Success Story
Carl Remigius Fresenius Education Group: Data Integration Impact Study
Company
Carl Remigius Fresenius Education Group
Services used
CRM Data Audit & Integration Management
Industry
Education
The Client
Carl Remigius Fresenius Education Group (CRF) provides higher education, vocational training and continuing education in Germany and abroad.
CRF uses Salesforce as its source of CRM data and HubSpot for marketing operations. RevOps Automated’s work focused on checking the data moving between these systems, investigating discrepancies and helping CRF maintain reliable marketing audiences.
The Challenge
CRF needed to understand which records should reach HubSpot and whether its audience counts were correct. Data passed through several systems, with duplicate handling, email validation and filtering rules affecting the records available to marketing teams.
Historical duplicates in HubSpot and differences between list criteria complicated those checks. Each discrepancy needed to be traced to its cause before the team could decide what action to take.
They faced several practical hurdles:
Unexplained audience gaps: Salesforce and HubSpot returned different contact counts, leaving the team to establish what accounted for the difference.
Historical duplicate records: Duplicate Product Interests inflated list counts and complicated comparisons.
Different filtering rules: Warehouse queries sometimes included blank or missing values that HubSpot list criteria excluded.
Missing contact matches: Invalid emails and matching issues affected the connection between Product Interests and contacts.
Several possible causes: Discrepancies could originate in Salesforce, data processing, synchronisation or HubSpot list configuration, requiring checks across the full data route.
The Solution
RevOps Automated used a repeatable audit process to follow records through CRF’s existing Salesforce-to-HubSpot pipeline. The work combined direct Salesforce checks with warehouse queries and validation of the records prepared for HubSpot.
This gave the team evidence to explain audience differences, identify specific faults and coordinate corrective work with Data Engineering.
Key pillars of the project included:
Independent source checks: Salesforce Workbench queries verified source records before downstream processing rules were applied.
Record-level investigation: Queries traced discrepancies through BigQuery, dbt, Hightouch and HubSpot, examining duplicates, email quality, filters and missing associations.
Duplicate clean-up: The work supported the removal of more than 16,000 duplicate Product Interest records across 6 lists in September 2025. SQL/model logic was also updated to exclude new duplicates.
Consistent audience criteria: Filtering was corrected across 6 Product Interest lists to exclude blank and NULL values where HubSpot’s criteria required it.
Stronger contact matching: Matching logic used email-based identifiers from both Salesforce Contact and Lead records to improve Product Interest-to-contact matching.
Repeatable monitoring: Colour-coded match thresholds helped prioritise discrepancies, while source checks and follow-up comparisons helped validate corrections.
The Impact in Numbers
Metric | Before | After |
Contact-segment reconciliation | A 20,343-record difference requiring investigation | Difference accounted for through duplicate merging and email exclusions |
Product Interest duplicates | More than 16,000 duplicate records across 6 lists | Duplicate records deleted, improving the basis for audience comparisons |
Audience filtering | Queries included blank and NULL values excluded by HubSpot criteria | Filtering corrected across 6 Product Interest lists |
Product Interest matching | Missing contact matches under investigation | Matching strengthened using identifiers from both Contact and Lead records |
Subscription list validation | A record-count discrepancy | 100% count match after correction |
Integration monitoring | Count differences needed investigation and interpretation | Consistent severity thresholds and repeatable checks across the data pipeline |
1. A 20,343-record gap accounted for
In September 2026, the audit examined CRF’s BU – Ausbildung contact segment. Salesforce held 108,662 contacts, compared with 88,319 in HubSpot.
The investigation accounted for the 20,343-record difference through duplicate merging and exclusions for invalid or unaddressable emails. CRF gained a clear explanation for the expected audience size and evidence to guide corrective work.
2. Cleaner Product Interest data
More than 16,000 duplicate Product Interest records were deleted across 6 lists in September 2025.
The clean-up improved the reliability of list comparisons. Updates to SQL/model logic also excluded new duplicates, helping maintain a cleaner dataset for ongoing checks.
3. More consistent audience checks
Filtering corrections brought warehouse queries into agreement with HubSpot criteria across 6 Product Interest lists. This reduced count inflation caused by blank and NULL values.
A separate subscription list returned a 100% record-count match after correction, giving the team a clear checkpoint for validating that fix.
4. Stronger matching between interests and contacts
Contact matching was strengthened using email-based identifiers from both Salesforce Contact and Lead records. Investigations also identified invalid or missing email addresses as causes of missing Product Interest matches.
These checks helped the team locate the causes of missing matches and direct follow-up to the relevant data or processing rules.
5. A repeatable process for ongoing monitoring
CRF has a consistent method for checking discrepancies across its data pipeline. Match-rate thresholds help the team prioritise investigations, and direct source queries provide an independent check on Salesforce records.
The process supports recurring issue tracking, targeted work with Data Engineering and validation of corrections. Marketing operations have a clearer basis for checking the audiences available in HubSpot.
“RevOps Automated gave us a clear view of how our data moves from Salesforce into HubSpot, something we had struggled to explain on our own. They traced every discrepancy back to its cause, from duplicate records to filtering and email issues, and worked closely with our Data Engineering team to fix them. We now trust the audiences our marketing teams rely on, and we have a repeatable process that keeps our data reliable as we grow.”
CRF Team
Impact Snapshot
20,343
record gap fully accounted for
Salesforce held 108,662 contacts in the BU – Ausbildung segment compared with 88,319 in HubSpot. The audit traced the entire difference to duplicate merging and exclusions for invalid or unaddressable emails, giving CRF a clear explanation of its expected audience size.
16,000
+
duplicate records removed
More than 16,000 duplicate Product Interest records were deleted across 6 lists, improving the reliability of list comparisons. Updated SQL/model logic now excludes new duplicates, keeping the dataset clean for ongoing checks.
100
%
record-count match on audience validation
Filtering corrections across 6 Product Interest lists brought warehouse queries into line with HubSpot criteria, removing count inflation from blank and NULL values. A separate subscription list returned a full record-count match after correction.
2
x
identifier sources for contact matching
Product Interest matching now uses email-based identifiers from both Salesforce Contact and Lead records. Investigations also pinpointed invalid or missing emails as the cause of missing matches, directing follow-up to the right data and processing rules.
5
systems covered by repeatable monitoring
Checks now run across Salesforce, BigQuery, dbt, Hightouch and HubSpot, with colour-coded match thresholds to prioritise discrepancies. Marketing operations have a consistent method for tracking issues, working with Data Engineering and validating corrections.
