Imagine the following situation: you are trying to choose between two apps. They have more or less the same functions, but one of them is free, and the other one is paid. Which one would you download? We bet you would go for the free application. And that’s exactly what most of your users would do! In case your product is not absolutely unique and special, they are more likely to prefer a free version instead of yours. However, we guess, you are not developing apps only for fun — you also want to earn some money releasing them and go for mobile app monetization. But how to do this while keeping your application free to download? No worries, that’s possible, and we have prepared a detailed guide to help you. So just keep reading to discover how to gain profit with your free app.

You may also find it interesting – Calculate LTV

Advertising for mobile app monetization

Advertising is the most popular strategy among those companies which want to monetize their apps. Its main principle is very simple: your app remains free, but you equip it with some third-party ads. Therefore, you earn money from views, clicks, and so on. Here are some of the most efficient types of ads:

Video ads

Video content is considered to be extremely engaging, so adding video ads to your application is a great decision. Videos can either be shown at transition points (for instance, while the game level is loading) or be offered to watch for a reward. In the case of rewards, a user can get a bit of in-game virtual currency for watching a video, or something like this.

Remember to micro-segment your users using AI before showing to them video advertisements. In our past experience different segments of customers differently, interact with different video lengths. Otherwise, your users won’t watch them often enough.


Banners are ads placed at the top or bottom of your application’s layout. They are often shown all the time until a user stops using the app or closes the banners themselves, if possible. Keep in mind that the banners should be designed very carefully. They are small on their own, and even smaller on the smartphone’s screen. So they shouldn’t contain too much text — a user won’t pay a lot of attention to tiny letters. Here A/B testing using machine learning could be useful.

Interstitial Ads

Interstitial ads are usually more efficient than banners, as they cover the entire app’s layout. In most cases, users can skip such an ad only after it is shown for a certain amount of time. That’s why you should be very careful with interstitial ads and make sure that the content impossible to skip is catchy enough.

Playable ads

Playable ads can be especially useful in case you advertise a game or mobile casino. They work like this: users can instantly try playing the game (right in the ad!) and then decide if they want to download it or not.

Notification ads

These ads appear in the smartphone’s status bar, just like push notifications. Again, be careful and don’t overuse them. Otherwise, such ads will only irritate your users, and nothing more.

Native ads

Native advertising is becoming more and more popular, and that’s logical. Such ads don’t look intrusive — they are perceived as a natural part of the app’s content. They are usually marked as “Sponsored”, “Featured” or “Recommended”, and you can often see them, for instance, on Facebook and Instagram. This kind of advertising is more popular and effective than the traditional advertising strategies we described above, and statistical data proves this. Thus, users view native ads 53%[1] more frequently than the traditional ones. Native ads containing video, audio, or other rich media elements can increase conversion by up to 60%[1]. It also able to boost the brand lift by up to 82%[1]. We guess these facts are enough to assure you that native ads are a reliable way to go.

loyalty and marketing

By the way, machine learning for marketing can be a great help in case you choose advertising as your monetization strategy. Using a product recommendation engine, you can improve customer segmentation and, therefore, personalize your advertising. And if you do everything in the right way, your reward will be an increasing average revenue per user (ARPU).

In-App Purchases increases mobile app monetization

In-app purchases is another popular strategy — the app itself is free, but its certain features or products are paid. For example, if your app is a game, you can offer users extra lives, an ability to customize their characters, etc. Feel free to be creative.

And a few more words about artificial intelligence — it can significantly increase IAP (in-app purchases). Deploy the recommendation system, and your users will receive personalized offers that they are more likely to buy. For instance, if a player runs out of lives, a system offers to buy an extra one. Such an ad has higher chances to succeed at this particular moment than a customization offer. That’s why products or features recommendation in-app using AI is a much more reliable way to the revenue growth than random offers.

Another important thing to mention here is LTV prediction for user monetization. With a proper algorithm, you will be able to offer products and features in a much more efficient way. LTV is a customer lifetime value, and we have already written a nice article about it — Customer Lifetime Value Prediction.

Freemium Model

The word “freemium” is a combination of the words “free” and “premium”, and this fact perfectly reflects the meaning of this strategy. A freemium app is available in two modes. The first one is free, but only the basic features are available. In turn, the premium model is much more convenient and pleasant to use. Spotify is a great example here. Its free version offers only shuffle play, but the premium one is much more attractive. Apart from shuffle play, users enjoy an ability to listen to music offline, the absence of ads and interruptions, and so on. Spotify even offers several Premium modes — for example, there are packages For Family and For Students.

Mobile app Data Monetization

With this monetization strategy, you should be very careful — it implies selling information about your users’ behavior to analytics companies or diverse advertisers. It sounds very simple, but there are two things that you must always keep in mind when using data monetization. The first one is your users’ awareness of what you are doing. They should know that you use their data. Secondly, data privacy regulations are something you must never break. If you do this, you may face serious problems, while your app and your company, in general, may forever lose credibility.

However, there is one more extremely important thing to mention, and it applies to all the monetization strategies. Obviously, it is crucial to choose a strategy wisely, but it is also essential to predict the monetization future of your app. Predictive analytics and historical data gathered from your users will help you to do this.

But in any case, we have described several mobile app monetization strategies, so now you can decide which of them will perfectly suit your product. And, as always, if you still have any questions, you are welcome to get in touch with us. Would you like to ask anything else about personalization using AI? Or about churn prediction for increasing retention? We are always ready to answer these and any other questions, just ping us a message in case you are interested in learning more.

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[1] Steve Olenski. 6 Types Of Native Advertising And How Each Can Benefit Your Business. Nov 12, 2015. URL: Accessed Jun 25, 2019.

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