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Data Consolidation

Unify fragmented customer data from multiple systems into one clean, governed, trusted source of truth.

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DATA AUDIT

How many versions of the truth does your organisation have?

When customer data lives in five systems, every team works from a different version of reality. Sales sees one number. Finance sees another. Marketing sees a third. We consolidate your fragmented data into HubSpot — cleaned, deduplicated, and governed — so every decision is based on the same trusted information.

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WHY MO FOR DATA

We don't just merge databases — we build the architecture for a single source of truth

Data consolidation isn't a technical exercise. It's an architectural decision about how your organisation stores, governs, and uses customer information. We design the data model before we move a single record.

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Architecture-first consolidation

Before merging anything, we map every data source, define ownership rules, and design the target data model. Which system is the source of truth for each data type? That's decided upfront, not discovered later.

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Deduplication and cleansing

Duplicate contacts, conflicting records, and inconsistent formats are resolved before consolidation. You don't inherit dirty data into a clean system — you inherit clean data into a governed one.

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Cross-system field mapping

Every property, field, and custom attribute is mapped across systems — with transformation rules for format differences, naming inconsistencies, and value conflicts.

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Governance from day one

Data quality rules, validation workflows, and permission structures are implemented during consolidation — not bolted on after. The clean state is maintained, not just achieved.

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Integration architecture

Consolidated data stays consolidated. We design the integration layer that keeps systems synced — with defined source-of-truth rules, sync frequencies, and conflict resolution.

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Zero-loss methodology

Every record is tracked through the consolidation process with reconciliation at every stage. Post-consolidation audits confirm nothing was lost, mismatched, or corrupted.

The cost of fragmented data is higher than you think

Fragmented customer data doesn't just create reporting inconsistencies — it creates operational dysfunction. Sales teams can't trust the pipeline because deal records are split across systems. Marketing sends campaigns to contacts that don't exist anymore. Finance reconciles invoices against customer data that doesn't match the CRM. Every team builds their own spreadsheet version of the truth. We consolidate your data into one governed platform — so every decision, report, and customer interaction is based on the same trusted foundation.

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Clean once, govern forever

Consolidation is only half the problem. Without governance, data quality degrades within months. We don't just merge your databases — we implement the validation rules, quality automation, and permission structures that keep the consolidated data clean. Property naming conventions, mandatory field rules, duplicate detection, and data quality workflows run continuously. Your single source of truth stays that way because the system won't let it drift.

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THE REALITY

Fragmented Data / Consolidated with MO Agency

Every organisation with more than two systems has a data fragmentation problem. The question is whether you're managing it — or ignoring it.

Fragmented Data

  • Multiple versions of the truth — Sales, marketing, finance, and service each have their own customer data in different systems. Every meeting starts with "which numbers are we looking at?"
  • Duplicate and conflicting records — The same customer exists in three systems with different spellings, different email addresses, and different account classifications. Nobody knows which record is current.
  • Manual data reconciliation — Staff spend hours weekly reconciling data between systems — exporting, cross-referencing, and updating spreadsheets. It's expensive, error-prone, and unsustainable.
  • Reporting nobody trusts — Dashboards show different numbers depending on which system they pull from. Leadership has lost confidence in the data, so decisions are made on instinct instead.
  • Scaling makes it worse — Every new market, product line, or acquisition adds another data source. The fragmentation compounds. Integration becomes exponentially harder.

Consolidated with MO Agency

  • One source of truth — All customer data lives in one governed platform. Every team works from the same records, the same definitions, and the same reporting layer.
  • Clean, deduplicated records — Duplicates are resolved, conflicts are mediated, and every record is validated against defined quality standards. The database is clean on day one and stays clean.
  • Automated data quality — Validation rules, duplicate detection, and quality workflows run continuously. Human reconciliation is replaced by system governance.
  • Trusted reporting — Dashboards pull from a single, validated data source. The numbers are accurate, consistent, and trusted across every team and function.
  • Scalable architecture — New systems, markets, and data sources plug into an established governance framework. Consolidation is a one-time effort. The architecture handles growth.
OUR APPROACH

How we consolidate fragmented data into a governed single source of truth

A structured methodology that starts with mapping and ends with governance.

Data Landscape Audit

We catalogue every system that holds customer data — CRM, ERP, marketing tools, finance platforms, spreadsheets, and legacy databases. We map what data exists, where it lives, and how it currently flows between systems.

Data Model Design

We define the target data model in HubSpot — objects, properties, associations, and source-of-truth rules for every data type. Naming conventions, validation rules, and governance structures are documented before any migration begins.

Cleansing & Deduplication

Records from each source are cleaned, standardised, and deduplicated using matching rules. Conflicts are resolved based on predefined ownership hierarchy. Every merge decision is logged and auditable.

Consolidation & Migration

Clean data is migrated into the target HubSpot environment in staged batches with validation at every checkpoint. Reconciliation reports confirm record counts, field completeness, and data integrity.

Integration & Sync

Systems that need to remain connected are integrated with defined sync rules, conflict resolution, and monitoring. The single source of truth is maintained through automated data flows.

Governance & Handover

Data quality automation, permission structures, and maintenance procedures are implemented and documented. Your team inherits a governed system with clear rules for how data enters, changes, and stays clean.

WHAT WE DELIVER

Every component of a governed data operation

From source mapping to ongoing governance — we build the infrastructure that makes a single source of truth possible and sustainable.

Source Mapping & Analysis

A comprehensive audit of every data source, field, and relationship in your organisation. The foundation for every architecture decision that follows.

Data Cleansing & Deduplication

Systematic cleaning, standardisation, and deduplication across all sources. Matching rules, merge logic, and conflict resolution — all documented and auditable.

Data Architecture & Modelling

Target data model design in HubSpot — custom objects, properties, associations, and validation rules built for your specific business requirements.

Governance & Quality Automation

Ongoing data quality rules, duplicate detection, validation workflows, and permission structures that keep consolidated data clean permanently.

CASE STUDIES

Trusted by leading brands

Cashflow Capital

Consolidated CRM data from multiple business entities into a single HubSpot environment — deduplicating 30,000+ records and delivering unified pipeline reporting for the first time.

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Enterprise Client

Merged data from Salesforce, an ERP, and three marketing tools into HubSpot — cleaning 5 years of accumulated data quality issues and establishing automated governance.

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Financial Services Group

Post-acquisition data consolidation for a financial services group — unifying customer records across two CRM platforms and four business units into one governed HubSpot instance.

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TESTIMONIALS

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Frequently Asked Questions

What does data consolidation involve?

Data consolidation is the process of bringing customer data from multiple systems — CRM, ERP, marketing tools, finance platforms, spreadsheets — into one governed platform. This involves auditing all data sources, designing a target data model, cleaning and deduplicating records, migrating data, establishing integrations, and implementing governance rules. The goal is a single source of truth that every team in your organisation trusts and uses.

How long does data consolidation take?

A focused consolidation from 2–3 sources typically takes 8–12 weeks. Complex multi-source projects involving 5+ systems, large data volumes, or post-acquisition merges can run 12–20 weeks. The timeline depends on the number of sources, data volume, cleanliness of source data, and complexity of the target data model. We scope the timeline during the data landscape audit.

Will we lose data during consolidation?

No. Our methodology includes staged migration with validation at every checkpoint, reconciliation reporting, and post-consolidation audits. Every record is tracked from source to destination. We also preserve source data for a defined period post-consolidation so nothing is permanently lost if an edge case is discovered after completion.

What happens to the source systems after consolidation?

That depends on your architecture plan. Some source systems are retired after consolidation (e.g., a legacy CRM). Others remain active but are integrated with HubSpot via defined sync rules — the ERP might continue as the finance system of record while HubSpot becomes the customer system of record. We define source-of-truth ownership for every data type during the architecture phase.

How do you keep data clean after consolidation?

Governance is built into the consolidation process, not added afterwards. We implement data quality automation (duplicate detection, validation rules, format standardisation), permission structures (who can create/modify records), naming conventions, and scheduled audit workflows. These run continuously in HubSpot to maintain the data quality achieved during consolidation.

How much does data consolidation cost?

A data landscape audit starts from R35,000 / £1,750. Full consolidation projects typically range from R120,000–R350,000 / £6,000–£17,500 depending on the number of sources, data volume, and complexity of the target architecture. Post-acquisition merges involving multiple CRM platforms are scoped individually. We provide a detailed proposal after the audit.

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