{"id":15503,"date":"2026-02-20T07:06:13","date_gmt":"2026-02-20T07:06:13","guid":{"rendered":"http:\/\/mariusz.bijok"},"modified":"2026-06-15T10:28:30","modified_gmt":"2026-06-15T10:28:30","password":"","slug":"attribution-faq","status":"publish","type":"docs","link":"https:\/\/tenjin.com\/pt\/docs\/attribution-faq\/","title":{"rendered":"Perguntas frequentes sobre atribui\u00e7\u00e3o"},"content":{"rendered":"

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O que s\u00e3o \u00abinstala\u00e7\u00f5es registadas\u00bb e \u00abinstala\u00e7\u00f5es comunicadas\u00bb? Por que raz\u00e3o estas duas instala\u00e7\u00f5es diferem?<\/h5><\/div><\/div><\/div>
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Ao utilizar o Tenjin, ir\u00e1 verificar que existem dois tipos de instala\u00e7\u00f5es: \u00abInstala\u00e7\u00f5es comunicadas\u00bb e \u00abInstala\u00e7\u00f5es monitorizadas\u00bb.<\/p>\n\n\n\n

Instala\u00e7\u00f5es comunicadas<\/strong> are installs that the ad network claims to drive for each of your campaigns. Instala\u00e7\u00f5es registadas<\/strong> are installs that an unbiased 3rd party attributes to an ad network’s campaign, taking into account the other campaigns you’re running on other ad networks. When looking at Tracked Installs, you are looking at an install metric that is holistic – it’s based on all campaigns, even ones that you’re running on other ad networks. Reported Installs, on the other hand, is calculated in a vacuum by the ad network you’re running on – it’s only based on what that ad network sees.<\/p>\n\n\n\n

So are Reported Installs supposed to be the same as Tracked Installs?<\/strong> Not always. The point of attribution ISN’T to make Tracked Installs = Reported Installs. In fact, sometimes attribution is supposed to do the exact opposite. The point of attribution is to take a holistic view of ALL the campaign activity on the various ad networks you’re using at the same time, and attribute users to the most appropriate campaign. Only an unbiased 3rd party can do this.<\/p>\n\n\n\n

Por exemplo:<\/strong> You’re running campaigns on two ad networks at the same time, Applovin and Tiktok. You set the CPIs to $1.00 for each campaign on each ad network. A unique user clicks on your Applovin campaign, then later that same user clicks on your Tiktok campaign, then installs the app. What happens? How is everything tracked for that user?<\/p>\n\n\n\n

Uma vez que a Applovin e o TikTok n\u00e3o comunicam entre si, n\u00e3o h\u00e1 forma de conciliar o utilizador \u00fanico que interage com ambas as campanhas publicit\u00e1rias em redes distintas ao mesmo tempo. Consequentemente, o n\u00famero de instala\u00e7\u00f5es reportadas pela Applovin seria \u201c1\u201d e o n\u00famero de instala\u00e7\u00f5es reportadas pela Tiktok seria tamb\u00e9m \u201c1\u201d. Eis o que temos at\u00e9 agora:<\/p>\n\n\n\n

\"image.png\"<\/figure>\n\n\n\n

Mas isto n\u00e3o faz sentido! S\u00f3 conseguimos um \u00fanico utilizador \u00fanico! Um utilizador \u00fanico s\u00f3 deve estar associado a uma das campanhas!<\/p>\n\n\n\n

That’s what attribution solves. By using a 3rd party attribution provider like Tenjin, Tenjin will place the user into the Tiktok campaign as a “Tracked Install” (based on the last click in this case). This way, the unique user who clicked on Applovin and then Tiktok will be associated with Tiktok’s campaign and NOT Applovin’s. In this example the count for Tracked Installs and Reported Installs would look like this:<\/p>\n\n\n\n

\"image.png\"<\/figure>\n\n\n\n

Now the unique user is in the appropriate ad network campaign for downstream analysis of your campaigns. If the user starts generating LTV, then you know what the effectiveness of your spend is. This is the only way you can measure your ROI on an apples-to-apples basis.<\/p>\n\n\n\n

Suponhamos, ent\u00e3o, que o utilizador adquirido gere um LTV de 90 dias de $2.5. A sua an\u00e1lise revelaria o seguinte:<\/p>\n\n\n\n

\"image.png\"<\/figure>\n\n\n\n

Neste caso, o ROI = (LTV\/Despesa - 1).<\/p>\n\n\n\n

Isto permite-lhe saber que a sua campanha no Google \u00e9 mais eficaz do que a sua campanha no Facebook para esse utilizador espec\u00edfico.<\/p>\n<\/div><\/div><\/div>\n\n\n\n

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Por que raz\u00e3o existem discrep\u00e2ncias entre as instala\u00e7\u00f5es registadas e as comunicadas?<\/h5><\/div><\/div><\/div>
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Normalmente, \u00e9 de esperar uma discrep\u00e2ncia de at\u00e9 30% para as SANs e de 10% para as n\u00e3o-SANs, pelas raz\u00f5es abaixo indicadas:<\/p>\n\n\n\n