15/09/2025

The Economist Group is a global media and information-services company, serving both consumer and business audiences. Its B2C business centres on The Economist, a globally respected publication known for in-depth analysis of international news, politics, business, and economics. Alongside this, its B2B businesses provide data, research, insights, and events that help organisations navigate complex global issues. Together, these offerings reflect the Group’s reputation for insightful commentary, rigorous analysis, and a commitment to high-quality journalism.

Their four independent B2B Business Units were operating from the same CRM, but the problem was that they were working in silos and data was not accessible across different BU’s. This also brought additional pains, in example: each BU had their own customised data model, with its own set of fields and picklist values.

After performing a data and system analysis, the client realised that changing this would simplify data processes, allow for less customised environments, and adopt a more standardised approach.

Additionally, as some of the B2B business overlaps with The Economists’ B2C business, and B2C already had its own established CRM, bringing B2B and B2C together was an additional benefit to the client.

The goal was to increase cross-selling and scale the business for the future.

The Economist Group’s four B2B business units had been running separately, each with its own ways of managing data and engaging clients. This siloed approach limited collaboration, made it harder to see the full picture of client relationships, and created an inconsistent experience across the businesses. By reviewing how data and systems were being used, it became clear that adopting a more consistent approach would not only make internal processes simpler but also bring sales and marketing closer together—ultimately improving the experience for clients.

The rollout was gradual, data for each business unit was migrated separately, in four phases over 12 months.

All the data had to be migrated onto the new platform following the new model structure and procedures. This included some complex business needs too, e.g.:

• merging and deduplicating accounts, contacts, and leads
• applying business requirements to already migrated data in previous phases
• new product configuration
• multi-year deal opportunities
• rules for updating existing accounts, contacts
• data quality handling, and other adjustments

The complexity arose because both orgs were used in parallel by the sales teams. In developing our solution, we needed to take care not only of migrating the data, but considering data in the new org and keeping the new org up to date.

The solution is based on the methodology internally developed by the Solvership team, which covers the end-to-end migration expertise, starting from data analysis and data architecture design to the solution build, testing and finally the delivery of the migration solution to production systems.

Project phases

1. Data Discovery (3 weeks) - Solvership performed an initial high-level data analysis of the source systems to understand the needs and requirements, as well as the data volumes. Most impactful Data Quality issues were highlighted to the client. The To-Be architecture was not yet decided at this point.

2. Detailed Analysis and Design (9 weeks) - In this phase The Economist and their SI defined the To-Be architecture and started firming up the roadmap. Solvership analysed the To-Be model, the complexity of the transformation, and detailed deduplication (and other DQ) needs. Full effort for the upcoming migration waves was estimated, and the backlog for Wave 1 created.

3. Wave 1 migration (5 months) - Includes build, testing and delivery. The Solvership team created a specification of the source to target data mapping, the solution architecture and developed the ETL processes. The build and delivery was performed in an agile manner, staggered per target object (e.g. Accounts first, then Contacts, etc.). To make a solid base for the further waves, a detailed UAT was performed, lasting 1.5 months.

4. Wave 2 migration (4 months) - New objects were introduced, as well as new rules for matching and updating data found in dual running.

5. Wave 3 migration (3 months) - New objects introduced, e.g. case management. As this was the biggest migration so far, additional improvements were made to enhance performance.

6. Wave 4 migration (2 months).

This migration successfully met all the project requirements. The specific challenge of this project was the complex business requirement of merging and deduplicating accounts, contacts, and leads because there was a cross-deduplication requirement, meaning deduplication between:

• source and source
• source and target
• and different objects as well

There were several rules to selecting source data as well, led by the Data Retention strategy defined by The Economist Group. These rules were reviewed by Solvership, and improved further with The Economist Group, and ultimately built into the Data Migration Solution filters.

As a final result, we have successfully migrated both active and historical data from the legacy systems and updated existing data on target following the business rules. Data was cleansed and adjusted to prevent data quality issues in the new system.

Even though the data was migrated in phases, the volume of data for some phases was high, e.g. 50k accounts, 1m leads, etc. In order to make the migration perform well and complete in a reasonable timeframe, Solvership also:

• created and followed a detailed cutover plan,
• and balanced the migration load over multiple workspaces.

This was crucial for loading ~100GB of file data (Content Version) into Salesforce in a timely fashion.

Additional benefits of the migration approach was tagging the data with custom identifiers, especially where different deduplication rules were used. This enabled The Economist to construct a reconciliation process on top of the legacy and target platforms, to ensure completeness of data related to the migrated business unit.

Systems

The platform used for the data migration solution is based on Microsoft technologies and contains several databases implemented on MS SQL Server and ETL packages developed in MS SSIS. The solution enables repeatable processes of data ingestion, transformation, and push to target orgs. Unlike manual file processing, it allows for a true test of the process in several stages: integration testing, user acceptance testing, and finally the tested process is used to deploy data onto production.

Source data was extracted from Salesforce, Eloqua, and Marketo, then transformed and loaded to target objects, which are standard Salesforce objects (Accounts, Contacts, Opportunities, etc.).

Data was migrated into a total of 24 target objects, which included sales, marketing and case management data.

Technologies

The Solvership solution used the following tools:

• Microsoft SQL Server (on AWS)
• Microsoft SQL Server Integration Services; SSIS (on AWS)
• The solution worked with the following technologies /systems:
• Salesforce
• Marketo
• Exports from Oracle Eloqua - CX Marketing