[null,null,["อัปเดตล่าสุด 2025-08-23 UTC"],[],[],null,["**Solution overview**\n\nWhat is ad frequency optimization?\n\nWhether your app is hybrid-revenue or ads-revenue driven, optimizing ads revenue\nand keeping a high-quality user experience can be tricky. Ads are a great source\nof revenue, but a high frequency of ads can provide a negative user experience\nand might lead to user churn.\n\nThere is no \"one ad frequency suits all\" approach for any app; ads performance\nvaries greatly from app to app and from audience to audience. You might be\nconcerned that increasing ad frequency could have a negative impact on user\nexperience or retention, but you might also be curious to see if it could lead\nto an increase in revenue and engagement when instrumented properly, keeping\nengagement metrics in check.\n***Figure 1**: Optimal ad frequency maximizes revenue with minimal impact to churn*\n\nTo resolve these unknowns, Firebase offers tools that help you test and then\nmake data-driven decisions about the optimal ad frequency:\n\n- Using Firebase, you can A/B test the performance of various ad frequencies\n with a *small subset* of users.\n\n- You can observe the test results and review recommendations from Firebase\n about which ad frequency is performing better and with minimal impact on\n retention.\n\n- Once you're confident that the changes will likely have a positive impact,\n you can roll out the changes to more of your users with a click of a button.\n\nBusiness case and the value\n\nDevelopers and publishers using Google AdMob and Firebase tools for\noptimizing their ad frequencies enjoy major revenue uplifts without adversely\nimpacting user experience.\n\n|---|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| | [**Qtonz**](/use-cases/qtonz-mbit-music) uses Firebase to boost ad revenue by 4x and grow engagement by customizing the experience for different stages of the user journey. - **Fewer ads for new users** : They *reduced the number of ads* that a user sees on their first day using the app. They also changed the placement so that ads only appear after users complete a key in-app action. These changes made ads less intrusive. - **More frequent ads for engaged users** : For users with longer session lengths, Qtonz *increased the number of ads* shown from 2 to 3-4 per day. |\n\nImplementing the solution\n\nTo implement this solution, you can follow our step-by-step tutorial (find an\noverview of this tutorial later on this page). \n\nIn this multistep tutorial, you'll learn **how to use Firebase to test various\nfrequency caps for Google AdMob ads in your app** . It uses\n[interstitial ads](https://support.google.com/admob/answer/7311435)\nas the example test case, but you can extrapolate and use these same steps to\ntest frequency capping for\n[other ad formats](https://support.google.com/admob/answer/6128738).\n\nThis tutorial assumes that you already use AdMob in your app and that you'd\nlike to test whether changing the *frequency* of an interstitial ad unit will\nhave an impact on your app's revenue or other metrics. However, if you don't already\nuse AdMob in your app, that's ok! The steps in this tutorial can also help\nyou understand what ad frequency you should use in your app.\n| **Tip:** If there's a term that you're not familiar with, check out the [glossary](#glossary) at the bottom of this page.\n\nProducts and features used for this solution\n\n|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| Google AdMob \u003e [Google AdMob](/docs/admob) enables you to create ad units with various ad frequencies or refresh rates that will be served within your app. When you link AdMob with Firebase, AdMob sends ad revenue information to Firebase to improve ad strategy optimization. Google Analytics \u003e [Google Analytics](/docs/analytics) gives you insight into user engagement, retention, and monetization metrics like total revenue, AdMob revenue, purchase revenue, and much more. It also allows you to create user audiences and segments. | Firebase Remote Config \u003e [Firebase Remote Config](/docs/remote-config) enables you to dynamically change and customize the behavior and appearance of your app for desired user segments --- *all without publishing a new version of your \u003e app* . In this tutorial, you'll use Remote Config parameters to control which ad unit is shown to your users. Firebase A/B Testing \u003e [Firebase A/B Testing](/docs/ab-testing) provides the interface and infrastructure to run product and marketing experiments in your app. It takes care of distributing experiment variants to users, and then performs statistical analysis to determine if an experiment variant is outperforming the control group based on your selected key metric, such as revenue or user retention. |\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e\n\nSolution tutorial overview\n\n[Go\ndirectly to the step-by-step tutorial](/docs/tutorials/optimize-ad-frequency/step-1)\n\n1. [**Use AdMob to\n create new ad unit variants for testing**](/docs/tutorials/optimize-ad-frequency/step-1)\n\n 1. Create two new interstitial ad units in AdMob.\n\n 2. Set the *Frequency capping* of each ad unit to an impressions per user\n value that you want to test.\n\n 3. Implement the ad unit placements within your app's code.\n\n2. [**Set up an A/B test\n in the Firebase console**](/docs/tutorials/optimize-ad-frequency/step-2)\n\n 1. Define testing basics, targeting, and the goals that the test will run\n against.\n\n 2. Define test variants and set up the Remote Config parameter that\n will control which ad unit is shown to users in the test.\n\n3. [**Handle\n Remote Config parameter values in your app's code**](/docs/tutorials/optimize-ad-frequency/step-3)\n\n 1. Use the Remote Config parameter in your app.\n\n 2. Implement the logic for displaying the ad unit based on the parameter's\n value.\n\n4. [**Start the A/B test\n and review the test results in the Firebase console**](/docs/tutorials/optimize-ad-frequency/step-4)\n\n 1. After starting the test and allowing it to run for a few days or weeks,\n check the Firebase console for whether the A/B test has a winning\n variant based on the primary goal of the A/B test.\n\n 2. Review the impact on secondary metrics for each variant to ensure the\n variants didn't cause unintended negative impacts to those metrics.\n\n5. [**Decide whether to\n roll out the new ad unit with the updated ad frequency**](/docs/tutorials/optimize-ad-frequency/step-5)\n\n 1. If A/B Testing determines that the variant showing the new ad format\n is the winner, you can start showing the ad format to all users targeted\n in the experiment, all users of your app, or to a subset of your users.\n\n 2. If a clear winner isn't yet determined, you can either continue running\n the experiment to gather more data, or end the experiment if it's\n already been running for a long period with inconclusive results.\n\nGlossary\n\n\u003cbr /\u003e\n\nView a list of common terms for this solution\n\n\u003cbr /\u003e\n\n- **AdMob revenue** : AdMob network and open bidding revenue\n\n- **IAP revenue**: In app purchases revenue\n\n- **Total revenue**: Total revenue\n\n- **Retention**: Retention as a key metric in A/B tests is tracked as 1 day,\n 2-3 days, 4-7 days, 8-14 days, or 15+ days user retention\n\n- **Remote Config parameter**: The configurable parameter used to control\n which ad unit is show to users. In this guide, it will be an ad unit ID.\n\n- **Baseline configuration** : The as-is configuration in any particular A/B test\n --- also known as the control. The control usually uses the default value for\n the Remote Config parameter, but it can be configured to use a new control\n value if needed.\n\n- **Variant configurations** : The variant configurations are the alternative\n configurations with different Remote Config parameter values that we would\n like to test against the baseline configuration.\n\n\u003cbr /\u003e\n\n\u003cbr /\u003e"]]
