Is TROPHiT yet another incentivized traffic solution?

Exactly the opposite. The idea of "rewards" and "gifts", traditionally associated with incent-traffic, are the root of the confusion... Below, we dig a little deeper, in order to make a proper comparison.

Traditionally, advertisers refer to two types of user acquisition methods: incentivized and non-incentivized. TROPHiT introduces a third method, which is the core essence of "value-driven marketing" as we call it. 

With the Incentivized method, an app would offer its user a reward inside itself, for downloading some other app, do something there, and come back. This usually drives a lot of traffic to the downloaded app, however, user quality is low, as the user’s mind is elsewhere – he is only downloading the app because he can’t wait to go back to his original app and get what he was offered.

In the non-incentivized method, an app does not offer any reward to its user – it usually just pops up an ad unit (image, video, etc), saying “Check out this game, download for FREE”. This drives less traffic volume to the downloaded app, user quality is higher, but the value of the offer isn't immediately apparent: saying the game is "FREE" is taken for granted and is not considered real value.

Hence, TROPHiT offers a third method: grant users real value in the form of virtual items - not in the game they are currently playing, but rather in the game they are about to download. Different user targets may receive different things. Example: “here’s a free 200 coin-pack for you (would normally cost 0.99$), tap here to claim in Car Racing 2”. It conveys a message of good will by the advertiser and the value is immediately apparent. Once the user downloads, opens the game and sees the bonus waiting for them inside, the sense of added value causes them to be more immersed in the game – not just neutral. They have downloaded the app to explore what that extra value could bring. Their mind is completely within the advertiser's game.

This method has already shown improvements in user quality: users stay longer in the game, their frequency of use increases, and as a consequence, their LTV may improve over time. Hence, this approach exhibits a reverse effect on the traditional incentive method.



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