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Overview table

The overview table shows how different models attribute a conversion journey with four different (non-direct) touchpoints.
Attribution ModelFirst TouchMiddle Touch 1Middle Touch 2Last TouchOnly Paid Channels
First touch100%0%0%0%
First touch paid only100%0%0%0%
Last touch0%0%0%100%
Last touch paid only0%0%0%100%
Linear25%25%25%25%
Participation100%100%100%100%
J-shaped20%10%10%60%
Inverse J-shaped60%10%10%20%
U-shaped40%10%10%40%
Time decay*----
Inverse time decay*----
* The Time decay and Inverse time decay models consider the time between touchpoints, which isn’t shown in the simplified table above. Read more about the Time decay model here.
All attribution models ignore direct touchpoints—unless the customer journey only contains direct touchpoints.For example, in this customer journey: Facebook > Direct > Google > Direct > Conversion, the last touch model attributes the entire conversion to Google, while a linear model attributes 50% to Facebook and 50% to Google.

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Attribution window

Converge uses a fixed attribution window of 30 days.

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Attribution models

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Direct

Description: All credit goes to the channel of the session where the conversion occurred. Use case: Understand which channel drove the conversion session.
The direct model attributes conversions to the channel of the conversion session, while the last touch model attributes conversions to the last touchpoint (non-direct if available) of the customer journey.For example, with this customer journey:
  • Facebook-session > Google-session > Direct-session with conversion
The direct model attributes the conversion to Direct, while the last touch model attributes it to Google.

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First touch

Description: All credit goes to the first touchpoint Converge observed in this customer journey. This touchpoint can be either a paid channel (e.g. Facebook) or a non-paid channel (e.g. Organic Search). Use case: Check how channels contribute to acquiring prospective customers. Example for 4 touchpoints:
First TouchMiddle Touch 1Middle Touch 2Last Touch
100%0%0%0%

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First touch paid only

If no paid touchpoint can be found, then the conversion will be attributed to No web touchpoint.
Description: All credit goes to the first paid touchpoint Converge observed in this customer journey. Use case: Check how paid channels contribute to acquiring prospective customers. Example for 4 touchpoints:
First TouchMiddle Touch 1Middle Touch 2Last Touch
100%0%0%0%

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Last touch

Description: All credit goes to the last touchpoint Converge observed in this customer journey. This touchpoint can be either a paid channel (e.g. Facebook) or a non-paid channel (e.g. Organic Search). Use case: Check how channels contribute to converting prospects into customers. Example for 4 touchpoints:
First TouchMiddle Touch 1Middle Touch 2Last Touch
0%0%0%100%

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Last touch paid only

If no paid touchpoint can be found, then the conversion will be attributed to No web touchpoint.
Description: All credit goes to the last paid touchpoint Converge observed in this customer journey. Use case: Check how channels contribute to converting prospects into customers. Example for 4 touchpoints:
First TouchMiddle Touch 1Middle Touch 2Last Touch
0%0%0%100%

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Linear

Description: Conversions are evenly attributed to all touchpoints in this customer journey. For example with 2 touchpoints each would receive 50% credit and with 3 touchpoints each would receive 33.3%. Use case: Check how channels contribute to the complete customer journey to conversion. Example for 4 touchpoints:
First TouchMiddle Touch 1Middle Touch 2Last Touch
25%25%25%25%

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Participation

It is normal for a participation model to show more attributed conversions than there are actual conversions because it will attribute the same conversion to multiple channels
It is possible for a single conversion to be attributed twice to the same channel if the customer has multiple touchpoints from different ads or campaigns within that channel
Description: The participation model gives 100% credit to every channel a user interacted with during their customer journey. If there are 2 channels, each gets 100% credit. If there are 3, each gets 100%. If a user interacts with multiple ads within the same channel, credit goes to the last touchpoint within that channel. Use case: Compare first-party attribution to in-platform attribution, which also attributes 100% credit to itself. Example for 4 touchpoints:
First TouchMiddle Touch 1Middle Touch 2Last Touch
100%100%100%100%

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J-shaped

Description: Conversions are attributed across all touchpoints but bias more towards the last touch. For 3 or more touchpoints, 60% of the credit is attributed to the last touch, 20% to the first touch, the remaining 20% is evenly distributed between the remaining touchpoints. For 2 touchpoints, 75% is credited to the last touch and 25% to the first touch. Use case: Use as your main model if you prefer Last touch attribution but want other touchpoints (especially first touch) to contribute. Example for 4 touchpoints:
First TouchMiddle Touch 1Middle Touch 2Last Touch
20%10%10%60%

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Inverse J-shaped

Description: Conversions are attributed across all touchpoints but bias more towards the first touch. For 3 or more touchpoints, 60% of the credit is attributed to the first touch, 20% to the last touch, the remaining 20% is evenly distributed between the remaining touchpoints. For 2 touchpoints, 75% is credited to the first touch and 25% to the last touch. Use case: Use as your main model if you prefer first touch attribution but want other touchpoints (especially last touch) to contribute. Example for 4 touchpoints:
First TouchMiddle Touch 1Middle Touch 2Last Touch
60%10%10%20%

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U-shaped

Description: Conversions are attributed across all touchpoints but bias more towards the first and last touches. Also known as Position-based. For 3 or more touchpoints, 40% of the credit is attributed to the first and last touchpoints. The remaining 20% is evenly distributed between the remaining touchpoints. For 2 touchpoints, 50% of the credit is attributed to both the first and last touchpoints. Use case: Check how channels contribute to the complete customer journey if you believe first and last touches are more important than other touches. Example for 4 touchpoints:
First TouchMiddle Touch 1Middle Touch 2Last Touch
40%10%10%40%

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Time decay

Description: Conversions are attributed across all touchpoints using exponential decay with a 7-day half-life, normalized to 100% across all touchpoints. Each touchpoint’s weight depends on the time elapsed between the touchpoint and conversion. The closer the touchpoint is to the conversion, the more credit it receives. For example, a touchpoint 7 days before conversion receives half the credit of a touchpoint on the same day as conversion. Use case: Check how channels contribute to the complete customer journey if you believe channels are less important when further from conversion. Example for 4 touchpoints:
First TouchMiddle Touch 1Middle Touch 2Last Touch
Days ago211470
Weight0.1250.250.51
Attribution6.7%13.3%26.7%53.3%

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Inverse time decay

Description: Conversions are attributed across all touchpoints using an inverse exponential decay with a 7-day half-life, normalized to 100% across all touchpoints. Each touchpoint’s weight depends on the time elapsed between the touchpoint and conversion. The earlier the touchpoint happened, the more credit it receives. For example, a touchpoint 7 days before conversion receives double the credit of a touchpoint on the same day as the conversion. Use case: Check how channels contribute to the complete customer journey if you believe that channels are more important if they are earlier in the buying journey. Example for 4 touchpoints:
First TouchMiddle Touch 1Middle Touch 2Last Touch
Days ago211470
Weight10.500.250.125
Attribution53.3%26.7%13.3%6.7%