Examples of Advanced segments

Here are some examples of advanced segments to help you understand how you can combine attributes from various filters to create the required segment.

For more information, see the following topics:

1. High value customers

In this example, we are creating a segment for high value users.

Use the following attributes to create the segment:

  • User > Lifetime activity > Lifetime revenue greater than or equal to 1000
  • User > Lifetime activity > Lifetime number of orders greater than or equal to 10

examples_adv_highvalue_2.png

2. Customers with category interest and no purchase

In this example, we are creating a segment for users who viewed items from a particular category or added items to their carts from the same category but did not purchase in the past 2 months.

Use the following attributes to create the segment:

  • Catalog activity: add_to_cart within past 2 months for category Fiction > Thrillers > General
  • Catalog activity: view atleast 5 times within past 2 months for category Fiction > Thrillers > General
  • Catalog activity: no purchase within past 2 months

examples_adv_category_visit.png

3. Inactive customers

In this example, we are creating a segment for users who have not viewed any items or not added items to their carts in the last 3 months and who have not purchased any items within the past 1 year.

Use the following attributes to create the segment:

  • Catalog activity: add_to_cart within past 3 months
  • Catalog activity: view within past 3 months 
  • Catalog activity: purchase within past 12 months

examples_adv_inactive.png

4. High value users at risk of churn

In this example, we are creating a segment for high value users who are at risk of churn and have no recent activity.

Use the following attributes to create the segment:

  • Predictive score: churn is greater than or equal to 50%.
  • Member of segment: High Value Customers (segment created in example 1)
  • Recent activity: no view events in past 1 month
  • Recent activity: no purchase events in past 1 month

examples_adv_highvalue_churn.png

5. Users with no engagement

In this example, we are creating a segment for users who are at risk of churn and have not engaged with recent subscription renewal reminder emails.

Use the following attributes to create the segment:

  • Predictive score: churn is greater than or equal to 50%.
  • Messaging:
    • no click
    • email channel
    • for the Renewal reminder campaign for the specific trigger and specific template
    • timeline is within past 2 days.

examples_adv_atrisk_noengagement.png

6. Advanced nested grouping to search for specific customers

In this example, we see how to create a segment to query for customers who browsed books related to East Asian Philosophy, but did not buy any. The product catalog does not have an “East Asian Philosophy” category, so it is not possible to use a basic segment for this query. The catalog does have the Philosophy > Zen and the Philosophy > Taoism categories and the books related to East Asian Philosophy are part of one of these categories.

So let's now build the Abandoned Browse East Asian Philosophy segment to find customers who browsed books from either the Philosophy > Zen or the Philosophy > Taoism category, but did not buy any.

Step 1: We are looking for customers who abandoned browsing in the category Philosophy > Zen or the category Philosophy > Taoism.

To achieve this, we must set the outermost grouping to OR.

adv_seg_step1.png

Step 2: Search for customers who abandoned browsing in the Philosophy > Zen category.

To achieve this, we must search for customers who satisfy both the following conditions:

  • Customers viewed an item in the Philosophy > Zen catalog within the past 7 days.
  • Customers did not buy an item in the Philosophy > Zen catalog within the past 7 days.

  1. Click Add Grouping within the outer OR grouping and add an AND grouping.

    adv_seg_step2.png

  2. Click Add Condition > Catalog Activity.

    adv_seg_step3.png

  3.  Set the condition to select customers who viewed an item in Philosophy > Zen within the past 7 days.

    adv_seg_step4.png

  4. Click Add Grouping within the added AND grouping and add another AND grouping.

    adv_seg_step5.png

  5. Change the newly created grouping from AND to NOT.

    adv_seg_step6.png

  6. In the NOT grouping, click Add Condition > Catalog Activity and set the condition to select customers who bought an item in Philosophy > Zen within the past 7 days.

    adv_seg_step7.png

Step 3: Search for customers who abandoned browsing in the Philosophy > Taoism category.

To achieve this, we must search for customers who satisfy both the following conditions:

  • Customers viewed an item in the Philosophy > Taoism catalog within the past 7 days.
  • Customers did not buy an item in the Philosophy > Taoism catalog within the past 7 days.

  1. Click Add Grouping within the outer OR grouping and add an AND grouping.

    adv_seg_step9.png

  2. Click Add Condition > Catalog Activity and set the condition to select customers who viewed an item in Philosophy > Taoism within the past 7 days.

    adv_seg_step10.png

  3. Click Add Grouping within the added AND grouping and add another AND grouping. Change the newly created grouping from AND to NOT.

    adv_seg_step11.png

  4. In the NOT grouping, click Add Condition > Catalog Activity and set the condition to select customers who bought an item in Philosophy > Taoism within the past 7 days.

    adv_seg_step12.png

The Abandoned Browse East Asian Philosophy segment is now created. The right side of the segment editor has a query summary.

adv_segment_abandonbrowse.png

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