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Migrating customer data can be a complex and challenging process

The process of migrating customer data can be intricate and demanding. However, CRM migration goes beyond a straightforward transfer of customer data between platforms, or shifting from on-premise to cloud-based solutions. It signifies a digital transformation.

To navigate this journey effectively, it is crucial for organizations to invest in meticulous preparation for their data migration projects.

This proactive approach will ensure you mitigate risks, minimize downtime, and achieve a seamless transition to the new system.

Here is a step-by-step guide to our CRM migration methodology

STEP 1 – Identify the Business Purpose

There are no data management initiatives, only business initiatives, therefore, before embarking on a CRM migration project, the business benefits of the migration should be agreed upon and understood by all of the interested parties.

STEP 2 – Communication

You cannot over communicate with the stakeholders and end-users in a data migration project.

It is crucial to ensure that they are aware of the business purpose, the migration process, and any potential impact on their work.

STEP 3 – Scope the Migration Objectives

It is essential to define the scope of the project and create a plan that includes:

    1. Agreeing what success looks like
    2. Identifying the customer data, to be moved and why it needs to move
    3. Uncovering any customisations or integrations that will need to be addressed
    4. Determining the timelines, milestones, and resources required
    5. Assessing the risks associated with the migration
    6. Agreeing a communication and team collaboration strategy
    7. Developing contingency plans in case of unexpected challenges

STEP 4 – Data Landscape Analysis

Conduct a thorough source and target data landscape analysis to discover, review, and document the legacy data stores, including their linkages, data quality requirements and the key data stakeholders.

This helps to understand the structure of the source and target systems and the responsibilities of all parties involved.

STEP 5 – Analysis and Mapping

Identify any gaps and anomalies between the source and target systems and determine what data is business critical.

Then map all data fields between the source and target entities, remembering to update the mapping documents as the project progresses.

STEP 6 – Backup your Data

Make sure you have a backup strategy and recovery process before starting the migration, in case of any issues during the process.

Having a full backup allows you to re-play all process, should something go wrong along the way.

STEP 7 – Choose a Migration Method

There are several methods to choose from when migrating data to any target system, including: manual data entry, data import, and data migration tools.

A method will be agreed based on a best fit with your business needs, budget, and resources.

STEP 8 – Prepare the Target Environment

Imagine asking your furniture removal men to move your house contents without knowing where anything goes.

To avoid this situation, set up the target CRM environment, ensuring it is complete, configured correctly, including: custom fields, entities, plug-ins, and workflows, and has the appropriate security privileges assigned.

STEP 9 – Map your Data

Create a source to target map for every database entity/table and all of their data fields, defining the relationships between the two or more systems and ensure that all data is properly aligned.

This is like specifying where the contents of every room in the old house should be moved to the new house ensuring that everything will fit.

STEP 10 – Define Data Transformation, Cleansing, Matching and Mastering Logic

Understand the business rules and logic for all data transformations and cleansing, including: data type changes, lookup and pick-list value changes, data value standardization, validation, verification and authentication requirements.

Additionally, agree the record matching methodology to remove duplicates and agree the record mastering logic to achieve a Single Customer View (SCV)

STEP 11 – Data Extraction

Using agreed data retention rules, extract all relevant data from the source system(s) and consolidate it into a staging download staging database which is then used for all subsequent data transformation processes.

STEP 12 – Data Transformation and Cleansing

In this phase, we apply the rules or functions agreed to transform and cleanse the extracted data to ensure it is fit for use in the target system.

This stage often includes customer data cleansing and enrichment where we will transform and validate the customer data as needed, whilst ensuring data privacy and security requirements are adhered to during data processing.

The transformation processes are either scripted using SQL or managed through our DQ Studio™ workflow engine to ensure repeatability.

STEP 13 – Test Loads

The testing process can vary widely based on the requirements. However, we run full test loads into a sandbox environment of the target system to ensure the data migration is effective.

We validate that data migrated into the target system is correct and complete to ensure that it has been migrated correctly, including testing customizations, integrations, and reports.

STEP 14 – Amendments

We hand over the migrated data in the target sandbox environment for client review and provide a feedback process for any queries.

We then make any necessary changes in preparation for another test load, or the go-live load.

STEP 15 – Go-Live Load Cut-Over

Once all changes are made and validated, we refresh the staging data from the source data and run the go-live loading scripts.

The go-live load is usually done over the weekend or at a designated time when the client is not using the source or target systems.

When a hot migration is being performed, we use delta management processing to ensure all records added or changed in the source systems are successfully inserted or updated into the target system.

During the cut-over we constantly monitor the migration processes and quickly resolve any issues which may arise. And confirm data accessibility and usability in the target system is correct.

STEP 16 – Post-Migration and Review

    • Validate the customer data in the target system is correct and fit for use
    • Document the migration process and outcomes achieved
    • Review and update any processes and procedures as needed
    • Provide training and support for end users
    • Implement data governance and maintenance processes
    • Evaluate the success of the migration and identify areas for improvement
    • Provide post-go-live support to ensure the new system is working as expected

In Conclusion

By carefully preparing for a data migration project, organizations can minimise risks, reduce downtime, and ensure a smooth transition to the new system.

Note: The specifics of your CRM data migration project may require different or additional steps. The list above serves as a general guide and should be tailored to exactly meet your needs.

Our DQ Studio CRM data migration methodology is designed to ensure a seamless and successful migration of your customer data from your source systems to the target system.

Our experienced team will work in consultation with you throughout the whole process to ensure a successful data migration project with minimal disruption to your business and a smooth transition to the new system.

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Written by Conor Doyle

Conor has been at DQ Global for the past 3 years. He now leads the sales team to maintain and build client and business partner relationships. Throughout, he has gained extensive knowledge and experience surrounding Data Quality and established himself as an industry expert.