Tackling the challenge of fragmented data in subscription app marketing
The subscription-based business model has enjoyed massive growth in recent years, reshaping the way app developers and marketers approach user acquisition and retention. According to our State of App Marketing for Subscription Apps, global consumer spending soared 35% in 2023, clearly indicating a shift in consumer preferences towards services that offer ongoing value.
However, the success of the subscription model brings a unique set of challenges, particularly when it comes to measuring the various stages in the subscription funnel, organizing the data, and optimizing campaigns. Developers and marketers must keep up with a complex landscape, making it challenging to stitch together a complete picture of the user journey.
The impact of such data challenges often degrades data quality and accuracy, which in turn leads to sub-optimized decisions and reduced growth over time. Additionally, the effort to maintain data accuracy can become tedious leading to the focus of your resources on non-core work.
In this blog post, we’ll examine the data challenges, explain their complexities, and suggest several alternatives to tackling them.
Data fragmentation: different data points, different platforms
When you want to make solid decisions, you need good data to support them. Good subscription data covers three pillars:
- Complete: data that offers a full picture of the user lifecycle following a sequence of events that users go through.
- Accurate: data from the most granular events and their revenue so that you can calculate ROI and optimize your business.
- Actionable: Having the right tools so that you can organize the data to make decisions effectively.
The differences between the subscription funnel stages, Android and iOS, the various plans you propose to the user, or other variables you have in the process are complex to organize meaningfully. The following section highlights these differences.
1. Data collection
The first part of the problem is collecting the data to measure the complete subscription lifecycle. It consists of three parts:
- Collecting real-time in-app events: To collect the events in real-time, the app developer must implement the app store framework that deals with purchases. For example, if a trial has been converted, you need to record the event and report on it. And if that’s not enough, there are different frameworks to apply for iOS and Android.
- Events outside the app: the problem intensifies because some events take place outside of the app. And without these events, the subscription lifecycle data is incomplete. For example, an auto-renew event that does not mandate a user to open the app. In this case, Apple and Google have different mechanisms to share the data with the app: Real-time Developer Notifications (RTDN) from Google Play and App Store Server Notifications in iOS.
- Validating the store receipt: the mobile app industry has always suffered from fraud and hence Apple and Google provide tools to validate the transaction. This adds another layer of complexity that has two implications:
- Transactions need to be validated in real-time to authorize users to access gated content behind a subscription.
- Valid transactions need to be properly reported for measurement purposes (how much revenue is generated).
2. From transaction data to meaningful in-app event
A subscription funnel can be quite complex. Let’s explore an example of such a user flow:
- The user subscribes to a fitness app for a seven-day free trial
- Converts to a paying user after the trial
- Pauses the subscription after two months
- Resumes the subscription after one month
Clearly, to have a complete view of the journey, you need full visibility across all touchpoints. For example, when you have a resume event, you need to know that a pause event occurred before and allocate the relative part of the revenue before and after the temporary pause. You might also want to know what product was sold, the special offer that had been provided, and the price, among other details that require capturing additional granularity.
3. Net revenue
Netting the revenue is a critical problem to solve for subscription apps because it’s how data is shown in stores and ultimately it’s the money that you see in the bank. In addition, when analyzing a campaign’s performance, it can be the difference between a profitable campaign when looking at gross revenue and a non-profitable campaign when looking at net revenue.
To net the revenue, you should deduct the store commissions and taxes from the receipt. In Google, subscription apps pay a 15% commission. But in Apple, you’re paying 30% in the first year and 15% in the second year. Apple’s approach is to encourage app developers to retain and engage users by focusing on experience and the longer term to generate more revenue. Lastly, both Google and Apple have a special program for SMBs that allows 15% commissions for up to $1M in revenue on a yearly basis.
Calculating taxes is even harder because it is determined by the country in which the user is buying your service. And in some countries, the taxes are excluded while in others it’s included.
How to solve these challenges?
Option 1: In-house development
If you want to do things on your own, you need to to develop the SDK integration and the store APIs while processing the data meaningfully and serving it in your internal system and/or in your Analytics partner of choice. This comes with several tradeoffs.
Pros:
- The most flexible option because you own everything and you set your own logic, data granularity, format, and so on.
- Seamlessly integrate with your existing infrastructure. The solution can be built to work hand-in-hand with your CRM, data warehouses, and other internal tools.
Cons:
- De-focuses you from your business optimization. Instead, you’re focused on building a subscription measurement product which is not your goal but rather only a means.
- High cost. Developing and maintaining store integrations is resource-heavy. You’ll have to pay for the cloud cost and for engineers who maintain these APIs as they frequently change.
- Data accuracy might become an issue over time, as it requires expertise. And typically you don’t have the time and resources it necessitates. You need to closely monitor the frequent store API changes, understand their implications which are anything but trivial, and ensure your tools are updated accordingly.
Option 2: 3rd party subscription management tools
Tools that provide app developers with cross-platform support, subscription analytics, real-time event tracking, integrations with app stores, and more.
Pros:
- Allows end-to-end subscription lifecycle management
- Centralizes subscription data
- Saves time and resources. You don’t need to do everything yourself because the tool you’re buying can do it for you.
Cons:
- On the analytics side, it focuses mainly on revenue. Without cost, you cannot optimize for ROAS or ROI.
- Another SDK dependency for the app creates a risk every time the vendor is making changes.
- Expensive. These tools are not cheap given that they have plenty of functionality, some of which might not be relevant to your business.
Option 3: Mobile Measurement Partner (MMP)
Some MMPs allow app developers to measure their subscription lifecycle focusing more on the data, reporting, and analytics aspects.
Pros:
- Lower SDK footprint. Since you already have the MMP SDK, there is no need for an additional 3rd party SDK to report on subscription data.
- All the data in one place. Whether it’s ROAS or LTV, your MMP provides you with all the tools you need to make decisions instead of matching multiple data points before you start taking action.
- Lower costs. If you buy a subscription management or do it yourself, be prepared to spend large amounts of your budget.
Cons:
- Does not allow you to change the paywall configuration without deploying a new app version.
- Can be less flexible when it comes to your specific needs (although an MMP offers several customization options).
The bottom line
Subscription measurement is a core part of making subscription-based apps work. To make good optimization decisions, you need comprehensive tools with complete, accurate, and actionable data.
Solving this problem is complex because it requires collecting the data from the app, the stores, and then validating, de-duplicating, maintaining the transaction state,and ultimately netting the revenue.
There are several approaches to solving this problem. It’s obviously easy to focus on in-house development when you’re a young company, but knowing these challenges upfront can help taking a different approach and leaving the data plumbing and tooling party to an external vendor so that you can focus on your own business.
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