Data Cleanup

Verify contact data quality

Remember, data cleanup can be a complex process, and the specific steps can vary depending on the nature of your data and the purpose of your analysis:

  • Define the scope and identify the datasets needing cleaning and the specific issues to address.
  • Backup data before starting the cleanup process.
  • Standardize and normalize data entries to ensure consistency in data.
  • Remove duplicates to avoid skewing data and leading to inaccurate analysis.
  • Tag invalid and out-of-the-norm data.
  • Handle missing values depending on the nature of data and analysis; this could involve imputation, deletion, or leaving them as is.
  • Validate accuracy and cross-check data samples with reliable sources.
  • Check for outliers that can significantly impact reporting.
  • Keep a record of all the changes made during the cleanup process.
  • Verify the final dataset once the cleanup process is complete.
  • Report the findings for each of the above steps.
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Data Management

Update contact data

This is an essential checklist and might need to be customized based on your specific needs and circumstances:

  • Identify all the sources from where you are getting your contact and account data.
  • Ensure you have a standardized process for collecting, entering and validating the data.
  • Verify and validate new data to ensure that it is accurate and relevant.
  • Check for and remove any new duplicate records.
  • Update data regularly to ensure it remains accurate and up-to-date.
  • Segment data based on relevant business categories.
  • Generate accurate target accounts and lead personas.
  • Generate leads from industry events you want to attend and target them before the events.
  • Monitor and control contact and account data activities.

Manage your data >>

Data Operations

lead acquisition and qualification

This is an essential checklist and might need to be customized based on your specific needs and circumstances:

  • Configure all sales and marketing platforms for data operations.
  • Create and manage the process for deleting/archiving data when it’s no longer needed or requested by the contact.
  • Create and manage the process for handling new contact and account data verification.
  • Create and manage the process for lead generation.
  • Create and manage the data update process.
  • Ensure that data entry is done accurately and consistently across all platforms.
  • Consolidate data between all sales and marketing platforms.
  • Analyze data regularly to gain insights about your contacts and accounts. This could help in making informed decisions.
  • Perform data projects to improve data quality and utility in the sales and marketing platforms.
  • Report on data activities.
Personalize your data Ops >>

Don't lose opportunities with data operations.

How much revenue and marketing cost could you be losing?