Over the last few years, companies like Taboola, Outbrain, Gravity and others have created a new online reading habit: clicking on one of the links at the bottom of the page for the next article to read.

It makes sense. After reading an interesting article, we’re more likely to click on a similar one recommended by the algorithm.

Using algorithms to make recommendations was actually a digital marketing innovation introduced by Amazon with their ‘Customers Who Bought This Item Also Bought’ functionality. In the same way that the algorithm increases sales for Amazon, its increasing page views and time spent on-site for the publishers integrating content discovery widgets.

When we look at mobile user habits we can see that content relevancy is even more important due to information overload and space scarcity. Proven in publishing and retailing, algorithm-based recommendations of relevant apps have great potential on mobile and deliver improved results. App discovery units implemented on publisher websites deliver a two-to-three percent click-through rate (CTR) on average, opening an additional revenue stream for mobile traffic monetization, while bringing additional user value.

That is why app discovery recommendations are providing publishers with new opportunities to increase user engagement and, ultimately, ad revenue.

Taboola, one of the leaders in content recommendation is already including apps among their recommendations on mobile, and I suspect that Outbrain will start doing so soon.

Here’s how publishers – from national portals to blogs – can benefit by extending their mobile content with app recommendations:

  • Offer apps as a recommendation: As long as the app being recommended is contextually relevant to the article, there is no reason not to include it among the recommendations being made at the bottom of the article. A reader who just finished reading an article about football is probably open to playing a quick in-app game of football or interested in checking out game stats in a relevant sport category app. Apps are forms of content and developers and publishers need to treat them accordingly. The implementation can be as simple as adding a widget.
  • Add app recommendations during natural in-app breaks: If app recommendations will work after reading an article, they’ll definitely work during natural in-app breaks. For example, let’s say a reader just boarded a bus based on the recommendation of Moovit, the transportation app. Wouldn’t that reader be interested in an app to make the bus ride more enjoyable? If she just finished checking her stock quotes in a financial app, is there a chance she might play a round of golf on her phone? In the same way that natural breaks in games are an effective time to present new games, a natural break in an app is a great time to recommend other complementary apps.
  • Make app discovery native: In the same way that article recommendations appear native to the publisher’s content, so should app recommendations. Whether apps are recommended at the end of an article or in-app, the users should feel that the apps being recommended are a natural and native extension of the content that they are currently experiencing.

App discovery can change our mobile content experience in the same way that content discovery changed our reading habits. It enables us to uncover new, relevant and exciting apps we didn’t know existed. With users spending more and more time with their mobile devices (and less time with stationary devices), app discovery is a trend which will only continue to grow.


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