How apps across APAC are engineering maximum revenue from every ad impression

In today’s digital landscape, the mobile first revolution is nowhere more evident than in Asia-Pacific (APAC). According to Statista, mobile phones accounted for 68.8% of all web traffic in Asia in March 2024, while the GSMA predicts that smartphone adoption in APAC will reach 94% by 2030. This unprecedented mobile connectivity has transformed how people in the region interact with digital services, work, communicate, and consume content. For businesses and developers, the APAC market represents an extraordinary opportunity, with nearly ubiquitous smartphone usage creating a vast, highly engaged digital ecosystem.

In such a dynamic and mobile-savvy region, having an app with a strong user pool can be incredibly lucrative, provided you have the right monetisation strategy for your business.

The unique challenge of app monetisation in APAC

Since the pandemic, APAC’s mobile app market has seen explosive growth fuelled by increasing smartphone adoption, the increasing sophistication and diversity of homegrown apps, and acceleration of digital transformation across the region. And with much of this development happening in recent years, app publishers can benefit from a greater understanding of the benefits and challenges of monetising their apps via either advertising or subscriptions, each approach leading to different levels of efficiency and economics for advertisers and publishers.

Though subscription-based models can fare well within certain categories like SVOD, a recent report from RevenueCat showed that having ad monetisation helps with a more stable revenue stream, compared to having a subscription model alone. For many app publishers with an established user base, monetisation through advertising can offer greater revenue scalability, if they can generate sufficient traffic and demand sources.

Take comico, for example. With 23 million downloads and counting in Japan since its 2013 launch, the popular manga app had a robust user base. However, as ads were the company's primary revenue stream, operating in a market dominated by only a few global partners presented challenges. To address these limitations and encourage greater competition for its ad inventory, comico recognised the importance of integrating an additional demand source.

Among the many available options for monetisation, comico turned to ad tech company Moloco, drawn by its machine learning-powered SDK, its direct connections to a global network of advertisers over 190 countries, and its ability to reach 6.7 billion devices.

comico wanted to evaluate how well Moloco's SDK would integrate with its app and drive significant traffic, ultimately boosting revenue. To assess this, the app ran A/B testing with 50% of traffic routed through Moloco’s SDK and the remainder forming a control group. By assessing the target value of each impression using machine learning (ML) algorithms, Moloco was able to draw in high-quality advertisers who recognised the real value of each placement within the comico app and were willing to pay a premium for them. Not only did this widen comico’s pool of advertisers, but it increased competition for its inventory, resulting in higher price of each ad placement and a meaningful increase in ad revenue.

The results: a 24% increase in average revenue per daily active user (ARPDAU), with the app clocking in significant growth across Android and iOS. comico rapidly transitioned 100% of its traffic to Moloco SDK.

In-app bidding SDKs are gaining ground

In their potential for profitability and precision, in-app bidding SDKs are becoming increasingly popular among publishers as performance marketing becomes more of an imperative. Allowing all buyers to dynamically bid at the same time — with spend optimised based on performance rather than at the floor price set by publishers in the more traditional waterfall model — helps publishers secure incremental returns by driving competition for their inventory.

Besides improving performance, using machine learning to automate processes such as targeting and bidding results in a more streamlined and significantly more efficient management. Contrasting this to the waterfall model, Nopparat Yokubon, country lead for AUNZ and SEA at Moloco explained, “With the waterfall approach, publishers set the value of each impression per ad network, giving them control over pricing. This process demands a lot of manual work. Publishers need to optimise fill rates and latency at each price point, set up region-specific configurations, adjust for user data availability, and adapt to seasonal and environmental factors.” She continued, “In almost all cases, SDK waterfall publishers who transitioned to SDK bidding were able to increase ARPDAU. This was true even without raising media costs or impressions, primarily due to reduced latency and enhanced efficiency.”

This is exemplified by the experience of game developer Guru Game, who had already successfully engaged with Moloco to deliver high fill rates and strong eCPMs through its waterfall SDK. Seeking to further optimise its monetisation strategy, the developer turned to Moloco's in-app bidding SDK to diversify revenue streams in a category heavily dependent on advertising. While the initial waterfall SDK was delivering strong eCPMs, the process required significant time and resources to regularly manage and optimise the value of a hundred ad listings. “We were seeing good performance similar to our experience with Moloco’s waterfall SDK but were spending a fraction of the time managing the optimisation," said Hao Li, head of monetisation at Guru Game. He continued, “With the waterfall SDK, Guru Game needed to regularly manage and optimise the value of a hundred listings. The inefficiencies came at the cost of bandwidth resources and mindshare — as the team regularly worried if everything was functioning correctly.”

Switching to Moloco’s in-app bidding SDK significantly improved efficiency, saving the team valuable time in managing optimisation. Within a month, Guru Game also saw ARPDAU increase by up to 5%, enhancing overall monetisation. This convinced the developer, once again, to transition 100% of its apps to the Moloco in-app SDK.

How machine learning is powering the democratisation of ad inventory

On a broader scale, transitioning to in-app bidding is helping to democratise the mobile advertising industry. Dynamic machine learning models that process vast amounts of data can swiftly and accurately determine the best path for an impression, the optimal bid amount, and the ideal creative for user engagement while taking market nuances and user behaviour into account. This doesn’t just create a better experience for marketers, but publishers and their users too — especially in a region as culturally and linguistically diverse as APAC.

With decision making driven by real time data, rather than a manually set up waterfall bidding, marketers can see the reach, engagement, and the true value of in-app ads on the open internet. And with 5.8 million bid requests processed on Moloco per second, the machine learning model is being continuously trained and improved on, meaning that its predictions are getting more precise every day.

For Moloco, machine learning is powering a better future for the world of app advertising, and that’s reflected in the fact that its SDK comes at no extra cost to app marketers. Yokubon said, “The in-app bidding SDK was developed by Moloco to facilitate a more efficient ad transaction between publishers and marketers, which creates a direct path between the two. By bypassing intermediaries, the Moloco SDK is a new supply path with material benefits for marketers which eventually benefits publishers' revenue. Moloco SDK is not a revenue-generating business line for the company, and we will not have additional fees that are passed to marketers or publishers.”

She concluded, “Advertisers are increasingly prioritising performance-driven campaigns. I have seen this growing preference for in-app bidding and increased competition amongst advertisers significantly boost revenue for publishers. Moreover, buying traffic through in-app bidding provides partners like Moloco with valuable signals, such as more accurate win/loss notification signals which enhance the optimisation of our ML models to predict better auction prices and eventually improve advertisers’ performance.”

To learn more about how to integrate Moloco’s SDK into your app, please visit the Moloco website.