The Appeals Dataset
  • 16 Jan 2026
  • Dark
    Light
  • PDF

The Appeals Dataset

  • Dark
    Light
  • PDF

Article summary

Slate for Advancement databases are provisioned with an Appeals dataset, in which each record represents an appeal.

When creating gifts on a record, use the autosuggest box to find the appeal you want to use.

📖 Appeals

Autosuggest_Appeals.png

Creating an appeals dataset

Advancement offices have historically created prompt lists to store appeals data. However, if your process involves tracking a lot of data within each appeal, storing all that data in a prompt list can be cumbersome. To allow for the setting of additional data points and to improve reporting, you can now use an appeal dataset to store the appeal data.

If your institution has yet to set up appeals data in your database, setup is as simple as setting up a fund (another type of dataset record):

  1. Go to Database → Datasets.

  2. Select Insert.

  3. Configure the following settings:

    • Name: Give your appeal a name, like Appeal.

    • Type: Enter gift_appeal

      Insert_New_Dataset_Record.png

  4. Select Save.

  5. Either manually or via import, add records to the dataset.

Migrating existing appeals prompts to your new appeals dataset

For institutions already using appeals prompts, the appeals dataset is all or nothing: if a dataset with the gift_appeal type exists, existing appeal prompts will not be used.

Since your institution may already have gifts that use the appeals prompt list, we've created a query that you can import into your database that walks you through the migration process.

Importing the migration query

🔔 Important!

Follow these steps in your test environment first to confirm the effects on your individual database before attempting in a production environment.

To import the query:

  1. Copy the following Suitcase ID:

    a358facd-4f34-0b66-ea06-96b5c906238f@slate
  2. Go to Database → Suitcase Import.

  3. Paste the ID.

  4. Select Import.

Migrating the prompts

💡 You can also find the following steps in the Suitcase query’s description in Slate.

To migrate appeals prompts:

  1. Go to Database → Datasets.

  2. Select Insert.

  3. Configure the following settings:

    • Name: Staging Appeal

      Type: staging_appeal

  4. Select Save.

  5. Go to the query you imported with Suitcase.

  6. Select Run Query. The following occurs:

    • The query recreates all existing gift_appeal prompts as records in the new dataset.

    • The name of the record is set to the value of the prompt, and the active status of the record is set to the active status of the prompt.

    • If the prompt already exists based on the ID, it will be skipped—no need to worry if you accidentally run it more than once.

  7. Perform any additional adjustments to the records either manually or via import.

  8. When you're ready to transition to using the dataset instead of prompts, update the appeal dataset type to gift_appeal (replacing staging_appeal).

Undoing the migration

If you followed the preceding steps and decide you aren't quite ready yet, you can undo the process:

  1. In the new appeal dataset, set the type back to staging_appeal.

  2. Use your appeal prompts.

The Suitcase process does not remove these prompts.

Housekeeping

Once you've migrated your appeals prompts to the new appeals dataset, there are a few things to do to enjoy its benefits fully:

  1. Create a local query base for the appeals dataset. This allows you to create exports and filters.

  2. Create the local exports and filters for Lookup and Partial Match, so the dataset appears in search results like other records.

  3. Refresh the Configurable Joins library (Database → Refresh Configurable Joins Library) so that joins for the appeals dataset appear. This also happens automatically overnight.

Mapping to appeals

In imports and forms, you may continue to use value mappings as before, but you'll also find an added destinations of Appeal - Key to which you may send the key of the dataset record.

Destination_-_Appeal_Key.png


Was this article helpful?