A product will go through many stages in its lifetime. Of these, product maturity involves long-term exploration of how to mine value from existing users for monetization. At this stage, operations personnel commonly launch promotions to encourage purchases and cultivate regular payments. These activities advertise themselves with in-app and push notifications. In-app messages reach users in the app and appear in diverse formats, such as modal, banner, and image. Such messages redirect users to activity landing pages with purchase options, a shortcut to monetization.
However, in-app messages are not always welcome. Not everyone wants their app usage interrupted, and their affected experience can cause user churn. To wisely wield this double-edged sword, operations personnel should first target audiences by attribute and behavior so in-app messages they send are tailored to the audience. Since users in these audiences are more willing to make purchases, they are considered of high value in these operations activities.
Let's learn how a tool app attempted to grow revenue from member subscriptions. It sent its users a daily modal in-app message at a scheduled time, but this activity resulted in a less than 0.1% payment conversion rate. Operations personnel then enabled the Prediction service and adjusted their strategy to message only users with high payment potential. Such users were offered limited-time-only promotions that were tailored to their subscription periods. This adjustment increased the payment conversion rate to over 20%, while also increasing overall revenue and retention rate despite the message audience being smaller.
So how do we leverage the Prediction service to mine users with high payment potential, and App Messaging to send them relevant messages?
i. Identifying high-value audience.
First, target users who are more likely to make purchases based on their attributes and behavior.
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ii. Configuring a modal in-app message.
Next, create a modal message in App Messaging, and set the title, image, buttons, and so on for your upcoming activity.
iii. Selecting a trigger event.
Choose when to display the message. This could be upon app launch or whenever a user launches the password protection module.
iv. Targeting users
Use the Prediction condition and then select the target audience.
Boost your own app's payment conversion with Prediction + App Messaging today.
To learn more, please visit:
HUAWEI Developers official website
Development Guide
Reddit to join developer discussions
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In today's oversaturated Internet, the cost of attracting new users has skyrocketed, and users tend to spend less time on specific apps. According to the data report, the total number of apps downloaded and installed per mobile netizen increased to 60 in 2019. But as the QuestMobile: 2020 Mobile Internet Panorama Ecology Report has noted, the number of apps launched monthly per netizen in 2019 was only 23, meaning that more than half of installed apps have a low launching rate.
Due to this reality, it's essential for apps to establish an effective communication channel with users, and activate users in a timely manner. Message pushing has thus come into being, as the preferred method for helping activate and retain app users.
What Is Message Pushing?
Pushing messages to users via the device notification panel can activate users and enhance their loyalty to your app. However, undifferentiated message pushing can annoy users, even causing them to uninstall apps, in certain cases. Therefore, it's necessary to not only guarantee message content, but also formulate appropriate policies for push messages. Fortunately, Push Kit has got you covered in every regard.
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HUAWEI Push Kit
As a stable, precise, and efficient messaging channel, HUAWEI Push Kit enables you to push custom messages to users in a timely manner, while also archiving valuable notifications.
1. Efficient Messaging Channel for Quick Delivery
You can push messages, even when your app has not launched or is not running in the background, ensuring that users receive messages in a timely manner.
2. Custom Messages for Niche Audiences
You can segment audiences by conditions, such as the device model, system language, or subscribed topic, and send custom messages to each audience. For a news app, you could distinguish between audiences by separating them according to the content that they are most interested in, select the audience for a specific type of content, and send the latest relevant news to them, for example, sending the latest sports news to users who are avid sports fans. This function helps you send messages with greater precision, for an increased user tap-through rate.
3. Scenario-Based Message Pushing
You can trigger automated messaging in real time based on usage behavior or geographical location, when authorized by users, a stark contrast with traditional undifferentiated marketing models. For instance, you could push messages to users who are near a coffee shop, informing them that there are relevant promotion associated with the coffee shop.
4. Diverse Message Display Styles
In addition to the common text, you also can choose from a range of other styles, including large text, emojis, and buttons, in order to improve the efficacy of message displays. If a message is relatively lengthy, you can simply select the large text style to have it displayed across multiple lines. You can also add emoji emoticons to messages, enticing more user taps.
With Push Kit, you'll have access to a range of message customization capabilities, to tailor content to suit users, for optimally efficient and effective user activeness and retention.
Push Kit currently serves over 50,000 high-quality apps, covering 200+ countries and regions, with a staggering 50 billion messages sent on a daily basis. We look forward to working together with you in the future!
Click View Original to view the development guide, or contact us by sending an email to [email protected].
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https://developer.huawei.com/consumer/en/hms/huawei-pushkit?ha_source=z
"And then even the mightiest company is in trouble if it has not worked on the future."
- Peter Drucker
The soaring growth of the mobile Internet brings both a trend of homogeneity in products and fierce competition. Analyzing users with session path analysis allows you to tap into the value of your users and guide their conversion in the lifecycle.
HUAWEI Prediction anticipates user behavior in advance based on user behavior data, helping you make smart and quick decisions.
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1. What is custom prediction?
In our previous posts, we introduced some prediction tasks provided by Prediction. So, what's special about the custom prediction task? Simply put, custom prediction tasks can be used in multiple scenarios.
User churn and payment is an important factor to determine whether a product can be monetized successfully, which is a key concern during product operations. You may also take into consideration other in-app events and their conversion nodes, such as the click-through rate of an in-app ad, or the probability of a player passing a game level. With the help of custom prediction tasks, you can evaluate the probability of user behavior.
Sourced from diversified data reported by your app, and similar to the preset prediction tasks, a custom prediction task uses the active user data from the previous two weeks to train a model, which then predicts the probability that active users from the previous week perform a certain behavior over the next week.
2. Method for starting a custom prediction task as required
Different operations solutions apply to different industries and scenarios. For example, an e-commerce app wants to attract more users and for users to add products to their shopping carts or tap an ad on the home screen, and a game app may want to know the probability of a player passing a level or consuming coins and items.
This post takes game apps as an example for evaluating the probability of a player passing a level using the custom prediction.
To achieve this, your app needs to report game level completion events. First, sign in to AppGallery Connect, click My projects, find your app, go to HUAWEI Analytics > Behavior analysis > Event analysis, and create a COMPLETELEVEL event, which is a preset event. Then mark it as a conversion event, go to Prediction, and create a custom prediction task. After you have selected the COMPLETELEVEL event, click OK.
Currently, you can create custom prediction tasks for automatically collected events, preset events, and custom events in HUAWEI Analytics in the same way.
3. Use cases of custom prediction task results
Since we have introduced the creation of a custom prediction task, let's see how its result can help with your business growth.
From the detailed result, it can be seen that the number of users predicted to have a low probability of completing the game level share a similar location and app version. To solve this problem, you can release different app versions for different countries and regions. Alternatively, you can develop an operations plan to improve the audience's experience and aim to turn them into paid users.
* The screenshot is from the custom prediction details page of HUAWEI Prediction. The data is for reference only.
Your game can recommend improved equipment and game coins to these players, as well as increase the probability of them making in-app purchases. By guiding the players to complete payments, you can turn minnows into dolphins and, eventually, whales.
Implementing this method couldn't be simpler. Prediction can work with AppGallery Connect Remote Configuration without you having to do extra coding.
On the Remote Configuration page in AppGallery Connect, you can choose to display item recommendation pop-ups just to players who are less likely to complete the game for promoting payment conversions. You can also attract players by setting a time limit on a discount for game coins. When your prediction task is updated, its audience is also updated, allowing you to reach target players without disturbing other players.
To learn more about HUAWEI Prediction, feel free to check out this document.
User retention is one of the most important factors you need to consider in your operations. A high user retention rate is a prerequisite for monetization, and is also an important way of defining an app's value. With ever increasing user expectations and competition, user retention has become a major challenge for every kind of app.
To resolve the issue of low user retention, marketing budgets have continued to increase to try to pull in new users. However, the downside to this is that non-organic users are even harder to retain, as such users are not actively seeking to use the app. A better solution would be to accurately predict user churn and take the right actions accordingly.
Luckily, Push Kit and HUAWEI Prediction allow you to do just that.
What Can Push Kit and HUAWEI Prediction Offer You?
Powered by machine learning technologies, HUAWEI Prediction precisely predicts the behavior of specific audiences based on user behavior and attribute data reported from Analytics Kit. Audiences are further divided into several sub-audiences, according to their behavior as predicted by the service. This allows you to take targeted measures to increase user retention and conversion.
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Push Kit is a messaging service that establishes a messaging channel from the cloud to devices. By integrating Push Kit, you can send messages to your app on users' devices in real time. This helps you maintain closer ties with users and increases user awareness of and engagement with your apps.
Push Kit and HUAWEI Prediction Example Usage Scenario
The operations team of a game planned to increase the engagement of users at high risk of churning in the next 7 days, as predicted by HUAWEI Prediction, but who still occasionally opened the app in the last 7 days.
With this information at hand, the app's operations team designed a time-limited event particularly for this audience, and used Push Kit to push messages for the event precisely to the audience.
Experience HUAWEI Prediction for yourself by going to AppGallery Connect > Grow > Prediction.
Click here to learn more about HUAWEI Prediction service.
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
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.