<p-l>We are talking about building analytics on the product side and taking the first launch of the product by the user as a starting point.<p-l>

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<p-l>Let us dive deeper and see what the taxonomy of the onboarding events should look like to conduct reliable tests. Take this Guideline and adjust it based on your product context. As a member of the Applica team, I am happy to provide these insights and conduct a personal audit if needed.<p-l>

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<p-l>Now, we are talking business: methodology and events taxonomy, onboarding monetization, and non-monetization experiments.<p-l>

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<article-h2>Onboarding monetization experiments<article-h2>

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<article-h3>Main Metrics and Concepts<article-h3>

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<p-l>Average Revenue Per User (ARPU) is one of the most important metrics for every product, and Onboarding is the epic where we can impact a product’s ARPU hugely by conducting monetization experiments. Most of them take place on the so-called payment screen, where the user is offered to buy a subscription for the first time.<p-l>

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<p-l>Onboarding ARPU is created on the payment screen, but really consists of 3 other metrics:<p-l>

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<step-s>1<step-s><p-l-b>Conversion to payment screen — the number of users who opened the app for the first time and saw the payment in the onboarding.<p-l-b>

<step-s>2<step-s><p-l-b>Conversion to purchase — the number of users who reached the payment screen and actually purchased the subscription.<p-l-b>

<step-s>3<step-s><p-l-b>The average revenue per paying user (ARPPU) — what is the average price of a purchase?<p-l-b>

<p-l>What is more, if the monetization model of the product includes a trial period offer of any kind, these two factors affect the APRU:<p-l>

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<step-s>1<step-s><p-l-b>Share of the trial activations in total purchases (if applicable);<p-l-b>

<step-s>2<step-s><p-l-b>Conversion from the trial period to the actual purchase (also called trial to purchase, or T2P).<p-l-b>

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<article-h3>The Analytics You Require<article-h3>

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<p-l>There is a fairly classic taxonomy of events used to measure onboarding monetization experiments:<p-l>

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<step-s>1<step-s><p-l-b>first_session (as a separate event or as an event property of the start_session event) — an event that is sent when the user launches the app for the first time. It is usually used as the first event that initializes the user in analytics. It is also often equated to application installation due to the fact that there are no normal data connectors between the Apple Store and other analytics environments.<p-l-b>

<step-s>2<step-s><p-l-b>payment_screen_open — an event that is sent when the user has reached the payment screen in the onboarding flow. It can be reused for the analytics on non-onboarding payments, but additional event properties will be required.<p-l-b>

<step-s>3<step-s><p-l-b>payment_screen_click — an event that is sent when the user interacted with the screen in some way. Actions are specified as event properties, but the purchase event should be implemented separately.<p-l-b>

<step-s>4<step-s><p-l-b>purchase — an event that should be used for all purchases on all payment screens in the app. Usually, this event has many properties:<p-l-b>

• origin — on which screen purchase was made;
• status — whether the purchase was successful;
• product — what product the user bought;
• price — what was the price of the product;
• is_trial — whether this product offers a trial period;
• trial_length — what is the length of the trial;
• Other properties such as show_day (on what day of the user’s existence in the app the purchase was made), show_count, etc.

<step-s>5<step-s><p-l-b>ab_test_name — user property that indicates the cohort the user belongs to. It enables you to compare average metrics such as ARPU and I2P (install to purchase) of different test cohorts.<p-l-b>

<p-l>The task is to calculate the amount of revenue per installation in this cohort (ARPU), the number of those who saw the ad and decided to buy, and define the general structure of purchases. The described events should be enough to cover these needs.<p-l>

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<article-h3>Onboarding Monetization Test Types<article-h3>

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<p-l>Onboarding monetization tests can be divided into two main types of experiments:<p-l>

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<step-s>1<step-s><p-l-b>Optimizing the APRU by changing the layout (design) of the payment screen;<p-l-b>

<step-s>2<step-s><p-l-b>Optimizing the APRU by changing the products (subscription packages). This includes experimenting with pricing, and subscription and trial periods.<p-l-b>

<p-l>It is vital to track all of the metrics described above for both types. However, keep in mind that the layout tests focus on the conversion to purchase and APRU, and pricing (products) tests focus on the structure of the purchases and ARPU.<p-l>

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<article-h2>Non-Monetization Onboarding Experiments<article-h2>

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<p-l>Not only Onboarding allows you to optimize the APRU, it also drives other important metrics. We have prepared a list of metrics that are worth conducting non-monetization onboarding experiments on:<p-l>

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<step-s>1<step-s><p-l-b>Conversion to onboarding finish — the number of users who launched the app for the first time, and completed the onboarding. Onboarding completion is crucial because it is the end of the onboarding funnel. The better the onboarding is, the more it will activate the users to complete it and start getting the product value.<p-l-b>

<step-s>2<step-s><p-l-b>Conversion into a permit for notifications — the number of users who allowed notifications. Local and push notifications are powerful drivers of the app’s retention. Therefore, optimizing for the said share of users is a must. This metric is especially important for IOS since, on Android, notifications are allowed by default.<p-l-b>

<step-s>3<step-s><p-l-b>Conversion into sign-up — the number of users who registered and/or allowed to include them in the mailing list. Registering users does not only improve their UX in the long run, but it also affects their retention. Products that engage in email marketing significantly drive retention and ARPU, and additionally optimize for users to allow emails to be sent to them.<p-l-b>

<step-s>4<step-s><p-l-b>Conversion into product features activation (applicable only if product features use the user’s answers gathered during onboarding) — the number of users who performed certain actions during the onboarding, which led to their activation in certain product features. For example, for your app to remind your user of their birthday, the user needs to answer the birthday question in the onboarding first.<p-l-b>

<p-l>Thus, by following this guideline’s tips, you should be able to get solid results. If you are looking for a more personalized approach, please contact the Applica team.<p-l>

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