Targeting and Quality in Mobile

Mobile advertising is expensive. Targeting is available but limited. There are no cookies in mobile. Apple has blocked the ability to target by user ID, instead allowing the use of the IFA. Google provides its own unique ID but is also limited. In short, it’s hard work.

Demographic targeting is an option, but this provides only general information about the user, not enough about their true preferences. In addition, most mobile publishers are primarily motivated to get paid for as many views as possible, using the CPM model.

The good news is that we are starting to see a shift in the market. Mobile advertisers are getting frustrated and want better options. They are tired of paying high prices for users who don’t stick around or accidentally click ads. Mobile ad networks are being forced to think of new and creative ways to help advertisers reach real mobile users.

Contextual targeting in mobile is most commonly presented in the form of location, time, weather, etc. But there is a lot more we can do here. If we know more about the context of “what,” we can promote ads to users that are more relevant resulting in better CTR percentages, higher retention and lower user acquisition costs. At Bunndle, we focus on trying to cross-promote apps that have contextual relevancy. For example, if you are using a banking app we might cross-promote a security app. Cross-promoting apps reaches users when they are most engaged and likely to install an application that is relevant.

Publishers also benefit because advertisers will pay more money for a real user than they will for a generic ad with no targeting. Backing into the math, publishers can make three to five times more, all due to better performance.

Contextual relevancy focused on the “what” also means a better experience for the end user. It’s still very difficult to find what apps you need, or want, without resorting to surveying friends or thumbing through the “top” sections in the App Store, Google Play and other marketplaces. Inefficient and ineffective discovery leads to low satisfaction and high app abandonment – figures from Nuance reveal as high as 95 percent of apps are never used again a month after download. The discovery problem will only get worse as app stores continue to balloon in size, with eMarketer forecasting mobile app downloads growing from 81 billion worldwide in 2013 to 309 billion by 2016.

By using what we know about the user and introducing them to apps related to those they’re already interested in, users and app publishers stand a better chance of match-making.

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