Consider a customer journey where a prospect clicks a Snapchat ad, then a Meta ad, then a Google Search ad before purchasing:
Here’s how Converge applies attribution to this journey:
Apply attribution window (e.g. 7 days): Filter out touchpoints outside the window. Since the Snapchat click happened on Day 1 (outside a 7-day window from the Day 10 conversion), only the Meta and Google clicks qualify.
Apply attribution model (e.g., Linear): Distribute credit across qualifying touchpoints. With a Linear model, the Meta and Google clicks each receive 50% credit.
Apply attribution mode (e.g., Click time): Assign when revenue credit is recorded. With Click time attribution, the $100 purchase is split: $50 credited to Day 5 (Meta click) and $50 to Day 10 (Google click).
* 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.
The attribution window determines how far back Converge looks for touchpoints that should receive credit for a conversion.Converge offers several fixed attribution window options: 1 day, 7 days, or 30 days.Example: A customer has touchpoints on January 1st, January 2nd, and January 3rd, then converts on January 4th.
With a 1-day attribution window, only the January 3rd touchpoint receives credit (it’s within 1 day of the conversion).
With a 7-day attribution window, all three touchpoints receive credit (they’re all within 7 days of the conversion).
The attribution mode determines when conversion and revenue credit are given. There are two modes:Click time: Credit is given at the touchpoint time. For example, if a user clicks a Facebook ad on January 1st and converts on January 5th, the conversion credit is attributed to January 1st.Conversion time: Credit is given at the transaction time. Using the same example, the conversion credit would be attributed to January 5th.
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.
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:
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:
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:
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:
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:
If no top of funnel touchpoints are found, the model will fallback to a linear distribution across all touchpoints. If no touchpoints can be found at all, then the conversion will be attributed to No web touchpoint.
Description: Conversions are evenly attributed to all qualifying paid touchpoints in the customer journey, based on channel and campaign name.Includes:
Paid touchpoints from these channels: paid search, paid social, paid video, paid shopping, and display.
Only touchpoints whose campaign name does not indicate “brand” (unless “non brand” or “NB” is present).
Does not include:
Any unpaid touchpoints (e.g., organic, direct).
Paid touchpoints with a campaign name containing “brand”, “brd”, or “SR” (unless the phrase includes “non brand” or “NB”).
For example, with 2 qualifying touchpoints, each would receive 50% credit, and with 3 qualifying touchpoints each would receive 33.3%.Use case: Understand how top-of-funnel paid channels drive conversions while excluding brand-related touchpoints.Example for 5 touchpoints:
First Touch
Middle Touch 1
Middle Touch 2
Middle Touch 3
Last Touch
Campaign Name
Summer Promo Search
Brand Awareness Search
Social Media Blast
Organic Blog Visit
Brand Display
Paid
Yes
Yes
Yes
No
Yes
Branded
No
Yes
No
No
Yes
Attribution
50%
0%
50%
0%
0%
Only paid, non-branded touchpoints are counted for attribution.
In this example:
“Summer Promo Search” and “Social Media Blast” are both paid and non-branded, so each receives 50% of the credit.
“Brand Awareness Search” and “Brand Display” are excluded from attribution because their campaign names contain brand-related terms (“brand”).
“Organic Blog Visit” is not a paid touchpoint, so it gets 0%.
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
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:
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:
If no paid touchpoint can be found, then the conversion will be attributed to No web touchpoint.
Description: Conversions are attributed across all paid touchpoints but bias more towards the last paid touch.For 3 or more paid touchpoints, 60% of the credit is attributed to the last paid touch, 20% to the first paid touch, the remaining 20% is evenly distributed between the remaining paid touchpoints.
For 2 paid touchpoints, 75% is credited to the last paid touch and 25% to the first paid touch.Use case: Use as your main model if you prefer last touch paid attribution but want other paid touchpoints (especially first touch paid) to contribute.Example for 4 touchpoints:
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:
If no paid touchpoint can be found, then the conversion will be attributed to No web touchpoint.
Description: Conversions are attributed across all paid touchpoints but bias more towards the first paid touch.For 3 or more paid touchpoints, 60% of the credit is attributed to the first paid touch, 20% to the last paid touch, the remaining 20% is evenly distributed between the remaining paid touchpoints.
For 2 paid touchpoints, 75% is credited to the first paid touch and 25% to the last paid touch.Use case: Use as your main model if you prefer first touch paid attribution but want other paid touchpoints (especially last touch paid) to contribute.Example for 4 touchpoints:
Description: Conversions are attributed across all touchpoints but bias more toward 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:
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 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:
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 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:
