-p-500.jpg){kind=tracking}
It's a question that every app startup asks at some point in its early days.
"How are we going to make money?"
Monetization strategy is critically important. It's not just a question of revenue; it's a question that influences your entire business model, including market positioning, user acquisition, UX and long-term sustainability.
A well-thought-out monetization strategy aligns with your app's core functionality and user expectations, while a hastily chosen model can create friction and deter engagement. The stakes are high, and the choices are far from simple. From subscription to freemium, advertising or pay-to-download — among others — each model comes with its own set of challenges, opportunities and implications.
In this guide, we'll walk through a few of the most common application monetization models, allowing you to weigh the pros and cons effectively and chart the course for your app's financial success.
The subscription-based model entails charging users a recurring fee to access an app’s content or features, providing a stable revenue stream. This model is suitable for applications that offer unique content on a periodic basis, such as:
With platforms like Netflix and Patreon making subscription content mainstream, consumers have been eager to sign up. In 2021, the top 100 subscription based apps surpassed $18.5 billion in revenue, a 41% increase over the prior year.
On the downside, this model may cause users to:
The usage-based monetization model, also known as consumption-based pricing, charges customers based on their actual usage of a product or service. This flexibility allows customers to pay only for what they use and manage their spending accordingly.
This model is common in:
The main challenge with usage-based monetization lies in accurately tracking usage and billing customers proportionately. Customers may also be hesitant to pay for usage they don’t fully understand or don’t deem necessary.
The freemium model remains one of the most popular and widely implemented monetization strategies. It offers limited features for free, while additional premium features are available for a fee, encouraging users to upgrade. A prime example of a successful freemium app is Spotify, with 24% of users converting from the free version to paying subscribers.
However, the freemium model isn't without its drawbacks. One major challenge is striking the right balance between free and paid features; offer too much for free and users won't feel the need to upgrade, but offer too little and they might churn out. There's also the risk of cannibalizing your own revenue if premium features don't offer sufficient value over free options.
For sustained revenue, it’s advisable to make in-app purchases enticing and full-featured. Product teams should also regularly adjust pricing based on geography and user demographics to ensure optimal pricing. This requires constant market research and iterative testing, adding another layer of complexity to the freemium approach.
The one-time purchase model is straightforward but powerful. Users pay a single upfront fee to access the full suite of an application's features for an indefinite period. This model is commonly found in software suites like Adobe Photoshop and certain premium mobile apps.
The advantages of this model are clear: it provides immediate revenue and eliminates the need for continuous sales and marketing efforts to keep users subscribed. It also offers a sense of permanence and ownership that many users find appealing, fostering a higher level of initial commitment.
However, there are drawbacks to consider. First, this model can create a higher barrier to entry, as potential users may be hesitant to commit to an upfront payment without trialing the app first. Second, without a recurring revenue stream, the business will face the pressure of continually attracting new users to sustain income. This means making constant updates and improvements to remain competitive, but without a built-in revenue stream for these updates, the financial burden can be significant.
If you opt for a one-time purchase model, it's crucial to have a robust marketing strategy and a clear plan for adding value through updates or additional services. Given the absence of recurring revenue, focusing on customer lifetime value and maximizing initial sales becomes critical for long-term success.
Combining advertising with other monetization strategies can maximize revenue by targeting both paying and non-paying users. In-app advertising can take various forms, including:
Integrating advertising with an app monetization strategy allows app developers to enhance income, targeting both paying and non-paying users, and promoting pertinent apps to a defined audience.
While advertising may seem like an easy and straightforward way to monetize an app, it comes with considerable drawbacks. The most notable is the negative impact on user experience, as ads can be intrusive and disrupt the natural flow of an application. This can lead to decreased user engagement and higher churn rates. Furthermore, advertising often requires a large, active user base to generate significant revenue, making it unsuitable for niche or newly launched apps. Finally, the reliance on third-party ad networks can introduce privacy concerns and make revenue streams less predictable.
White labeling or licensing enables businesses to monetize their app’s technology or content by selling it to other businesses, thus creating additional revenue streams. This model allows businesses to use an app’s technology or content under their own brand, saving development time and resources.
An example of successful licensing is Waze, a community-driven navigation app that provides businesses with access to its data collection for location-based advertisements.
A downside is that white labeling often involves substantial customization to meet the licensee's specific needs, which can divert development resources from your core product. The revenue is usually fixed or limited by contract, offering less scalability compared to direct-to-consumer models. Lastly, relying too heavily on a few big clients for licensing can make your revenue stream vulnerable to contract terminations or renegotiations.
Data monetization refers to the process of leveraging user data to generate revenue, either through targeted advertising or selling the data to third parties. This model is particularly prevalent in applications that collect a wealth of user information, such as social media platforms, search engines and e-commerce apps.
For example, Facebook and Google heavily monetize user data by offering targeted advertising solutions. Apps in the fitness and health sector, for instance, might sell anonymized data to research institutions or insurance companies interested in health trends.
However, when implementing data monetization strategies, app developers need to comply with data privacy regulations such as GDPR in Europe or CCPA in California. Transparency with users about how their data is being used is crucial for maintaining trust and avoiding potential legal ramifications.
Building a startup is hard, so we created Archie to make things a little easier.
Archie leverages GPT-4 and our own secret sauce calibration to evaluate your startup idea and offer in-depth recommendations for product models, problem statements, user design and monetization mechanics, among a slew of other things that founders have to keep in mind.
Using AI and machine learning algorithms, Archie assesses a business concept and measures its potential, taking into account aspects such as the originality of the idea and the venture’s ability to receive backing. Based on its evaluation, Archie provides extensive suggestions to help you get your business idea off the ground.
Want to give it a try? Head over to Archie, and get started today.
