If you already use our Remote Config feature and have paywalls or onboarding flows configured, you can launch the experiment right from existing configurations. Learn more here.
Writing down your idea beforehand helps to avoid several biases (for instance, confirmation bias) during experiment analyses. At the start, we recommend you focus on the following sections:
Experiment name, as the title of your experiment, helps you understand your main idea at a glance.
Context key, as an identification of your application context on the SDK side, helps you target experiments for specific parts of your user journey. Examples of app contexts you may experiment with:
main_paywall: to validate ideas for the content different user segments see on your main paywall.
main_paywall_products: to run experiments only for the products section.
onboarding: to check how changes related to the entire user onboarding journey affect your revenue.
onboarding_step_2: to validate changes for some specific steps of your onboarding flow.
[your_key]: to run experiments for any other part of your user’s monetization experience.
Hypothesis description, as a short idea representation, helps you stay focused on what you intended to validate initially.
After filling in the main information, you can select the Primary Metric for the experiment. Setting primary metrics in this step helps you get information about statistical significance and recommended sample size during the experiment analysis phase. Qonversion metrics you can choose from:
To enable Qonversion to run and calculate A/B testing results, you need to have Qonversion SDK installed in your app.
By using Qonversion Experiments, you can test any part of your paywall (and even more). Moreover, Experiments and Remote Config share the same API & architectural concepts, so you do not need to implement complex logic to use both.
Qonversion Experiments work with the same in-app values as Remote Config. The core of these attributes is a plain JSON file consisting of key-value data. We support the following data types:
String.
Use this option to validate pricing, communication, or visual hypothesis.
Examples: native.subs.full.v4.w.8.99.trial.7d, Unlock Fast and Secure Browsing, #3076FF, etc.
Number.
Use this option, for example, to show only a subset of your onboarding screens.
Examples: 2, 5, 23, etc.
Boolean.
Use this option to turn some features on or off.
Examples: true, false
Json.
Use this option to validate advanced changes in your app’s behavior.
Qonversion Remote Configs and Experiments share single methods to get configurations. You can distinguish the source of the result received by looking at the source field. Learn more about fields available.
To receive the configuration with the Context key set, call the following Qonversion remoteConfig method.
Qonversion.shared().remoteConfig(contextKey: "my_context_key") { remoteConfig, error in // Use remoteConfig here}
In case you’re using configurations with empty Context key, call the same method with no arguments added:
Qonversion.shared().remoteConfig { remoteConfig, error in // Use remoteConfig here}
If necessary, you can also request a list of remote configs for all the context keys, including the empty one.
Qonversion.shared().remoteConfigList { remoteConfigList, error in // Use remoteConfigList here}
If you need remote configs for a specific set of context keys, just use the following method.
Qonversion.shared().remoteConfigList( contextKeys: ["my_context_key", "another_context_key"], includeEmptyContextKey: true // to include remote config without context key) { remoteConfigList, error in // Use remoteConfigList here}
We highly recommend testing if your app works properly with the changes you want to roll out to your users. You can do so by following the following steps:
Copy the ID for your experiment and the variant you want to test.
Pass the values to Qonversion SDK by using the attachUserToExperiment method
Do not forget to remove the usage of the attachUserToExperiment method before your app release. Otherwise, all your users may be exposed to only one experiment group.
Use this option to run new behavior only in selected countries.
Store
Use this option to target only a specific store (Apple App Store or Google Play).
User’s active subscription
Use this option to target only users with/without any active subscriptions or having a specific one.
Purchased product
Use this option to target users based on their purchase history. You can select specific products or use (any) to match users who made at least one purchase, or (none) for users with no purchase history. Unlike “Active subscription”, this filter checks all purchases regardless of their current status (active, expired, or cancelled).
Last purchase date
Use this option to target users based on when they made their most recent purchase. For example, you can target users whose last purchase was more than 60 days ago to identify churned users.
User properties
Use this option to target users with specific custom user properties set via the SDK. Useful for behavior-based or attribute-based experiments.
We do not recommend starting your experiments with 100% of all eligible users. It might be enough to start with 10% to ensure everything works fine and gradually increase your traffic level later.
Once you have configured your experiment, segmentation, and traffic level, it’s time to start your experiment and proceed to the section with real-time analytics.What’s Next
