Best practices for loading test data

[BrendaDavis1982]

We are migrating from one Marketo instance to another.  At this point, we have migrated all of our marketing activities plus assets, lists and reports into our new instance sandbox.  We have also synced Salesforce QA to our Marketo sandbox.  Our next step is to test everything in our Marketo sandbox environment. Does anyone have best practices for loading data into our Marketo sandbox or salesforce QA environment prior to testing all of our activities?

Thanks in advance!

[Darshil_Shah1 · Accepted solution]

Absolutely! Testing data is crucial for a smooth Marketo and Salesforce QA migration. Here are some best practices for loading data into your Marketo sandbox and Salesforce QA environment:

Data selection and volume:

• Marketo:
  • Leads:
    • Create a set of test leads across different segments, lifecycle stages, and campaigns. Avoid overloading the sandbox with too many leads.
    • Include test records with both positive and negative engagement histories for comprehensive testing.
• Salesforce QA:
  • Contacts/Leads:
    • Focus on contacts/leads mirroring the imported Marketo data, ensuring data integrity for integration testing. Include both active and inactive records.
  • Opportunities/Cases:
    • Select a sample of opportunities and cases in different stages to test sales workflows and reporting.
  • Custom Objects and Fields:
    • Ensure any custom objects and fields used in Marketo integrations are present and mapped correctly in Salesforce QA.

Data preparation and cleaning:

• Remove sensitive data:
  • Anonymize or scrub any PII data in both Marketo and Salesforce QA before loading.
• Validate data integrity:
  • Check for missing or invalid data values, formatting inconsistencies, and duplicate records before import.

Data loading methods:

• Marketo:
  • Most users would use the Import People to a Static list method for loading people to the Marketo. However, there's also an option to import people via Marketo's sync lead/bulk import API.
  • You can also select the Program while importing people to the list if you are testing the Marketo Program and synced Salesforce campaign.
• Salesforce QA:
  • Utilize Data Loader or Salesforce API for large datasets.
  • For Marketo integration testing, focus on syncing lead/contact data and ensuring field mapping accuracy.

Additional considerations:

• Monitor and troubleshoot:
  • Consider creating monitoring smart lists/reports to verify the testing. This could help you to reduce the manual effort of verifying the testing manually by checking each test record.
• Document your process:
  • Document the data selection, preparation, and loading steps for future reference and auditability.

[BrendaDavis1982]

Amazing! This is so helpful! Thank you so much.

[BrendaDavis1982]

One more question - is there typically a scheduled black out time (days or week) associated with data loading prior to migration?

[Darshil_Shah1]

Well, it depends on how conservative you are—some of my clients follow stringent guidelines regarding testing and migration even in the Sandbox environment. Then some directly build, test, and launch new stuff in the production environment where other stuff is already live. Below are some best practices or advice from my own experience:

Key Reasons for a Blackout Period:

• Minimize Disruptions: Prevents conflicts with active campaigns, lead scoring, or other marketing processes in the production environment.
• Thoroughly Test Migration: Allows for robust testing of migrated data, activities, and integrations without impacting live systems.
• Ensure Data Integrity: Protects against accidental overwrites or modifications to production data.

Typical Blackout Duration:

• Ranges from a few days to a week, depending on:
  • Data volume
  • Complexity of Migration
  • Testing requirements
  • Organizational preferences

Best Practices:

• Plan Early: Schedule the blackout well in advance to coordinate with stakeholders and minimize disruptions.
• Thorough Testing: Conduct comprehensive testing scenarios to identify any issues before going live.
• Monitor Performance: Track system performance during data loading and testing to address any bottlenecks.
• Document Procedures: Create detailed documentation of the blackout process for future reference.
• Data Cleaning: Allocate time for data cleansing and validation before loading to ensure data quality.

I hope this is helpful! Please let us know if you have any questions/comments!