{"_id":"57599f34ace5c30e00cb25ff","parentDoc":null,"user":"560c92f2ac2859170013faa3","version":{"_id":"560c93ae7e9b9d0d00ca81a5","project":"560c93ad7e9b9d0d00ca81a2","__v":9,"createdAt":"2015-10-01T02:00:14.709Z","releaseDate":"2015-10-01T02:00:14.709Z","categories":["560c93af7e9b9d0d00ca81a6","560c9d9399bb5a0d0044f220","560d76d899bb5a0d0044f307","560d76ee1ec45619006069ed","560d86e099bb5a0d0044f32e","560dba80373c0e0d0024ff3b","57c722ecdf19130e001fba5d","57c743d1b6f94a2200659903","58995ec083f743190077bbe2"],"is_deprecated":false,"is_hidden":false,"is_beta":false,"is_stable":true,"codename":"","version_clean":"1.0.0","version":"1.0"},"category":{"_id":"57c743d1b6f94a2200659903","__v":0,"project":"560c93ad7e9b9d0d00ca81a2","version":"560c93ae7e9b9d0d00ca81a5","sync":{"url":"","isSync":false},"reference":false,"createdAt":"2016-08-31T20:53:37.154Z","from_sync":false,"order":3,"slug":"attribution-models-explained","title":"Attribution Models Explained"},"githubsync":"","project":"560c93ad7e9b9d0d00ca81a2","__v":11,"updates":[],"next":{"pages":[],"description":""},"createdAt":"2016-06-09T16:54:12.902Z","link_external":false,"link_url":"","sync_unique":"","hidden":false,"api":{"settings":"","results":{"codes":[]},"auth":"required","params":[],"url":""},"isReference":false,"order":1,"body":"Attribution allows you to allocate conversions to the channel that makes the most sense for your business.\n[block:api-header]\n{\n  \"type\": \"basic\",\n  \"title\": \"First Touch Attribution\"\n}\n[/block]\nWith First Touch Attribution, we will attribute the cost and conversion to the source of the first visit that occurred in the date range.  Our Attribution models are cohort based, so the conversion can happen at any point during or after the date range.\n\n<a href=\"https://attribution.readme.io/docs/multi-touch-attribution-example\">Example</a>\n[block:api-header]\n{\n  \"type\": \"basic\",\n  \"title\": \"Last Touch Attribution\"\n}\n[/block]\nWhen looking at Last Touch Attribution, we will attribute the cost and conversion to the source of the last visit in the date range immediately prior to the conversion event.\n\n<a href=\"https://attribution.readme.io/docs/last-touch-attribution-example-direct-included\">Example</a>\n[block:api-header]\n{\n  \"type\": \"basic\",\n  \"title\": \"Linear Attribution Model\"\n}\n[/block]\nWhen viewing the Dashboard using the Linear Attribution model, we will attribute the cost and conversion equally to each visit in the date range, that subsequently resulted in a conversion.\n\n<a href=\"https://attribution.readme.io/docs/linear-attribution-example-direct-included\">Example</a>\n[block:api-header]\n{\n  \"type\": \"basic\",\n  \"title\": \"Time Decay Attribution Model\"\n}\n[/block]\nWhen viewing the Time Decay Attribution Model we will attribute credit based on the number of days the visit was before the conversion.\n\nThe Calculation we use for this is:\n\ny = 2^( -x / 7 )\n\nwhere x is the number of days the referral happened prior to the conversion. The 2 in the equation is the half-life. A touchpoint 7 days before a different touchpoint, will receive half the credit.\n\nThe result is that the Last Touch will get the most credit and the First touch will get the least credit.\n\n<a href=\"https://attribution.readme.io/docs/time-decay-attribution-example-direct-included\">Example</a>","excerpt":"","slug":"understanding-attribution-models","type":"basic","title":"Understanding Attribution Models"}

Understanding Attribution Models


Attribution allows you to allocate conversions to the channel that makes the most sense for your business. [block:api-header] { "type": "basic", "title": "First Touch Attribution" } [/block] With First Touch Attribution, we will attribute the cost and conversion to the source of the first visit that occurred in the date range. Our Attribution models are cohort based, so the conversion can happen at any point during or after the date range. <a href="https://attribution.readme.io/docs/multi-touch-attribution-example">Example</a> [block:api-header] { "type": "basic", "title": "Last Touch Attribution" } [/block] When looking at Last Touch Attribution, we will attribute the cost and conversion to the source of the last visit in the date range immediately prior to the conversion event. <a href="https://attribution.readme.io/docs/last-touch-attribution-example-direct-included">Example</a> [block:api-header] { "type": "basic", "title": "Linear Attribution Model" } [/block] When viewing the Dashboard using the Linear Attribution model, we will attribute the cost and conversion equally to each visit in the date range, that subsequently resulted in a conversion. <a href="https://attribution.readme.io/docs/linear-attribution-example-direct-included">Example</a> [block:api-header] { "type": "basic", "title": "Time Decay Attribution Model" } [/block] When viewing the Time Decay Attribution Model we will attribute credit based on the number of days the visit was before the conversion. The Calculation we use for this is: y = 2^( -x / 7 ) where x is the number of days the referral happened prior to the conversion. The 2 in the equation is the half-life. A touchpoint 7 days before a different touchpoint, will receive half the credit. The result is that the Last Touch will get the most credit and the First touch will get the least credit. <a href="https://attribution.readme.io/docs/time-decay-attribution-example-direct-included">Example</a>