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The Need for Speed: How Video Load Time Affects Ad Delivery

Shlomi Gian

Ask any mobile app developer, and they'll tell you that one of the greatest challenges in monetizing their apps through video ads isn't finding the right demand or knowing when to run the videos; it's figuring out how to present video ads without slowing down their apps.
 
I'm sure every developer at some point has done a Google search for something like, "Which ad networks are optimized for mobile apps?" or "Which mobile ad network is the fastest?"
 
If the primary revenue you get from your app is ad generated, speed is hardly inconsequential.
 

The Developer Challenge

 
One company explained their ad situation like this: After a user completes a level, the user either goes into their store and browses around for a few minutes or goes to the next level within a few seconds. The developer's goal is to show a video ad right before the next level starts, but they've found themselves in a pickle. Most developers will cache their videos a few minutes before showing them, and the expiration is around 15 minutes. If the developer starts the video download as soon as the user finishes the current level, and that user then browses the store for a few minutes, the ad could expire before it can be shown, i.e., right before the next level.
 
On the flipside, if the developer starts the video download shortly after the user finishes the current level, and that user skips the store to go immediately to the next level, then the video has not downloaded yet and cannot be shown to the user before the next level. In this case, it would be ideal for the video to be delivered consistently within a set amount of time. But since ad retrieving timeout is around 300-400 milliseconds, even when you cache the video, slow ad retrieval leads directly to missing revenue.
 
Net net, while video pre-caching is a valid technique, it comes with a cost, and often times expired content would still result in real-time video downloads that usually are not fast enough.
 

Compounding the Challenge: Painful Disconnects

 
Connection drops are another issue that affect video ads. Disconnects happen all the time, especially when users are on the move, such as when they're commuting or walking around a busy city and their connections must transfer to a different network type. If a disconnect happens during an API call to an ad network or while downloading a large video asset, then that ad will fail to load.

When disconnects happen, the end user typically doesn't realize that the fault lies with the networks. Instead, they usually assign blame to the developer and the app itself. Many users will get so frustrated with a dropped connection that they won't even put in the brief time it takes to reload an app.
 
Some networks are faster and more reliable than others. Verizon and T-Mobile top the US for speed, and lag slightly behind AT&T in disconnects. The problem of disconnects is particularly acute in developing countries that don't have reliable cellular and WiFi networks. But it can infest developed countries as well. According to our benchmarks from February of this year, apps users in Russia, Indonesia, Germany and Brazil all suffer from more than 10% disconnects on average, with disconnect rates as high as 30 percent on 2G networks.
 

Examples of Various Ad Download Times

 
The charts below show ads within a popular news app. The top chart shows video ads delivered by SuperSonic and the bottom chart shows those delivered by Vungle. The x axis shows the amount of time a video took to download in milliseconds; the y axis shows the percentage of the total transfers that finished within that bucket of milliseconds. What we can see overall is that ads aren't delivered within a consistent amount of time; they're usually delivered anywhere from half a second to two seconds.





 
What this says is that if you use a mediation ad network, you should expect your ads to load anywhere from less than one second up to four seconds or longer. That doesn't help you to engineer your app if it has time constraints like the example above.

So what do you do? Well, if you choose to just use one ad network, you should be able to engineer your app/game to that specific ad network based on how long that specific network loads ads. Or, you could continue to use an ad mediator with the understanding that some percent of your users will not see the ad due to it loading too fast or too slow.
 
Bottom line is, attention shifts when something takes longer to load, and time is money. So keep this in mind with your in-app video ads.

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The Need for Speed: How Video Load Time Affects Ad Delivery

Shlomi Gian

Ask any mobile app developer, and they'll tell you that one of the greatest challenges in monetizing their apps through video ads isn't finding the right demand or knowing when to run the videos; it's figuring out how to present video ads without slowing down their apps.
 
I'm sure every developer at some point has done a Google search for something like, "Which ad networks are optimized for mobile apps?" or "Which mobile ad network is the fastest?"
 
If the primary revenue you get from your app is ad generated, speed is hardly inconsequential.
 

The Developer Challenge

 
One company explained their ad situation like this: After a user completes a level, the user either goes into their store and browses around for a few minutes or goes to the next level within a few seconds. The developer's goal is to show a video ad right before the next level starts, but they've found themselves in a pickle. Most developers will cache their videos a few minutes before showing them, and the expiration is around 15 minutes. If the developer starts the video download as soon as the user finishes the current level, and that user then browses the store for a few minutes, the ad could expire before it can be shown, i.e., right before the next level.
 
On the flipside, if the developer starts the video download shortly after the user finishes the current level, and that user skips the store to go immediately to the next level, then the video has not downloaded yet and cannot be shown to the user before the next level. In this case, it would be ideal for the video to be delivered consistently within a set amount of time. But since ad retrieving timeout is around 300-400 milliseconds, even when you cache the video, slow ad retrieval leads directly to missing revenue.
 
Net net, while video pre-caching is a valid technique, it comes with a cost, and often times expired content would still result in real-time video downloads that usually are not fast enough.
 

Compounding the Challenge: Painful Disconnects

 
Connection drops are another issue that affect video ads. Disconnects happen all the time, especially when users are on the move, such as when they're commuting or walking around a busy city and their connections must transfer to a different network type. If a disconnect happens during an API call to an ad network or while downloading a large video asset, then that ad will fail to load.

When disconnects happen, the end user typically doesn't realize that the fault lies with the networks. Instead, they usually assign blame to the developer and the app itself. Many users will get so frustrated with a dropped connection that they won't even put in the brief time it takes to reload an app.
 
Some networks are faster and more reliable than others. Verizon and T-Mobile top the US for speed, and lag slightly behind AT&T in disconnects. The problem of disconnects is particularly acute in developing countries that don't have reliable cellular and WiFi networks. But it can infest developed countries as well. According to our benchmarks from February of this year, apps users in Russia, Indonesia, Germany and Brazil all suffer from more than 10% disconnects on average, with disconnect rates as high as 30 percent on 2G networks.
 

Examples of Various Ad Download Times

 
The charts below show ads within a popular news app. The top chart shows video ads delivered by SuperSonic and the bottom chart shows those delivered by Vungle. The x axis shows the amount of time a video took to download in milliseconds; the y axis shows the percentage of the total transfers that finished within that bucket of milliseconds. What we can see overall is that ads aren't delivered within a consistent amount of time; they're usually delivered anywhere from half a second to two seconds.





 
What this says is that if you use a mediation ad network, you should expect your ads to load anywhere from less than one second up to four seconds or longer. That doesn't help you to engineer your app if it has time constraints like the example above.

So what do you do? Well, if you choose to just use one ad network, you should be able to engineer your app/game to that specific ad network based on how long that specific network loads ads. Or, you could continue to use an ad mediator with the understanding that some percent of your users will not see the ad due to it loading too fast or too slow.
 
Bottom line is, attention shifts when something takes longer to load, and time is money. So keep this in mind with your in-app video ads.

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The Latest

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

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