Attribution model - the weighted number of conversions - GA

[Tormar]

Hi,

1.Can someone explain me with an example what is "The weighted number of conversions under the custom selected attribution model"? How Analytics calculate it?

2. If I increase e.g social source for 1.4 in my attribution model, my organic or direct source are loosing that weighted number of conversions. Could it be because of organic or direct getting lower credit, or for some other reason?

Ty. Br.

[Tormar]

Thank you.

But, hm, I don't know. I'm using a data driven attribution model with 12 channels.

If I increase boost for 1.4, my boost weighted conversions will grow from 8 to 8.50.

How can I see, how much real conversions I will get with that change?

[TrentonGreener]

Hey Tormar,

I saw that you posted this question a few times here in various Google Analytics forums, but didn't get any help. Let's see if we can't get you all sorted out.

Your questions as I understand it

1. You want an example to better help you understand 'weighted number of conversions' under the custom selected attribution model within Google Analytic's Model Comparison Tool.
2. You want to know how Google Analytics calculates this value.
3. You want to know if when you increase the value of social sources in your attribution model, why you then see a lower value for organic or direct.

I'm going to attempt to tackle these three, but if you feel I did not adequately understand your question, please feel free to add more information or correct me.

Before we get started
I think it's important to first address that all attribution models within Google Analytic's Model Comparison Tool are a zero-sum game. By that I mean that there is an inverse correlation between each facet of each individual attribution model.
Stated differently, each conversion (or goal, or transaction, etc.) is only one conversion. While the linear attribution model disperses the 'value' of a conversion equally across all interactions, the summation of all of these interaction's value will always = 1.

Ok, now that we've covered that let's jump into it.

1. I think you're attempting to create a custom attribution model. When doing so, you will need to first determine what existing model you want to base your custom model from, then you will define the value you want to give to each facet. I cannot possibly go into all the possible combinations here, but here's a starting point to diving into the process.
   The weight you're giving each facet is the percentage (expressed in decimal form) of the total (which is 1) that facet will receive. In a linear attribution model with 5 interactions each interaction would receive 20% (0.2) of the credit for each conversion.
   Circling back to your question, the number of conversions when viewing a report is the summation of all attributed values across the defined timeline & parameters.
2. I explained this a bit in #1, but Google Analytics is taking your defined values for each facet & distributing value aross them proportionally to the values you defined in the custom attribution model.
3. As I mentioned above, this is a zero-sum game, or an inverse correlation. When you increase one facet's value (in your example, social) the other values must decrease proportionally.

I hope this helps. Let me know if you need any further help or if this answered your question!

Regards,
Trenton