{"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\/vi\/docs\/attribution-faq\/","title":{"rendered":"C\u00e2u h\u1ecfi th\u01b0\u1eddng g\u1eb7p v\u1ec1 Quy\u1ec1n t\u00e1c gi\u1ea3"},"content":{"rendered":"

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\u201cC\u00e0i \u0111\u1eb7t \u0111\u01b0\u1ee3c theo d\u00f5i\u201d v\u00e0 \u201cc\u00e0i \u0111\u1eb7t \u0111\u01b0\u1ee3c b\u00e1o c\u00e1o\u201d l\u00e0 g\u00ec? T\u1ea1i sao hai lo\u1ea1i c\u00e0i \u0111\u1eb7t n\u00e0y l\u1ea1i kh\u00e1c nhau?<\/h5><\/div><\/div><\/div>
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Khi s\u1eed d\u1ee5ng Tenjin, b\u1ea1n s\u1ebd nh\u1eadn th\u1ea5y c\u00f3 hai lo\u1ea1i l\u01b0\u1ee3t c\u00e0i \u0111\u1eb7t: \u201cL\u01b0\u1ee3t c\u00e0i \u0111\u1eb7t \u0111\u01b0\u1ee3c b\u00e1o c\u00e1o\u201d v\u00e0 \u201cL\u01b0\u1ee3t c\u00e0i \u0111\u1eb7t \u0111\u01b0\u1ee3c theo d\u00f5i\u201d.<\/p>\n\n\n\n

S\u1ed1 l\u01b0\u1ee3t c\u00e0i \u0111\u1eb7t \u0111\u00e3 b\u00e1o c\u00e1o<\/strong> are installs that the ad network claims to drive for each of your campaigns. C\u00e0i \u0111\u1eb7t \u0111\u01b0\u1ee3c theo d\u00f5i<\/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

V\u00ed d\u1ee5:<\/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

V\u00ec Applovin v\u00e0 TikTok kh\u00f4ng k\u1ebft n\u1ed1i v\u1edbi nhau, n\u00ean kh\u00f4ng c\u00f3 c\u00e1ch n\u00e0o \u0111\u1ec3 hai n\u1ec1n t\u1ea3ng n\u00e0y \u0111\u1ed1i chi\u1ebfu th\u00f4ng tin v\u1ec1 ng\u01b0\u1eddi d\u00f9ng duy nh\u1ea5t t\u01b0\u01a1ng t\u00e1c v\u1edbi c\u1ea3 hai chi\u1ebfn d\u1ecbch qu\u1ea3ng c\u00e1o tr\u00ean hai m\u1ea1ng l\u01b0\u1edbi ri\u00eang bi\u1ec7t c\u00f9ng m\u1ed9t l\u00fac. Do \u0111\u00f3, s\u1ed1 l\u01b0\u1ee3t c\u00e0i \u0111\u1eb7t \u0111\u01b0\u1ee3c b\u00e1o c\u00e1o c\u1ee7a Applovin s\u1ebd l\u00e0 \u201c1\u201d v\u00e0 s\u1ed1 l\u01b0\u1ee3t c\u00e0i \u0111\u1eb7t \u0111\u01b0\u1ee3c b\u00e1o c\u00e1o c\u1ee7a TikTok c\u0169ng s\u1ebd l\u00e0 \u201c1\u201d. D\u01b0\u1edbi \u0111\u00e2y l\u00e0 nh\u1eefng g\u00ec ch\u00fang ta c\u00f3 \u0111\u01b0\u1ee3c cho \u0111\u1ebfn nay:<\/p>\n\n\n\n

\"h\u00ecnh.png\"<\/figure>\n\n\n\n

Nh\u01b0ng \u0111i\u1ec1u n\u00e0y th\u1eadt v\u00f4 l\u00fd! Ch\u00fang ta ch\u1ec9 thu h\u00fat \u0111\u01b0\u1ee3c m\u1ed9t ng\u01b0\u1eddi d\u00f9ng duy nh\u1ea5t! M\u1ed9t ng\u01b0\u1eddi d\u00f9ng duy nh\u1ea5t ch\u1ec9 n\u00ean \u0111\u01b0\u1ee3c li\u00ean k\u1ebft v\u1edbi m\u1ed9t trong c\u00e1c chi\u1ebfn d\u1ecbch!<\/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

\"h\u00ecnh.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

Gi\u1ea3 s\u1eed ng\u01b0\u1eddi d\u00f9ng m\u1edbi thu h\u00fat \u0111\u01b0\u1ee3c t\u1ea1o ra gi\u00e1 tr\u1ecb tr\u1ecdn \u0111\u1eddi (LTV) trong 90 ng\u00e0y l\u00e0 $2.5. Ph\u00e2n t\u00edch c\u1ee7a b\u1ea1n s\u1ebd cho th\u1ea5y nh\u1eefng \u0111i\u1ec1u sau:<\/p>\n\n\n\n

\"h\u00ecnh.png\"<\/figure>\n\n\n\n

Trong tr\u01b0\u1eddng h\u1ee3p n\u00e0y, ROI = (LTV\/Chi ph\u00ed - 1).<\/p>\n\n\n\n

\u0110i\u1ec1u n\u00e0y cho b\u1ea1n bi\u1ebft r\u1eb1ng chi\u1ebfn d\u1ecbch Google c\u1ee7a b\u1ea1n hi\u1ec7u qu\u1ea3 h\u01a1n chi\u1ebfn d\u1ecbch Facebook \u0111\u1ed1i v\u1edbi ng\u01b0\u1eddi d\u00f9ng c\u1ee5 th\u1ec3 \u0111\u00f3.<\/p>\n<\/div><\/div><\/div>\n\n\n\n

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T\u1ea1i sao l\u1ea1i c\u00f3 s\u1ef1 ch\u00eanh l\u1ec7ch gi\u1eefa s\u1ed1 l\u01b0\u1ee3t c\u00e0i \u0111\u1eb7t \u0111\u01b0\u1ee3c theo d\u00f5i v\u00e0 s\u1ed1 l\u01b0\u1ee3t c\u00e0i \u0111\u1eb7t \u0111\u01b0\u1ee3c b\u00e1o c\u00e1o?<\/h5><\/div><\/div><\/div>
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Th\u00f4ng th\u01b0\u1eddng, m\u1ee9c ch\u00eanh l\u1ec7ch t\u1ed1i \u0111a l\u00e0 30% \u0111\u1ed1i v\u1edbi c\u00e1c h\u1ec7 th\u1ed1ng SAN v\u00e0 10% \u0111\u1ed1i v\u1edbi c\u00e1c h\u1ec7 th\u1ed1ng kh\u00f4ng ph\u1ea3i SAN l\u00e0 \u0111i\u1ec1u c\u00f3 th\u1ec3 d\u1ef1 ki\u1ebfn \u0111\u01b0\u1ee3c do c\u00e1c l\u00fd do sau \u0111\u00e2y:<\/p>\n\n\n\n