referring to real-time overview, you can easily spot abnormal fluctuations, and then quickly optimize your app and take corresponding operations methods.
* Test environment data is for reference only.
Scenario 3: Real-Time View of User Characteristics
Real-time overview helps you understand whether the in-app journey of users matches the product design, whether you have attracted the target users who use specific device models and come from specific places, as well as their in-app behaviors.
The User analysis report clearly displays the real-time distribution of users by each attribute, like channels and countries/regions, in the form of cards.
* Test environment data is for reference only.
With the Event analysis report, you can learn about users' frequent in-app behaviors, so that you can identify the best time to send push notifications and in-app messages.
* Test environment data is for reference only.
How to Use Real-Time Overview
Sign in to AppGallery Connect, click My projects, find your project, and go to HUAWEI Analytics > Overview > Real-time overview.
Visit our official website to learn more.
Are you always wondering how to perform attribution tracking and evaluate the user acquisition performance of different channels in a more cost-effective way? A major obstacle to evaluating and improving ad performance is that users' interactions with ads and their in-app behavior are not closely related.
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Using HUAWEI Ads and Analytics Kit to evaluate E2E marketing effect
Analytics Kit lets you configure conversion events (including app activation, registration, adding to cart, payment, retention, repurchase, rating, sharing, and search), which can then be quickly sent back to HUAWEI Ads for E2E tracking. This can provide analysis all the way from exposure to payment, so that you can measure the conversion effect of each marketing task, and adjust the resource delivery strategy in time. Moreover, HUAWEI Ads can learn the conversion data through models, helping dynamically optimize delivery algorithms for precise targeting, acquire users with higher retention and payment rates, and enhance ROI.
Identifying paid traffic to analyze the user acquisition performance of channels
As the cost of acquiring traffic is soaring, what is critical to the ad delivery effect is no longer just the investment amount, but whether you can maximize its performance by precisely purchasing traffic to enhance traffic scale and quality.
You can use UTM parameters to mark users, and therefore easily distinguish between paid traffic and organic traffic in Analytics Kit. You can compare users and their behavior, such as which marketing channels, media, and tasks attract which users, to identify the most effective marketing strategy for boosting user conversion.
* The above data is derived from testing and is for reference only.
You can also utilize the marketing attribution function to analyze the contribution rate of each marketing channel or task to the target conversion event, to further evaluate the conversion effect.
* The above data is derived from testing and is for reference only.
Moreover, Analytics Kit offers over 10 types of analytical models, which you can use to analyze the users of different marketing channels, media, and tasks from different dimensions. Such information is great for optimizing strategies that aim to boost paid traffic acquisition and for reaping maximum benefits with minimal cost.
For more information about how Analytics Kit can contribute to precision marketing, please visit our official website, and don't hesitate to integrate it for a better ad delivery experience.
For a business to grow, it must be capable of fine-grained and multi-dimensional user analysis, facing the popularity of precise operations. HMS Core Analytics Kit, which has been dedicated to exploring industry pain points and meeting service requirements, can do that. Recently, it released the 6.6.0 version, further expanding its scope of data analysis.
Here's what's new:
Updated Audience analysis, for even deeper user profile insight.
Added the function of saving churned users as an audience to Retention analysis, contributing to the multi-dimensional analysis on abnormal user churn, and boosting timely user retention with the help of targeted strategies.
Added the Page access in each time segment report to Page analysis, making users' usage preferences even clearer.
Added the function of sending back day 1, day 3, and day 7 retention data to HUAWEI Ads along with conversion events, to help you evaluate ad placement.
1. Updated Audience analysis to Audience insight, and added the User profiling report, for deep knowledge of users
In the new version, the Audience analysis menu is changed to Audience insight, which is broken down into the User grouping and User profiling submenus. User grouping contains the audience list and the audience creation function, while User profiling displays audience details. What's more, User profiling has added the Audience profiling module, which presents basic information about the selected audience through indicators like consumption in last 7 days, so that you can make a practical operations plan.
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* This data is from a test environment and is for reference only.
2. Saving churned users as an audience in a click to enhance winback efficiency
Winning back users is vital to any business and this can be even more achievable thanks to clear churn analysis, which helps boost winback efficiency with less effort. In Analytics Kit 6.6.0, we have updated the retention analysis model and added the saving churned users function. This allows you to analyze the behavior features of churned users, and what's more, by combining this function with the audience insight function, you can customize differentiated and targeted operations strategies to win back users effectively.
* This data is from a test environment and is for reference only.
3. Displaying users' preferences for page access time segments, to pinpoint the best opportunity for operations
An abundance of different app types and page functions inevitably leads to varying user preferences for access time segments, making selecting the proper time segments to push content complicated. Fortunately, with Page analysis, you can view the access time segment distribution of different pages. By comparing the number of accesses and users in different time segments, you can fully understand users' product usage preferences and seize proper operations opportunities.
* This data is from a test environment and is for reference only.4. Evaluating ad placement effects through detailed user loyalty indicators
Analytics Kit can send back conversion events, which provides data support for ad effect evaluation and placement strategy adjustment. In the new version, this function has been updated to send back day 1, day 3, and day 7 retention data along with conversion events, helping you better evaluate user loyalty. By using this retention data, you can further evaluate whether the user groups you advertise to are your target users and whether they are loyal, and adjust ad placement to improve the ROI.
Moreover, Analysis Kit 6.6.0 has also optimized functions like Event analysis and Project overview. To learn more about the updates, refer to the version change history. For more details, click here to visit our official website.
For a business to grow, it must be capable of fine-grained and multi-dimensional user analysis, facing the popularity of precise operations. HMS Core Analytics Kit, which has been dedicated to exploring industry pain points and meeting service requirements, can do that. Recently, it released the 6.6.0 version, further expanding its scope of data analysis.
Here's what's new:
Updated Audience analysis, for even deeper user profile insight.
Added the function of saving churned users as an audience to Retention analysis, contributing to the multi-dimensional analysis on abnormal user churn, and boosting timely user retention with the help of targeted strategies.
Added the Page access in each time segment report to Page analysis, making users' usage preferences even clearer.
Added the function of sending back day 1, day 3, and day 7 retention data to HUAWEI Ads along with conversion events, to help you evaluate ad placement.
1. Updated Audience analysis to Audience insight, and added the User profiling report, for deep knowledge of users
In the new version, the Audience analysis menu is changed to Audience insight, which is broken down into the User grouping and User profiling submenus. User grouping contains the audience list and the audience creation function, while User profiling displays audience details. What's more, User profiling has added the Audience profiling module, which presents basic information about the selected audience through indicators like consumption in last 7 days, so that you can make a practical operations plan.
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"lightbox_new_window": "New window",
"lightbox_toggle_sidebar": "Toggle sidebar"
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* This data is from a test environment and is for reference only.
2. Saving churned users as an audience in a click to enhance winback efficiency
Winning back users is vital to any business and this can be even more achievable thanks to clear churn analysis, which helps boost winback efficiency with less effort. In Analytics Kit 6.6.0, we have updated the retention analysis model and added the saving churned users function. This allows you to analyze the behavior features of churned users, and what's more, by combining this function with the audience insight function, you can customize differentiated and targeted operations strategies to win back users effectively.
* This data is from a test environment and is for reference only.
3. Displaying users' preferences for page access time segments, to pinpoint the best opportunity for operations
An abundance of different app types and page functions inevitably leads to varying user preferences for access time segments, making selecting the proper time segments to push content complicated. Fortunately, with Page analysis, you can view the access time segment distribution of different pages. By comparing the number of accesses and users in different time segments, you can fully understand users' product usage preferences and seize proper operations opportunities.
* This data is from a test environment and is for reference only.
4. Evaluating ad placement effects through detailed user loyalty indicators
Analytics Kit can send back conversion events, which provides data support for ad effect evaluation and placement strategy adjustment. In the new version, this function has been updated to send back day 1, day 3, and day 7 retention data along with conversion events, helping you better evaluate user loyalty. By using this retention data, you can further evaluate whether the user groups you advertise to are your target users and whether they are loyal, and adjust ad placement to improve the ROI.
Moreover, Analysis Kit 6.6.0 has also optimized functions like Event analysis and Project overview. To learn more about the updates, refer to the version change history.
For more details, click here to visit our official website.
MOD ACTION:
Thread closed as duplicate of https://forum.xda-developers.com/t/try-updated-functions-of-analytics-kit-6-6-0.4473115/