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Data Reintegration is the process of layering modified data over the original dataset; or combining data from various sources  into valuable, actionable information centralized under one database.


Data Reintegration infographic

Data integration processes help the user cleanse, dedupe, monitor, and transform data, so the information is consistent and trustworthy. The primary goals are to:

  • Keep critical data points unchanged
  • Add data points via appended information
  • Modify outdated data points from data decay

Why Data Reintegration? Why not just process your data in the CRM?

Processing data within your CRM is not realistic for large-scale data operations, and will likely impact the quality of your existing CRM data negatively. There are two reasons for this:

  1. API Limits: most CRM’s do not provide a sufficient number of API calls needed to do a full data refresh
  2. Speed: API-based access is a slow process when working on a large dataset

To run a proper data integration, the existing data set must be extracted from the CRM into a data sandbox.

Planning Stage for Data Reintegration

Here are the necessary steps to properly execute a data reintegration:

Initial Pull:

Include as many data points as possible; reintegration planning begins when the initial dataset is pulled from the CRM

  • Most data cleansing operations have a better chance of success when more fields are pulled
  • Example: even when appending Account level data, including Contact or Lead data can help the process. An email associated with a particular contact can provide the website of the company via the email domain.
    • Then, that website can be used to verify the company name to better match firmographic data on the company.

Include All Required Unique ID’s:

If your data records include both Account and Contact data, include both the Unique Record ID for Account and Contact.

Do Not Forget Date Values: 

It is a common practice to consider old data “unusable” because of the rate at which data decays (ex: a former company that went out of business).

  • Look at the original “created date” at the end of a data refresh process to help make decisions about your data
  • Remove data points that are too old to be usable

Performing a Data Reintegration: Step By Step

  1. Create a Data Reintegration Plan: a step-by-step attack plan based on your goals, and the recommendations in this section
  2. Make a backup first
    • Most CRM’s have either internal or external solutions that allow the user to save the “state” of the CRM
    • Do this before the reintegration starts
  3. Use a sandbox before live testing on CRM
    • A sandbox refers to a temporary location for testing new operations or products
    • Make a copy of your CRM to test reintegration in the sandbox
  4. Start with a small data sample
    • Before a full reintegration, begin with a sample of 50 or 100 records
  5. Meet with your team
    • Explain which fields will be affected and get them to buy-in to the process
      1. There may be marketing, sales, financial, or operations processes that depend on certain data fields
    • Make a list of each field and how that field will be affected
  6. Score fields by importance
    • Low = ok to overwrite
    • Medium = possibly ok to overwrite (case by case basis)
    • High = do not overwrite
      • Strategy for scoring fields is to create a new, temporary field that lives side by side with your existing fields.
        • Allows the team to adjust new values/fields without losing data
  7. Set old fields as Read-Only
    • Do not allow the user to work with old data fields
    • Consider the “read-only” fields as “reference” fields (they can exist until the team is trained to use the new fields)
  8. Train Your Team: explain how the original dataset was changed during the reintegration
  9. For major changes, change one, or a few critical fields at a time
    • Make sure to make periodic backups of the data
    • Rule of Thumb: the longer the CRM has been used, the more dependencies there are
      • Regular usage should uncover broken reports or functions after each change
  10. Rename old fields before deleting them
    • Deleting fields is dangerous to automated processes and reporting. If you rename a field and a report breaks, this is better than losing data.
  11. Use the One Year Rule
    • Do not delete any old, unused fields
    • Some reports are run quarterly or yearly. Test reports on your new CRM structure
  12. Create a Change Log
    • Visible to all CRM users: show the changes that have been made and the upcoming changes scheduled

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