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Hi SM community - happy to submit my first thread here!

 

I’ve created a dashboard on Looker Studio to display :

  • Dimensions: Date, Market (based on page ID)
  • Metrics: Reach, Engagement, ER

However, it would be interesting to differentiate what goes on regular media campaigns and what is post boosting. Is there a dimension that I’m unaware of that could do this trick? Or any other work-around you may be using?

 

Best,

Tomás

​@tsoares Hi there!

The first thing that comes to mind is leveraging CASE functions in Looker Studio in custom fields to build out and categorize your ads, as long as you have a naming convention that supports your efforts.

For example, lets say you have three campaigns:

  • Campaign A (a post boost) called MARKET1--CAMPAIGNA--BOOST--$300
  • Campaign B (regular media campaign) called MARKET1--CAMPAIGNB--ADVERT--$1000
  • Campaign C (another post boost) called MARKET2--CAMPAIGNC--BOOST--$350

What you could do is leverage a CASE function in the following way:

CASE
WHEN REGEXP_CONTAINS(CAMPAIGN,'BOOST') THEN 'Boosts'
WHEN REGEXP_CONTAINS(CAMPAIGN,'ADVERT') THEN 'Marketing Campaigns'
ELSE CAMPAIGN
END

The function looks at the field ‘CAMPAIGN’ in your source data, then reads the campaign name to find ‘BOOST’ in your naming convention. Every time it finds it, it categorizes that data as ‘Boosts’. Same goes for ‘ADVERT’ if you use that for general marketing campaigns. When you save the custom field, you then get a field you can use in a table with cleaned up, categorized data. Here’s a live example I have in a client’s dashboard for audiences:
 

‘Audience Targeting’ is a custom field based on the naming conventions in ‘Audience Name’

Here’s the code I used for my CASE function:

CASE
WHEN REGEXP_CONTAINS(Audience Name,"CSIS-0001|001") AND REGEXP_CONTAINS(Audience Name,"GF") AND REGEXP_CONTAINS(Audience Name,"IG") THEN "Main Targets - Instagram - Female"
WHEN REGEXP_CONTAINS(Audience Name,"CSIS-0001|001") AND REGEXP_CONTAINS(Audience Name,"GM") AND REGEXP_CONTAINS(Audience Name,"IG") THEN "Main Targets - Instagram - Male"
WHEN REGEXP_CONTAINS(Audience Name,"CSIS-0001|001") AND REGEXP_CONTAINS(Audience Name,"GF") AND REGEXP_CONTAINS(Audience Name,"FB") THEN "Main Targets - Facebook - Female"
WHEN REGEXP_CONTAINS(Audience Name,"CSIS-0001|001") AND REGEXP_CONTAINS(Audience Name,"GM") AND REGEXP_CONTAINS(Audience Name,"FB") THEN "Main Targets - Facebook - Male"
WHEN REGEXP_CONTAINS(Audience Name,"CSIS-0001|001") AND REGEXP_CONTAINS(Audience Name,"GA") AND REGEXP_CONTAINS(Audience Name,"FB") THEN "Main Targets - Facebook - Blended (alumni panel)"
WHEN REGEXP_CONTAINS(Audience Name,"CSIS-0001|001") AND REGEXP_CONTAINS(Audience Name,"GA") AND REGEXP_CONTAINS(Audience Name,"IG") THEN "Main Targets - Instagram - Blended (alumni panel)"
ELSE "Other"
END


While my naming convention is a bit long and not fully readable in the table above for ‘Audience Name’, I’m able to pull out key data from that using CASE function, and I can recategorize things to look like this:
 

Easier to read, easier for the client to digest, and easier to pull out insights for our campaigns based on specific audiences. 

 

For your example, you can use it for boosts, but once you explore the power of CASE functions, your uses will be limitless…. then you move on to building a data warehouse and recategorizing whole data sources, and your life will be filled with SQL 😅

Let me know if you find this helpful, or if you need anything else!

Hello ​@gcfmineo , thank you for your detailed answer. We went back to our Media Agency and realized (thankfully) they had a naming convention in place to differentiate post boosting from regular media ads campaigns.

 

In the meantime, I realized I could do this with regular filters, but looking at the examples you provided with the Case function I realize it is way more powerful.

 

Once again, thank you for taking the time and helping!

Tomás

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