Metric type and Attribution
You can configure the metric type and attribution model for a metric in a calculated metric definition.
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Select
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In the popup dialog:
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Specify the Metric type:
table 0-row-2 1-row-2 2-row-2 Metric Type Definition Standard If a formula consists of a single standard metric, it displays identical data to its non-calculated-metric counterpart. Standard metrics are useful to create calculated metrics specific to each individual line item.
For example,
Grand total Use Grand total for the reporting period in every line item. If a formula consists of a single Grand total metric, the calculated metric displays the same Grand total number on every line item. Grand total metrics are useful when you want to create calculated metrics that compare against total data.
For example,
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Specify Attribution.
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You can either:
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Disable Use non-default attribution model to use the default column attribution model, which is Last Touch, with a lookback window of 30 days.
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Enable Use non-default attribution model. In the Column attribution model dialog,
- Select a Model from the attribution models.
- Select a Container from the container options.
- Select a Lookback window from the lookback window options. If you select Custom Time, you can define the time period in Minute(s) up to Quarter(s).
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Select Apply to apply the non-default attribution model. Select Cancel to cancel.
If you already have defined a non-default attribution model, select Edit to modify the selection.
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See Example for an example of using an attribution model, container, and lookback window.
Attribution models attribution-models
An attribution model determines which dimension items get credit for a metric when multiple values are seen within a metric’s lookback window. Attribution models only apply when there are multiple dimension items set within the lookback window. If only a single dimension item is set, that dimension item gets 100% credit regardless of attribution model used.
2^(-t/halflife), where t is the amount of time between a touch point and a conversion. All touch points are then normalized to 100%. Ideal for scenarios where you want to measure attribution against a specific and significant event. The longer a conversion happens after this event, the less credit is given.
At a high level, attribution is calculated as a coalition of players to which a surplus must be equitably distributed. Each coalition’s surplus distribution is determined according to the surplus that was previously created by each subcoalition (or previously participating dimension items) recursively. For more details, see John Harsanyi’s and Lloyd Shapley’s original papers:
Shapley, Lloyd S. (1953). A value for n-person games. Contributions to the Theory of Games, 2(28), 307-317.
Harsanyi, John C. (1963). A simplified bargaining model for the n-person cooperative game. International Economic Review 4(2), 194-220.
Container container
An attribution container defines the desired scope for the attribution. Possible options are:
- Session: Looks back up to the beginning of the session where a conversion happened. Session lookback windows respect the modified Session timeout in a data view.
- Person: Looks at conversions from the scope of the person container.
- Global Account [B2B Edition]{class="badge informative"}: Looks at conversions from the scope of the global accounts container.
- Accounts [B2B Edition]{class="badge informative"}: Looks at conversions from the scope of the person container .
- Opportunity [B2B Edition]{class="badge informative"}: Looks at conversions from the scope of the opportunity container .
- Buying group [B2B Edition]{class="badge informative"}: Looks at conversions from the scope of the buying group container.
Lookback window lookback-winwow
A attribution lookback window is the amount of time a conversion should look back to include touch points. If a dimension item is set outside of the lookback window, the value is not included in any attribution calculations.
- 14 Days: Looks back up to 14 days from when the conversion happened.
- 30 Days: Looks back up to 30 days from when the conversion happened.
- 60 Days: Looks back up to 60 days from when the conversion happened.
- 90 Days: Looks back up to 90 days from when the conversion happened.
- 13 Months [B2B Edition]{class="badge informative"}: Looks back up to 13 months from when the conversion happened.
- Custom Time: Allows you to set a custom lookback window from when a conversion happened. You can specify the number of minutes, hours, days, weeks, months, or quarters. For example, if a conversion happened on February 20, a lookback window of five days would evaluate all dimension touchpoints from February 15 to February 20 in the attribution model.
Example
Consider the following example:
- On September 15, a person arrives to your site through a paid search advertisement, then leaves.
- On September 18, the person arrives to your site again through a social media link they got from a friend. They add several items to their cart, but do not purchase anything.
- On September 24, your marketing team sends them an email with a coupon for some of the items in their cart. They apply the coupon, but visit several other sites to see if any other coupons are available. They find another through a display ad, then ultimately make a purchase for $50.
Depending on your attribution model, container and channels receive different credit. See table below for examples:
Credit is divided between paid search, social, email, and display.
- 60% credit is given to display, for $30.
- 20% credit is given to paid search, for $10.
- The remaining 20% is divided between social and email, giving $5 to each.
- Gap of zero days between display touch point and conversion.
2^(-0/7) = 1 - Gap of zero days between email touch point and conversion.
2^(-0/7) = 1 - Gap of six days between social touch point and conversion.
2^(-6/7) = 0.552 - Gap of nine days between paid search touch point and conversion.
2^(-9/7) = 0.41Normalizing these values results in the following:- Display: 33.8%, getting $16.88
- Email: 33.8% getting $16.88
- Social: 18.6%, getting $9.32
- Paid Search: 13.8%, getting $6.92
Conversion events that typically have whole numbers are divided if credit belongs to more than one channel. For example, if two channels contribute to an order using a Linear attribution model, both channels get 0.5 of that order. These partial metrics are summed across all people then rounded to the nearest integer for reporting.
[B2B Edition]{class="badge informative" title="Customer Journey Analytics B2B Edition"} Use specific B2B containers, like Accounts, or Opportunities, and more appropriate lookback windows (up to 13 months) to apply above attribution models in typical B2B scenarios.