Countries Segment Screenshot.JPG

Getting the Most Out of Your Data with Segments

Vladislav_Vagn1
Level 5 - Community Advisor Level 5 - Community Advisor
Level 5 - Community Advisor

Segmentations in Marketo are a powerful feature to organize and sort your database based on data already available to you.

 

One tip I wanted to share today is how you can use segmentations in Marketo to group multiple fields that have the same or similar data and create segmentations using those data points. This will allow you to simplify your workflow when building smart campaigns and smart lists and reduce the potential for error later on.

 

The problem statement:

You might have multiple fields in your instance that contain essentially the same information. Geographical data is one example that I have seen from instance to instance. You might have a field for Country (Marketo field), Inferred Country (Marketo field), Billing Country (Syncs from SFDC), and other country fields from your data appending services. Moving data from one field to another might not be as simple due to restricted picklists, different ways of spelling the same thing, varying data quality depending on source, data governance rules specific to an organization, etc.

 

If you constantly use these fields in your smart campaigns or smart lists, you might be finding that you are dragging all of those fields into your filters, populating them, and then configuring your field logic. Not a hard task but definitely time-consuming. Wouldn’t it be easier if you had just one filter you could use that incorporated all of those fields?

 

The solution:

Using segmentations you can do just that!

I will use the example I provided earlier with the country fields. If I wanted to simplify that process, I would begin with creating a new segmentation or editing the current one I have for Countries.

 

Step 1:

Once you have the segmentation, the first thing you want to do is identify the fields that you want to “aggregate”.

 

In my example I will have:

  • Country
  • Inferred Country
  • Billing Country
  • DiscoverOrg Person Country

All four fields could contain the same information or some of them could be blank while the others are populated.

 

Step 2:

The next thing you will want to do is determine the segments you want to have within the segmentation.

 

To keep the example short, I will pick three segments:

  • USA
  • Canada
  • United Kingdom

Countries Segment Screenshot.JPGNote: I like to number my segments based on the order I have them in the setup so that it doesn’t sort them alphabetically and I can see the priority of them at a glance.

 

Step 3:

Once you have created your segments and determined the order within the segmentation (remember the order is important!) you can begin bringing in the filters from step 1 and populating them accordingly.

 

USA Filter Logic Example.JPG

Note: Be sure to change your filter logic from “ALL” to “ANY”

 

Step 4:

Repeat step 3 for all the other segments from step 2.

 

Once you are done, you will have a segmentation that is more robust than any one of those fields alone.

 

If I was sending an email to a US-only audience, here is what my smart list looked like before we created this segment:

example email send - old way.pngNotice that each field has their own accepted picklist values for country. The filter logic is not fun to keep up with either.

 

After building this segment, I can create the same list but quicker and with less potential errors using a segment filter.

example email send - new way.png

 

The next time you are building a smart list to send an email to an audience in a specific country, you can use just one filter – the Countries segmentation – instead of having to remember all the fields that might contain that information, dragging all of them over, and then setting up the filter logic.

 

And remember, this can be useful for a wide variety of fields, not just Country based fields. I have seen instances have these kinds of segments for Industry fields, Job Title fields, Job Level fields, and more.

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