Use cases

Based on the SurveyMonkey Apply connector operations provided, here are some use case examples that showcase how this connector can be integrated into Tray workflows: In each of these examples, data transformation and mapping would likely be necessary between steps to ensure that the data is in the correct format for each operation. The exact transformations would depend on the specific data structures used in your SurveyMonkey Apply instance and any external systems you're integrating with.

Automated Application Processing

Objective: Streamline the process of reviewing and managing applications in SurveyMonkey Apply. Steps:

  1. Trigger: Use a Scheduled Trigger to run the workflow daily.
  2. Fetch Applications: Use the list_applications operation to retrieve all new applications.
  3. Process Applications: Loop through each application: - Use the list_application_tasks operation to get tasks for each application. - Use the get_application_task operation to retrieve details of each task.
  4. AI-Powered Analysis: Use the Merlin Functions connector with the classify text operation to categorize applications based on their content.
  5. Data Masking: Before sending sensitive applicant data to AI services, use the Merlin Guardian mask data operation to protect personal information.
  6. Update Applications: Based on the AI classification, use the update_application operation to update the application status or add notes.

This workflow demonstrates how to automate the initial screening of applications, using AI to assist in the process while ensuring data privacy.

Multi-Program Application Management

Objective: Manage applications across multiple programs and synchronize data with external systems.

Steps:

  1. Trigger: Use a Webhook Trigger to start the workflow when a new application is submitted.
  2. Fetch Program Data: Use the list_programs operation to get a list of all active programs.
  3. Create Application: Use the create_application operation to create a new application in the appropriate program.
  4. Fetch Tasks: Use the list_application_tasks operation to retrieve tasks associated with the new application.
  5. Process Files: For each task, use the list_task_files_ddl and get_task_file operations to download and process any attached files.
  6. AI-Powered Document Analysis: Use the Merlin Extract connector with the extract text operation to extract key information from uploaded documents.
  7. Data Transformation: Use JSON Transformer or Data Mapper to structure the extracted data for your target system.
  8. External System Sync: Use appropriate connectors (e.g., Salesforce, HubSpot) to sync the application data with your CRM or other systems.

This workflow showcases how to manage applications across multiple programs and integrate with external systems, utilizing AI for document processing.

Automated User Onboarding

Objective: Streamline the process of creating new users in SurveyMonkey Apply and associated systems.

Steps:

  1. Trigger: Use an HTTP Trigger to receive new user data from an external system.
  2. Data Validation: Use a Boolean Condition to verify if all required fields are present.
  3. Create User: Use the create_user operation to add the new user to SurveyMonkey Apply.
  4. Fetch Organizations: Use the list_organizations operation to get a list of available organizations.
  5. AI-Powered Organization Matching: Use the Merlin Functions connector with the generate text operation to suggest the most appropriate organization for the user based on their profile.
  6. Update User: Use the raw_http_request operation to assign the user to the suggested organization (assuming there's an API endpoint for this).
  7. Welcome Email: Use an email connector (e.g., Gmail, SendGrid) to send a welcome email to the new user with their account details.

This workflow demonstrates how to automate user creation and onboarding, using AI to assist in organizational placement.

Application Stage Progression Analysis

Objective: Analyze and report on how applications progress through different stages.

Steps:

  1. Trigger: Use a Scheduled Trigger to run the analysis weekly.
  2. Fetch Stages: Use the list_stages operation to get all stages in the application process.
  3. Fetch Applications: Use the list_applications operation to get all applications.
  4. Data Processing: Use Loop and Boolean Condition connectors to categorize applications by their current stage.
  5. AI-Powered Insight Generation: Use the OpenAI connector to generate insights about application progression trends.
  6. Data Visualization: Use a BI tool connector (e.g., Tableau, Power BI) to create visualizations of the stage progression data.
  7. Report Distribution: Use a communication connector (e.g., Slack, Microsoft Teams) to distribute the analysis report to stakeholders.

This workflow showcases how to perform regular analysis of application data, leveraging AI for insight generation and integrating with BI tools for reporting.

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