Preparing Your Sandbox for CRM Analytics Testing

In this post, I will discuss the benefits of utilising a Sandbox for CRM analytics projects, and I’ll also explain how to set it up for better testing.

Testing CRM analytics in a sandbox environment is crucial for several reasons. Understanding its significance can help emphasise the importance of proper preparation.

By setting up a sandbox environment specifically for testing CRM analytics, organisations can create a controlled and isolated space where developers, data analysts, and other stakeholders can experiment, validate, and refine analytics models without any risk to live customer data or business processes. This separation ensures that any issues or unexpected outcomes can be addressed and resolved before deploying changes to the production environment.

Additionally, testing in a sandbox environment allows for thorough validation of analytics algorithms, data pipelines, and integration with other systems or data sources. It provides an opportunity to simulate real-world scenarios and assess the performance and accuracy of analytics insights under different conditions. The initial step after choosing to develop in a Sandbox involves considering a full Sandbox copy, as it provides access to the most recent version of production data for working purposes.

The initial step after choosing to develop in a Sandbox involves considering a full Sandbox copy, as it provides access to the most recent version of production data for working purposes.

Here’s a step-by-step guide on how to set up a sandbox for effective testing:

1. Access Analytics Studio: Begin by logging into the sandbox and navigating to Analytics Studio. Here, you will have the tools needed to create apps and datasets crucial for our testing.
2. Create a Sandbox App: To maintain organisation, it’s advisable to create a dedicated app to store all relevant datasets. Simply go to Analytics Studio, click on Create, select App, choose Blank App, and name your app accordingly.
3. Establish Local Output Connection: Your system administrator should create a Local Output Connection. This connection grants access to local Salesforce objects necessary for testing purposes.
4. Set Permissions: Ensure that the CRM analytics profile has appropriate permissions, especially for Salesforce objects with Master or Lookup relationships with custom objects. This ensures seamless data access during testing.
5. Consider User Roles: If creating campaigns data is part of your testing scope, the user creating the Local Output Connection should have Marketing user privileges.

Loading Data into Salesforce Objects through Recipe

Prepare Test Data:

Identify mandatory fields such as Account Name for Account Object and any related lookup relationships. Prepare test data accordingly, ensuring completeness and accuracy.

Create Dataset:

In Analytics Studio, navigate to Create > Dataset. Choose the CSV file containing your prepared test data, select the appropriate app, and give your dataset a descriptive name. Define each field type (Dimension, Date, or Measure) and proceed to upload the file.

Creating a Recipe:

In Data Manager, under Recipes, create a new recipe. Add the input data by selecting the dataset created earlier. Define the output node with details like connection name, object name, and operation (Insert/Update/Upsert). Map all fields accordingly.

Run the Recipe:

Once configured, save the recipe, and initiate the run. Monitor the progress in the Job Monitor queue. Upon successful completion, the data will be loaded into the Account object.

In a similar way, you can load data into any object like Case, Campaign, Contact, or custom objects.

Testing with Ease

With this setup, testers can effortlessly create test files, load them into the dataset, and run the recipe to validate their data. This streamlined process ensures efficient CRM analytics testing within the sandbox environment.

Few Tips and Hints

• Ensure that when creating datasets for test data, designate the related fields type as Dimension, Measure, or Date. This prevents any issues during the mapping process when writing data back into Salesforce Objects.
• Ensure data objects are refreshed each time data is loaded.
• Regularly back up your data to prevent loss.
• Safeguard your metadata by downloading JSON files as backups.

In general, it’s a good idea to write down every step that you take when developing. CRM Analytics has tools to help with this, like description fields and version history. Whether you’re working in production or sandbox, clear documentation makes it easier to manage and support CRM Analytics for your team.

By following these steps, your sandbox environment will be adequately prepared for comprehensive CRM analytics testing, facilitating accurate insights and informed decision-making.