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SKAdNetwork conversion value mapping data shows gaps between gaming and non-gaming apps

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There’s little question that Apple’s iOS 14+ has launched essential measures to safeguard person privateness. Nevertheless it has additionally created important challenges for entrepreneurs who’ve needed to adapt to a very new method of measuring their campaigns.


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Some of the sophisticated areas entails SKAdNetwork’s conversion worth and timer extension mechanisms. It is a drawback, since post-install information is what issues most within the freemium-driven app ecosystem.

Earlier than iOS 14, entrepreneurs may measure in-depth and at size to find out person/marketing campaign worth. However in Apple’s SKAdNetwork, information is much much less in-depth and at size…You get 64 mixtures from 6 bits to map post-install exercise and some days at better of exercise information. In different phrases, conversion values are SKAN’s various to [limited] LTV.

With restricted choices, it’s crucial that advertisers benefit from what is feasible. To be clear, what is feasible may be lots if accomplished proper. However what does ‘proper’ seem like? How ought to entrepreneurs map their conversion worth schemes?

To reply this query, we checked out information from our Conversion Studio and analyzed the configurations of 900+ apps to assist advertisers study the bits and bytes in regards to the bits and bytes.

The information reveals that for a lot of entrepreneurs, conversion values are robust to grasp. Whereas some have discovered to squeeze the information lemon (unsurprisingly, primarily from the gaming crowd), others will not be even near using the total potential of this new mechanism.

On this article, we’ll present you ways totally different verticals are:

  1. Mapping conversion worth schemas
  2. Defining the exercise window timer
  3. Utilizing the 64 mixture capability, or not

For a fast recap on conversion values, watch this video beneath:

For extra SKAN Insights, go to the Inside SKAN sequence.

What are the sorts of conversion mappings?

Earlier than we present you the information, right here’s a high-level clarification of the several types of fashions we’ll current within the charts (for extra detailed information click on right here).

Income: Income generated by the person in the course of the exercise window earlier than the one-time postback is shipped. It may be recorded utilizing a single occasion, or related to income by stream (IAP, IAA, subscription income) utilizing choose in-app occasions.

In-App Occasions: Put up-install in-app habits akin to tutorial completions, logins, purchases, shares, and stage completions. Entrepreneurs can measure the variety of distinctive customers performing an occasion, the variety of occasions an occasion was carried out, or each.

Funnel: Measures the incidence of in-app occasions based mostly on an inventory of sequential occasions in a funnel. A person performing any occasion within the funnel is considered having carried out all of the occasions previous that occasion. That is essentially the most environment friendly option to measure sequential occasions, utilizing fewer values for a similar quantity of in-app occasions measured.

Income and in-app occasions are essentially the most configured schemes

A sub-division appears like this:

Key findings

1. Gaming apps are pushed by income in comparison with events-driven non-gaming apps.

The vast majority of gaming apps are pushed by income, with 84% of gaming apps using income configurations. In distinction, 85% of non-gaming apps measure in-app occasions.

Why? Gaming apps have a decrease time to first buy – significantly among the many extremely fashionable informal video games – in comparison with non-gaming apps. The latter depend on in-app occasions to be key indicators for purchases that happen past the exercise window.

2. Nearly 40% of Procuring apps use a mixture of in-app occasions and income.

As talked about above, in-app occasions like registrations and e-mail signups may be key LTV indicators for purchasing apps.

A minimum of 77% of purchasing app configurations contain counting occasions, whereas 39% use a mixture of occasions and income. The first aim for purchasing apps is to drive the primary buy as shortly as doable whereas measuring key occasions within the course of.

3. 92% of Well being & Health apps measure in-app occasions.

Most Well being & Health apps depend on subscription fashions, requiring apps to give attention to constructing loyalty and supply constant worth to their customers.

With free trials additionally being widespread, customers take for much longer to make a purchase order, so it’s crucial that Well being & Health advertisers give attention to measuring early indicators of worth via in-app occasions – akin to registrations, exercises accomplished, and shares.

4. 23% of Social On line casino apps configured funnel occasions and income.

As one of many highest-grossing app verticals with a superb potential to determine early patterns of high-value behavioral indicators, greater than a fifth of social on line casino apps measure the mix of funnel occasions and income.

5. Hardcore video games are laser-focused on income.

Hardcore video games closely depend on in-app purchases and never in-app promoting, which is why 93% of those video games make the most of income configurations.

Exercise window correlates with length of the funnel

Key findings

1. Because the default setting, 24-hour exercise home windows are the most typical.

The vast majority of apps throughout all verticals are using the default 24-hour exercise home windows to gather information, however we anticipate this to vary as SKAdNetwork utilization matures.

Past the truth that 24h-hour window is the default, it’s essential to keep in mind that information can solely be collected as soon as, so there may be an intentional tradeoff.

Shorter exercise home windows allow sooner information assortment, however go away you with restricted info. Alternatively, longer home windows present richer information, however entry to it is going to be delayed.

Additionally, the timer can’t be prolonged for all customers – so even when it’s prolonged, it’s going to solely apply to a portion of customers. The one option to lengthen the timer is by updating the conversion worth, which may solely occur if the app is opened.

So, even in the event you set the timer to 72H, if the person didn’t open the app for 24H, the conversion worth is locked. For instance, if a person opens the app on day 0, day 1, and day 3, the exercise of day 3 received’t be recorded – as a result of the app wasn’t opened on day 2.

Lastly, don’t overlook that some main advert networks nonetheless don’t help optimization past 24 hours, affecting entrepreneurs’ timer selections.

2. Non-gaming verticals with longer buy funnels use the 72-hour window.

Finance apps usually have longer buy cycles, which is why 40% of them are utilizing the utmost 72-hour window.

Equally, apps in different non-gaming classes use for much longer buy cycles than Gaming apps whose buy journeys are considerably shorter.

3. 86% of Social On line casino video games have 24-hour home windows.

On the alternative facet of Well being & Health apps, we’ve got Social On line casino apps whose final aim is to get gamers engaged, hooked, and spending as shortly as doable.

Gaming apps make the most of extra of the conversion worth capability

Key findings

1. Not like non-gaming apps, extra Gaming apps make the most of conversion worth capability.

Gaming app entrepreneurs are well-known for his or her stage of data-driven experience and skill to quickly react to vary.

The sheer competitiveness of this vertical dictates that, with 63% already using virtually all choices, in comparison with solely about 40% of non-gaming apps (Meals & Drink apps are an exception with at least 80% utilizing all choices).

2. Hardcore and Midcore video games have considerably larger conversion worth capability.

74% of Hardcore and 76% of Midcore video games make the most of 60-64 conversion values resulting from their extra complicated funnels.

Customers have much more actions and experiences to take at their disposal. In addition they each make the most of longer exercise home windows, which give extra time to file extra occasions.

Easy methods to squeeze the conversion worth lemon 

Whereas it’s key to study from trade finest practices, your success with conversion targets is determined by the way you tailor your technique to your distinctive app.

Listed here are a number of methods to remember:

Having 64 choices is a limiting issue, however nonetheless provides loads of worth if bits are correctly allotted and utilized. Benefit from ranges and mixtures and give attention to the post-install actions that matter most. Cut up, swap, and mix your conversion mapping configurations till you discover the right combination.

Trade finest practices are place to begin. If you happen to don’t have plenty of information to work with, the statistics above are a superb start line.

There’s no “proper” reply, solely what’s finest for you. The way you implement, measure, and optimize your conversion values is an ongoing course of. Check, take a look at, and take a look at once more till you discover the precise mapping (having a UI actually makes it simpler).

Measure smarter with funnels. We’re nonetheless within the early days of SKAdNetwork. Subsequently, most advertisers are under-utilizing funnel configurations, which could be a extra environment friendly option to allocate your bits.

As a substitute of dedicating 3 bits to measure three separate occasions, a funnel configuration can measure sequential habits utilizing just one bit.

Predictive modeling isn’t a luxurious anymore, it’s a should. The postback timer limits the quantity of knowledge you may acquire to foretell LTV on your customers. Leverage predictive modeling to determine the best metrics and behaviors that may finest determine your most worthwhile customers.

You may make use of a predictive profit rating that makes use of all 6 bits to speak any rating, a particular mixture (which can very probably differ from one advertiser to a different) will point out a priceless person cluster.

Do not forget that whereas the profit rating is related to a particular person, as soon as the data comes again from SKAN it’s introduced in an mixture method for a person cluster.