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Customer Data Feed (CDF) - Use Case to Support Implementation

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Level 2

As we continue to mature the Audience Manager product with my organization, there was a consideration to use a Customer Data Feed (CDF) from Audience Manager into our central data lake.  As I am starting my discovery and reading about CDF, I am intrigued about how best to communicate it to our stakeholders to get their support for this effort.   With the additional information Audience Manager is providing for each ID (on an hourly basis) in a CDF, what are the best way to sell CDF to our stakeholders?   What sort of additional business insights can they gain?  Why would various IT and non-IT team be onboarding with supporting another file process?


Please feel free to share any thoughts you have on CDF....good, bad, and anything in between.  I would love to hear the wide spectrum.  Thanks in advance for your time!

1 Accepted Solution

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Correct answer by
Employee Advisor

Hello @JL143 ,

 

Please find the my inline inputs below:

  • It contains the Marketing Cloud ID (MCID) which can be used to analyze the behavior of anonymous site visitors, plus it includes the timestamps. How would you be able to use MCID to identify your anonymous users?
    • In AAM, MCID has associated UUID. So, all MCID corresponds to one device which can be counted as Anonymous users.

 

  • Use this information to understand the marketing touch points that precede a person's qualification into a trait. Can you provide an example of how this is done with CDF data?
    • When we are talking about Person, we are considering authenticated profiles. So, for one authenticated profile you get all the traits and segments returned in these logs which can be first round of check. Alternatively, you can build more intelligence on your side using scripts or any prebuilt tools that can pull all the server calls per authenticated profile basis which will further provide more insights on the behavior of the user.

 

  • Knowing the effectiveness of our marketing touch points will allow us to optimize our marketing spend. Can you elaborate on how this can be achieve with CDF File?
    •  To know all the touch per server call or per profile or per device, we have Referer filed in CDF logs, this might give insights there. Apart from this, I feel qualified traits columns is best to analyse all the inbound channels provided we have traits in AAM for each of those channels.

 

Regards

Ankita Sodhi

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3 Replies

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Employee Advisor

Hello @JL143 ,

 

A few points:

  • To analyze this raw data in order to optimize the digital marketing efforts.
  • It contains the Marketing Cloud ID (MCID) which can be used to analyze the behavior of anonymous site visitors, plus it includes the timestamps.
  • Use this information to understand the marketing touch points that precede a person's qualification into a trait.
  • Knowing the effectiveness of our marketing touch points will allow us to optimize our marketing spend.

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Level 2

Thanks for providing your expertise.   Some follow-up questions came to mind.

 

  • It contains the Marketing Cloud ID (MCID) which can be used to analyze the behavior of anonymous site visitors, plus it includes the timestamps.  How would you be able to use MCID to identify your anonymous users? 
  • Use this information to understand the marketing touch points that precede a person's qualification into a trait.  Can you provide an example of how this is done with CDF data?
  • Knowing the effectiveness of our marketing touch points will allow us to optimize our marketing spend.  Can you elaborate on how this can be achieve with CDF File?

 

 

Avatar

Correct answer by
Employee Advisor

Hello @JL143 ,

 

Please find the my inline inputs below:

  • It contains the Marketing Cloud ID (MCID) which can be used to analyze the behavior of anonymous site visitors, plus it includes the timestamps. How would you be able to use MCID to identify your anonymous users?
    • In AAM, MCID has associated UUID. So, all MCID corresponds to one device which can be counted as Anonymous users.

 

  • Use this information to understand the marketing touch points that precede a person's qualification into a trait. Can you provide an example of how this is done with CDF data?
    • When we are talking about Person, we are considering authenticated profiles. So, for one authenticated profile you get all the traits and segments returned in these logs which can be first round of check. Alternatively, you can build more intelligence on your side using scripts or any prebuilt tools that can pull all the server calls per authenticated profile basis which will further provide more insights on the behavior of the user.

 

  • Knowing the effectiveness of our marketing touch points will allow us to optimize our marketing spend. Can you elaborate on how this can be achieve with CDF File?
    •  To know all the touch per server call or per profile or per device, we have Referer filed in CDF logs, this might give insights there. Apart from this, I feel qualified traits columns is best to analyse all the inbound channels provided we have traits in AAM for each of those channels.

 

Regards

Ankita Sodhi