One of the reasons that people have trouble understanding attribution models is that there are a lot of rules to follow, and it's almost impossible for a human to keep track of everything for many users and many visits. The best way to understand how Attribution works is to look at one user with multiple conversions over a timeline.

Consider this scenario, where a user has 6 visits over 12 days and 2 conversions. How would you allocate the conversions to each of these channels in each Attribution Model?

DateChannel (visit)Action
5/5Direct
5/9DirectConversion \$10
5/12Conversion \$5

### 🚧Understanding Date Ranges

When you select a date range in Attribution, the results shown are the visits that happened in that date range and the resulting conversions that came from those visits, even if they happen in the future.

## Time Decay Attribution (Direct Traffic Included) 5/1 - 5/12

First we will look at the results of the model and then we will explain the math below:

SourceVisitsConversionsConversion Revenue
Direct2.821\$6.46
Total2\$15

Below is the calculation for the 1st conversion for the date range:

SourceDays from ConversionFirst ConversionPro Rata ConversionRevenue
Facebook82^(-8/7) = .45.45 / 3.56 = .127.127 * \$10 = \$1.27
Adwords52^(-5/7) = .61.61 / 3.56 = .171.171 * \$10 = \$1.71
Direct42^(-4/7) = .67.67 / 3.56 = .189.189 * \$10 = \$1.89
Facebook22^(-2/7) = .82.82 / 3.56 = .231.231 * \$10 = \$2.31
Direct02^(-0/7) = 11 / 3.56 = .281.281 * \$10 = \$2.81
3.561\$10

Below is the calculation for the 2nd conversion for the date range:

SourceDays from ConversionFirst ConversionPro Rata ConversionRevenue
Facebook112^(-11/7) = .34.34 / 3.55 = .095.095 * \$5 = \$.47
Adwords82^(-8/7) = .45.45 / 3.55 = .128.128 * \$5 = \$.64
Direct72^(-7/7) = .50.50 / 3.55 = .141.141 * \$5 = \$.70
Facebook52^(-5/7) = .61.61 / 3.55 = .172.172 * \$5 = \$.86
Direct32^(-3/7) = .74.74 / 3.55 = .209.209 * \$5 = \$1.05
Adwords12^(-1/7) = .91.91 / 3.55 = .255.256 * \$5 = \$1.28
Total3.552\$5