The Mobile advertising industry landscape consists of two major parts – Supply, that is presented by publishers and a SSP (stands for Supply Side Platform) that aggregates mobile inventory across hundreds of thousands of publishers and Demand, that is presented by a DSP (stands for Demand Side Platform) that allows advertisers to place mobile ads in publishers desktop or mobile inventory.
A Mobile Ad Network function is to serve a middle point between these two ends of the value chain, moving inventory across both supply and demand, either directly or via reselling or re-broking of inventory.
On some occasions, companies register with an ad network as both advertiser and publisher. Such double registration allows these companies to account traffic it generates as a publisher to cover fees it needs to pay for traffic it acquires as an advertiser.
Ad networks involvement into advertiser – publisher dynamics isn’t always limited with mobile traffic delivery and providing performance stats, sometimes, when advertisers budget is high, ad networks get involved into ad creatives production. For instance, in a case of video ads, that today run supreme of digital advertising efficiency, ad networks can substantially improve advertiser’s ad campaign efficiency and increase its revenue.
The pioneer in the mobile ad networks space was AdMob , that really took off after its acquisition in 2009 by Google, Inc. Over the course of more than 10 years since, the advertising networks space has grown with a small number of top tier companies have been controlling the market. Apart from AdMob by Google, which later become part of the Google Ads ad platform, these are Facebook, Twitter and, in a smaller degree, Snapchat and Pinterest. The paramount advantage that allows these companies to occupy the top tier of the mobile ad market is how much data they can accumulate on their registered users and leverage this data for ad campaigns precise targeting.
Now, the recent newcomers Reddit and TikTok present an interesting case. The former has one of the most diverse online communities on the planet to reach and monetize and the latter is the brand new China-based social media that is like no other US counterpart. Both are worth of advertisers attention as an alternatives (or extra options) to Facebook and Google.
The next tier, that has survived competition with aforementioned companies and continues to compete for mobile advertisers budgets, consists of Applovin, UnityAds, ironSource and Vungle. Compared with the Google and Facebook duopoly, these four have much less data points for a mobile user profile and therefore can not target mobile ads as precise as the top tier companies. To partly negate this limitation and help advertisers achieve their goals, these companies provide account managers to handle low-level ad campaigns management.
One of the most profound shifts in the mobile ad industry is that mobile apps have become the major inventory for ads to be displayed in, replacing traditional mobile web. This shift has even coined a new term – in app advertising. There is a simple reason behind this transition – multiple researches demonstrate that people spend most of the time with mobile devices, using apps, not browsing web sites as they used to. With the number of mobile apps that continues to increase exponentially, mobile in app advertisements have a potential to replace mobile web ads completely. Today all highest paying mobile ad networks are laser focused on mobile as the fastest growing digital advertising sector.
As mobile advertising industry continues to grow, it becomes more and more apparent that moving all operations into programmatic area is the only way to go. This is how you can accommodate greater and greater advertising volumes, allow ever increasing number of advertisers to manage their ad campaigns efficiently and mobile publishers to maximize their inventory monetization.
The downside of the programmatic approach is that it produces lower engagement rates, introduces advertisers to risk of a fraud, generally it’s less relevant compared to manual ad campaigns and can even be harmful for brands in cases when their ads occasionally being placed on websites next to questionable content.
Continue the trend on advertising automation, Artificial Intelligence algorithms are praised as the way to tackle multiple challenges that digital advertising faces. In fact, AI is the technology that many industries embrace to handle big data volumes to search for patterns and valuable insights to increase its efficiency. For mobile advertising it is also a brand new way to better fight off mobile ad fraud.
Speaking of mobile ad fraud, according to Jupiter research this year it’s the advertisers fate to loose $42 billion because of a fraud. There are two kinds of digital ad fraud – technical and compliance one. The first one covers all sorts of technical ways to trick ad network into considering fake advertising events as genuine ones and the second covers multiple tactics to break the rules established on a specific advertising platform. Examples of technical fraud are ad stacking, attribution fraud, faked postbacks. The compliance fraud has to do with viewability, cases of placing ads in areas it rarely can be seen but still reported as seen, tricking users into clicking on ads, re-brokering ad offers from one publisher to another and more.
Table of Contents
- Mobile Advertising Business models
- Mobile Ad Formats
- Mobile Advertising rankings
- List of best mobile ad networks
Now, before we’ll start profiling top mobile ad networks, let’s define several characteristics to describe a mobile ad network.
Mobile Advertising Business Models
All mobile ad networks provide users with several types of business models to run ad campaigns with. There are 5 major types – CPM, CPC, CPI, CPA and CPV.
With CPM (cost-per-mile) type, an advertiser is charged each time her or his ads are shown 1,000 times (so-called ‘a mile’). It’s the best business model for publishers, because it allows to make money every time an ad was displayed. If they have a stable predictable traffic, it allows publishers to forecast their revenue. The down side is that they may loose some extra revenue, if their app or website audience is really interested in a product or service they advertise. For that case CPC model would allow them to make more money.
With CPC (cost-per-click) model an advertiser is charged for each click made on her or his mobile ads. This model works better for advertisers, because it allows them to pay only for instances when an interest to their product or service is explicit (their ads were clicked) and, as mentioned above, in some cases may work for publishers as well. For a publisher this model always presents a certain risk of him serving lots of ad impressions for free.
CPI (cost-per-instal) model implies that advertisers are charged only when a click on their ads resulted into an actual mobile app install. It’s a specific case of a more generic CPC business model. Cost-per-install price has become one of the most important metrics for mobile app marketers to measure and keep track of, because essentially it represents a price they pay to acquire customers and hence it should be factor into ROI calculations.
CPA (cost-per-action) type is more advanced version of CPI, when an advertiser is charged for specific action (in-app sale, subscription, form submit, sign up and more) users take inside an app that is advertised on a mobile ad network. This type of a business model presents more opportunities for publishers to monetize their inventory on one hand and more options for advertisers to grow their business on the other.
And finally CPV (cost-per-view) type is applicable to mobile ad networks that provide advertisers with video ad campaigns. With this model, advertisers are charged for each instance their video mobile ad was viewed. With the current pace of a video advertising growth, this model becomes more and more popular.
Top Mobile Ad Networks
- EvaDav - Buy and sell traffic, push-notification, native ads
- Jampp - Unlock new growth
- Performcb - #1 Performance Marketing Network Worldwide
- Hitapps - Complex digital advertising solutions that drive results.
- mediasmart - Self Serve Programmatic Platform For Incremental Growth
- Adikteev - Data-driven app marketing platform
- Zoomd - Know More, Do More
- App Annie - Unlock advertising, monetization and acquisition ROI with Ascend
- Bidease - #1 DSP for mobile app marketers
- myAppFree - High Quality Mobile Traffic & Exclusive Placements on SONY Xperia, Native SDK
- Tenjin - iOS 14-proof advertising analytics
- Adjust - Mobile Measurement Partner
- Mobupps - A One Stop Shop For All Your Mobile Marketing Needs
- TrafficGuard - #1 ad fraud prevention for brands, networks and agencies
- Appitate - We provide mobile CPI and CPA offers
- ironSource - Connecting people with apps
Mobile Ad Formats
A full screen ads that cover the interface of their host application. This mobile ad format is most frequently used to display an ad between different app screens and it’s quite often displayed between different levels in a mobile game app.
A classical static or animated image ad, which is placed inside an app’s interface. Such ad may advertise a third party product, other digital or physical goods, as well as an option to expand an app’s functionality.
Either a banner image or video ad that matches the form and function of the app interface it’s displayed in. The core concept of native ads to mimic an app’s interface to be least intrusive compared to other ad formats.
It is an ad unit within a mobile app that provides end users with lots of offers to engage with. The most frequent use case is mobile games, where offerwalls may either advertise third party games or a series of games from the same game developer.
Video ads consist of a short, usually up-to 60 seconds, video clip to advertise products and services. This mobile ad format is most often used within media apps. There are two major types of video ads – in-stream and out-stream. With in-stream type, video ads are displayed full-screen before, after and within video content that is streamed inside an app. With out-stream type video ads are displayed on a web page, displayed inside a mobile app.
Mobile Ads Reporting
An advertising campaign performance data reporting is one of the key components that is crucial for its success. This information is provided by mobile ad networks to advertisers via an online dashboard. It includes data on such parameters of ads performance as number of impressions, clicks, installs, video ad views, platform, country, ad format and so on.
Mobile Ads Targeting
There are number of parameters that allow to narrow down a mobile ad campaign reach to a specific audience. These parameters are called targeting options, there are a number of such options but the majors are the following:
It allows to narrow down an ad campaign within a specific country or region. It enables mobile marketers to advertise a product or service that is relevant only within a specific region.
It allows to show ads on specific models of mobile devices only. This type of targeting lets advertisers to display ads on devices with a specific screen size and other hardware requirements, which allows to avoid a mobile ad experience degradation.
With this option, it’s possible to show ads only to mobile users, who are served by a specific mobile carrier. It presents advertisers an opportunity to display ads to mobile users, those mobile carrier provides a better mobile signal reception in a specific area.
it allows to show ads on mobile devices running specific operating system or even particular versions of OS. It gives advertisers a benefit of displaying ads to mobile users on devices that are best to display those ads software wise.
By applying this targeting option, it’s possible to show mobile ads on mobile devices when they are connected to the Internet either via Wifi or 3G/LTE connection.
mobile ad network that collect mobile users data and build their profile allows to narrow down an ad campaign on an audience segment with specific interests only.
This option allows to narrow down an ad campaign to mobile users of a particular gender. Naturally, just like with any kind of advertising such targeting is aimed to market goods specifically to females and males.
One of the best sources to check a particular mobile ad network performance is the AppsFlyer semi-annual Performance Index. Below you can see the snippet from the H1, 2019 edition and it covers media sources performance for both gaming and non-gaming apps for iOS and Android operating system.
In the table, Volume Ranking based on the total number of non-fraudulent installs each was attributed for, Power Ranking based on the normalized and combined number of non-fraudulent installs, the number of apps running with each media source and the weighted retention score.
Mobile Advertising rankings
Top 10 Media Sources [both iOS and Android]
Another company that provides data to measure mobile ad networks performance is Singular – the mobile marketing analytics platform that issued earlier this year the Singular ROI Index. It’s compiled based on the data Singular derived from more than 550+ mobile media sources, 2.2 billion installs with matching ROI, $6.3 billion in advertising spend. The index factors in a number of metrics, such as mobile user retention, revenue per install and what is the most important – the cost to drive app users engagement.
This year Index does’t rate the companies that got on the list due to really narrow margins in their performance.
Singular ROI Index Top 10 [iOS app data]
|Apple Search Ads||Applovin|
|Twitter Ads||Unity Ads|
Source: Singular ROI Index 2020
Singular ROI Index Top 10 [Android app data]
|Facebook Ads||Google Ads|
|Twitter Ads||Unity Ads|
Source: Singular ROI Index 2020
Now let’s take a look at the list of top mobile ad networks of 2020 we’ve compiled for app developers and mobile business owners to find the right one to work with. To compile this list we researched the major players in the mobile advertising field, included companies that offer the wide range of ad formats and targeting options, as well as robust statistics and good technical support.