Migrate Maximizer Contacts to Salesforce Opportunities in Days
Maximizer's contact and activity silos make territory scaling painful—your sales records live in fragmented views with limited forecasting power. SuprSwitch uses its proprietary transformation layer to extract your Maximizer Contacts, Activities, and Companies directly into Salesforce's native Opportunity and Account schema, preserving every relationship and timeline in under 72 hours with zero manual reconciliation.
Why Sales Teams Choose SuprSwitch Over a DIY Maximizer CSV Export to Salesforce
Maximizer's native export flattens hierarchical contact-company relationships, strips custom field types (reducing them to plain text), and breaks activity timestamp integrity across interactions and history records. SuprSwitch's in-house transformation layer rebuilds Maximizer's relational structure into Salesforce's Account-Contact-Opportunity model, preserves field metadata through native schema mapping, and reconstructs complete activity timelines without loss of engagement context.
Company-Contact Links Rebuilt Correctly
Maximizer's Companies and Contacts export as separate flat files, losing the many-to-many relationship data that defines your account structure. SuprSwitch's direct data extraction engine reads Maximizer's relationship metadata and intelligently maps Companies to Salesforce Accounts and Contacts to Salesforce Contacts with proper AccountId linkages. This means your org hierarchy survives the migration intact—no duplicate contacts, no orphaned records, no manual re-linking in Salesforce.
Opportunity-Owner Assignments Persist
Maximizer's CSV export of Opportunities includes user assignments by name only, which breaks when Salesforce user IDs don't match. SuprSwitch's transformation layer performs intelligent owner mapping by matching Maximizer user login credentials and email addresses to your Salesforce user roster, automatically assigning Opportunities to the correct Salesforce owner records. Even if your Salesforce org has different user names or email domains, SuprSwitch resolves the mapping without manual lookup tables.
Custom Fields Land as Proper Data Types
Maximizer's native export converts all custom fields to text strings—currency fields become '100.50', dates become '2024-01-15 14:30:00', and picklists become comma-separated values. SuprSwitch's in-house schema mapper reads Maximizer's field definitions and re-types every custom field as it lands in Salesforce: currency as Currency, dates as Date, picklists as proper select lists. Your Salesforce formulas, reports, and roll-up summaries work correctly on day one.
Activity History & Timelines Fully Migrated
Maximizer's Activities, Interactions, and History records export with timestamps but no context linking to their parent Contacts or Opportunities. SuprSwitch's native data extraction rebuilds those relationships, importing each Activity, Call, Email, and Task into Salesforce with the correct ActivityDate and WhoId/WhatId references intact. Your complete engagement timeline—every call, note, and milestone—migrates in sequence, preserving your deal progression and customer history exactly as it was recorded.
Every Maximizer Asset, Accounted For
Maximizer stores business data across Contacts, Companies, Opportunities, Activities, Notes, and Products. SuprSwitch migrates all of these core objects to Salesforce while preserving data integrity, relationships, and custom fields throughout the migration process.
Built for Maximizer's Relational Data Architecture
Maximizer operates on a deeply nested relational schema with multiple interdependent tables, complex field types (including OLE object storage, binary fields, and custom attribute sets), and a proprietary index-based record linkage system. SuprSwitch's proprietary extraction engine reads directly from Maximizer's database layer, bypassing CSV exports to preserve type fidelity, maintain referential integrity through RecordID-to-SalesforceID translation, and handle Maximizer's non-standard field storage patterns (such as BLOB serialization and multi-value custom fields) through our native schema mapping transformation layer.
Direct Database Extraction
Type-Safe ExtractionMaximizer stores contact, account, and activity data across interconnected relational tables with strong type definitions—text, numeric, date/time, OLE objects, and binary fields. Our proprietary extraction engine connects directly to Maximizer's database and reads native field types without conversion to CSV, preventing data loss and type degradation. This preserves precision on numeric fields, maintains datetime zones, and extracts embedded objects (attachments, embedded rich-text) that CSV export would corrupt or discard. The result is zero rounding errors, no quote-escaping artifacts, and complete reconstruction of complex field values on the Salesforce side.
RecordID Linkage & Relationship Rebuild
Referential IntegrityMaximizer uses a RecordID-based system to link Contacts to Companies, Activities to Records, and custom related records through a junction table pattern. Our transformation layer maps every RecordID relationship in real-time, building a live translation table that converts Maximizer's internal record references into Salesforce's ID scheme as data loads. We rebuild parent-child relationships (Account→Contact, Contact→Activity), many-to-many associations (Contact Groups), and custom object relationships without data orphaning. If a Contact references a deleted Company, we log the orphan and flag it for remediation before cutover, ensuring no broken references reach production.
Custom Field Type Mapping & Attribute Translation
Schema-Aware MappingMaximizer's custom attribute system stores user-defined fields with varying storage patterns—some as native columns, others as serialized attribute pairs in auxiliary tables. SuprSwitch's native schema mapper auto-detects field cardinality (single-value vs. multi-value), data type (text, number, date, picklist), and storage location, then translates each field to its optimal Salesforce equivalent (standard field, custom field, or custom object). Picklists are extracted with their original values and sort order preserved. Long-text fields stored as TEXT or BLOB are mapped to Text Area or Long Text Area without truncation. Formula fields and read-only attributes are flagged during mapping review to prevent overwrite attempts.
Live-Safe Cutover with Delta Sync
Zero-Downtime MigrationOur transformation layer supports incremental synchronization: the initial bulk load moves all historical data to Salesforce, then a delta engine captures net-new and modified records from Maximizer's transaction log between cutover validation and go-live. On cutover day, we run a final sync of only changed records (new Contacts, updated Activity notes, new Opportunities) in minutes, not hours. Users remain in Maximizer until the final delta completes and is validated; only then do we flip the switch. This eliminates the risk of data entered during migration getting lost and ensures Salesforce is never stale at handoff.
100% Data Fidelity Guarantee
We verify record counts and field values in before sign-off. Any discrepancy is fixed before you go live.
30-Day Post-Migration Support
A dedicated migration engineer is available for 30 days post-launch to fix any data issues that surface after your team starts using.
SOC 2 Compliant Process
Data is encrypted in transit and at rest. We never store your credentials — OAuth tokens are used and revoked per migration.
Migration Architecture: Maximizer → Salesforce
SuprSwitch's Maximizer-to-Salesforce migration leverages deep knowledge of Maximizer's hierarchical contact database and company structures, mapping its contact-centric model to Salesforce's Account-Contact relationship while preserving custom fields, activity histories, and relationship metadata throughout the migration process.
SuprSwitch's proprietary extraction engine directly reads Maximizer's native database structures, indexing all contact hierarchy levels, company relationships, and custom field configurations without requiring external tools or middleware.
Multi-stage transformation layer processes Maximizer records through intelligent batch pipelines, deduplicating contacts, normalizing account hierarchies, and mapping custom fields to Salesforce field types before direct data pipeline ingestion.
Post-migration validation framework compares source-to-target record counts by object type, validates field mappings at row level, and confirms relationship integrity across Accounts, Contacts, and activity records before go-live sign-off.
Beyond Automation: In-House RevOps Experts
Our proprietary engine handles 99% of the heavy lifting, but every CRM has strict platform limitations. When HubSpot restricts automated imports for complex workflows or proprietary activity history, our in-house RevOps professionals step in.
We manually rebuild the business logic that machines can't touch, ensuring your new environment is perfectly tuned and ready for your sales team on day one.
What our experts handle manually:
Complex Workflows & Automations
Automated engines cannot migrate business logic. We manually translate and rebuild your HubSpot automations natively in HubSpot.
Restricted Activity History
Some historical data types are locked by HubSpot. Our team uses creative data-structuring to ensure no context is lost.
Custom Object Architecture
When standard mapping isn't enough, we architect and deploy custom objects in HubSpot to match your exact sales motion.
Choose the Migration Plan That Fits Your Business
Whether you want complete control or expert guidance, we’ve got you covered.
Self-Service
$499
Starting price, up to 50,000 records
Access to all supported CRMs
Free Sample migrations
Real-time Preview
Migration Analytics Report
Guided Migration
$999
Starting price, varies on volume.
Everything in Self-Service +
Selective Data Migration
Expert Migration Guidance
Data Mapping Support
Data Quality Management
Custom Migration
$Talk to us
Custom quotes for complex migrations.
Everything in Guided Migration +
Complex Field Transformations
Industry-Specific Customizations
Legacy System Integration
Complex Data Filtering