3. Slate CRM Queries Best Practices

What is a query? I consider a query as a real-time, on-demand list.

Let’s suppose that there is a list of accepted students. It may be an accurate list when the list is created. As there are more newly admitted students, the list becomes outdated and it needs to be updated.

With queries, such repetitive jobs don’t have to be performed as queries only show an updated list of filtered students. To put it simply, the query will run through the filters every time you run the query– therefore, you don’t have to worry about its accuracy.

Another advantage of utilizing Slate Query is that you can change how the data appears in the query without making changes to the underlying data source.

For example, the Slate Form has “I paid the deposit” as one of the drop-down menus for students. This same data can be shown as “Paid” in the query for administrators.

Similarly, the date information can be customized to MM/dd/YYYY or YYYY-dd-MM depending on your preference without making changes to the source data.

When you know how Slate Queries can change the way you work and, what is more, you cannot go back to the spreadsheet-only business process.

Let’s dive into how you can be freed from repetitive work with Slate Queries.

Slate CRM Queries Best Practices
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Real case scenario- Benefits of using Slate Queries:

*Before the CRM (BC) and after the CRM adoption (AD)

  • BC: When international students are issued visas, students’ information such as education level, gender, date of birth, agent, etc were entered manually
  • AD: Export a Slate Query that has all the information automatically pulled from the student’s record. What staff needs to do is copy and paste the columns to the internal spreadsheet. By doing so, it can increase the data accuracy and efficiency.

  • BC: To see if the student meets 4 pre-registration steps, 4 columns were created and practitioners had to go through each row to see if the student completed all pre-registration steps.
  • AD: By utilizing filters or subquery, an export (column) can be created to automatically show if the student completed all of the steps or not. This makes it very easy and intuitive to follow up with students.

  • BC: To explain how the internship is related to the major, the office had a template and customized it for each student with internship information.
  • AD: An export that shows in the query as a column can be a concatenated with multiple fields. For example, if you want to say “The student will be working for {{employer}} for {{term}},” this full sentence can be automatically updated for each student/internship by having 4 fields:

    1. Literal field “The student will be working for
    2. Export {{employer}}
    3. Literal field “for
    4. Export {{term}}


    Scroll down to the “How to create Slate Queries” section to find a step-by-step guide on how to build Slate Queries.

  • BC: The commission information was entered manually every semester.
  • AD: An export (column) can be created to show “Commission required” if the agent information is not blank (= the student comes through the agent). 

  • AD: Quick Query is useful for getting simple lists which is a great to cross-check the number that you see in your working query.
  • AD: Historical data query can be pulled by adding a date field which is critical to see the trend, compare the numbers, etc. For example, by having the “application created date <1/1/2025”, all of the filtered applications that are created before 1/1/2025 will be retrieved.
  • BC: The list of scholars who completed the program was manually moved to a different tab
  • AD: The list of inactive scholars can be managed easily by using the sort button, or by creating two queries- one with active and the other with inactive scholars.
  • AD: The status of any field within the query can be updated to active/inactive easily with a toggle button- this is useful when the field is not applicable for this term but it may be in future terms. Instead of removing the field, by making it inactive, the user can be reminded to switch it on in the future.
  • BC: Based on the query, use the mail merge to mail out if needed
  • AD: The same query can be exported in virtually all formats including an Excel spreadsheet, CSV file, PDF report, or HTML report. It can be used to send out mailing as well.

How to create Slate Queries

Having a good understanding of how a query works and knowing how to use it can transform your work forever.

Building Slate Query may not seem easy at first but it’s not! As I explained at the beginning of this post, remember two things: with Slate Query, 1. you can pull the most up-to-date information and 2. how data appears can be customized without making changes to the source data.

As you can see, there is a lot you can do with Slate Queries and it will certainly free you from performing repetitive tasks.

Although this article covers technical features, the most important thing when it comes to building Slate Queries is the understanding of the business process on your campus and what fields you need to use.

If this post convinced you to start building your own query, one of the easiest and fastest ways to learn which fields you need to use is by having the technology team create the first query for your office.

From there, you can click the “Edit Query” button to see which exports and filters are used. By referring to this query, you will be able to build multiple queries— because the truth is that the same fields will be used again and again in the future. That’s the beauty of building queries.

One downside of Slate Query is that users need to manually export the query. What should you do if you would like to have the most updated list in your inbox automatically?

You can utilize Slate Reports to schedule which I am going to cover in my next post.

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