CRM migration

Migrate from Floww.ai to Microsoft Dynamics 365 Sales

Field-level mapping, validation, and rollback between Floww.ai and Microsoft Dynamics 365 Sales . We move data and schema; workflows are rebuilt natively in Microsoft Dynamics 365 Sales .

Floww.ai logo

Floww.ai

Source

Microsoft Dynamics 365 Sales

Destination

Microsoft Dynamics 365 Sales  logo

Compatibility

70%

7 of 10

objects map 1:1 between Floww.ai and Microsoft Dynamics 365 Sales .

Complexity

BStandard

Timeline

4-8 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Migrating from Floww.ai to Microsoft Microsoft Dynamics 365 Sales requires navigating a fundamental shift from a no-API, hyper-flexible pipeline model to a structured, API-first CRM built on Dataverse. Floww.ai provides no public REST endpoint or bulk export API, so all source reads depend on manual in-platform CSV exports that we coordinate in batches with the customer. We preserve the full Contact, Lead, Deal, Pipeline, Stage, and Activity record set, and we handle Floww.ai's Custom Object many-to-many relationships by mapping them to Dataverse entity relationships or flattening them into custom fields on the primary record. Pipeline stage filters from Floww.ai cannot be exported programmatically, so we document each pipeline's stage-level filter state for reconstruction in Microsoft Dynamics 365 Sales Processes. Workflows, AI Copilots, and Dashboards do not migrate; we deliver a written configuration inventory for the customer's admin to rebuild using Microsoft Dynamics 365 Sales Processes and Power Automate.

Field-level fidelity

Every standard and custom field arrives verified.

Schema-aware mapping

AI proposes the map; you confirm before any record moves.

Relationships preserved

Parent–child, lookups, and ownership stay linked.

Full activity history

Calls, emails, meetings — with original timestamps.

Attachments & notes

Documents, uploads, and inline notes move with the record.

Why teams make this switch

Two sides of the same decision

Leaving

Floww.ai logo

Floww.ai

What's pushing teams away

  • Manual filter reconfiguration is required at every pipeline stage, making pipeline restructuring a repetitive ops burden that erodes productivity over time.
  • The platform has no public REST API or documented export endpoints, forcing teams to use CSV manual exports for any data portability needs.
  • Recording features lack adequate delete and storage-management controls, leading to data hygiene issues and confusion about what constitutes a complete export.
  • Steep learning curve combined with insufficient in-platform tutorials means onboarding relies heavily on the vendor's own customer-success team.

Choosing

Microsoft Dynamics 365 Sales  logo

Microsoft Dynamics 365 Sales

What's pulling them in

  • Deep Microsoft 365, Teams, and Outlook integration makes Microsoft Dynamics 365 Sales a natural fit for Microsoft-first organizations already invested in that ecosystem
  • Sales Enterprise and Premium tiers offer unlimited custom tables and advanced AI-driven forecasting and predictive analytics not available in lower tiers
  • Professional tier pricing at $65 per user per month offers a lower entry cost than Salesforce for SMB teams with straightforward CRM needs
  • Flexible customization options allow businesses to build bespoke apps, tailor forms and views, and integrate with other Dynamics 365 modules
  • Microsoft Copilot AI tools are embedded directly into the sales workflow on Enterprise and Premium, automating routine tasks and providing deal intelligence

Object mapping

How Floww.ai objects map to Microsoft Dynamics 365 Sales

Each row shows how a Floww.ai object lands in Microsoft Dynamics 365 Sales , including any object-level transformations, lookup resolution, or schema-design dependencies.

Typical mapping — final map is confirmed during the sample migration step.

Floww.ai

Contact

maps to

Microsoft Dynamics 365 Sales

Contact

1:1
Fully supported

Floww.ai Contact records map directly to Microsoft Dynamics 365 Contact. Standard fields (FullName, Email, Phone, BusinessPhone, CompanyName) migrate 1:1. Floww.ai custom Contact properties migrate as typed fields on the Contact entity in Dataverse. Email address is used as the primary dedupe key during import to prevent duplicate Contact creation.

Floww.ai

Lead

maps to

Microsoft Dynamics 365 Sales

Lead

1:1
Fully supported

Floww.ai Lead records (distinct from Contacts in Floww.ai's data model) map to Dynamics 365 Lead. Lead source, status, rating, and any custom categorization fields migrate to the corresponding Lead entity fields in Dataverse. We preserve the Floww.ai lead categorization as a custom field for audit and to support any downstream segmentation logic.

Floww.ai

Company

maps to

Microsoft Dynamics 365 Sales

Account

1:1
Fully supported

Floww.ai Company records map to Dynamics 365 Account. Company name maps to Account Name; domain fields map to Website. Account is created before Contact import so that the CustomerId (Account) lookup relationship is satisfied at the moment of Contact insert. The customer chooses whether to use Account as the primary organizational unit for Deals or to attach Deals directly to Contact records.

Floww.ai

Deal

maps to

Microsoft Dynamics 365 Sales

Opportunity

1:1
Fully supported

Floww.ai Deal records map to Dynamics 365 Opportunity. Deal value maps to EstimatedRevenue; expected close date maps to EstimatedCloseDate; owner assignment maps to OwnerId. The Deal's linked Pipeline and Stage are resolved during migration by matching Pipeline name to a Microsoft Dynamics 365 Sales Process and Stage to a Stage within that process. We create the Sales Process configuration before migration if it does not already exist in the destination org.

Floww.ai

Pipeline

maps to

Microsoft Dynamics 365 Sales

Sales Process + Record Type

lossy
Fully supported

Floww.ai Pipelines (which support multiple concurrent pipelines with distinct stage sets) map to Dynamics 365 Record Types on Opportunity, each paired with a corresponding Sales Process that whitelists the relevant stage values. Stage order and naming conventions are reconciled against the Dynamics 365 stage model during configuration design. If the customer has three distinct business lines with different stage sequences, we create three Record Type and Sales Process combinations to preserve that structure.

Floww.ai

Pipeline Stage

maps to

Microsoft Dynamics 365 Sales

Opportunity Stage

lossy
Fully supported

Floww.ai Pipeline Stages map to Dynamics 365 Opportunity Stage values within the corresponding Sales Process. Stage probability percentages migrate from Floww.ai to Dynamics 365 StageProbability. Note that Floww.ai stage-level filters (which do not persist across navigation in the source platform) are documented as part of the configuration inventory rather than exported directly; we provide a written reconstruction plan for each stage filter that the customer's admin implements in Microsoft Dynamics 365 Sales Processes or Power Automate.

Floww.ai

Activity

maps to

Microsoft Dynamics 365 Sales

Activity (Task or Email)

1:1
Fully supported

Floww.ai Activities (calls, emails, notes, scheduled tasks logged against Contacts and Deals) map to Dynamics 365 Activity records. Call activities become Task with TaskSubtype=Call; email activities become Email; notes become Annotation (note) records linked via Dataverse RegardingObjectId to the parent Contact, Account, or Opportunity. Activity timestamps (CreatedAt) map to ScheduledEnd for tasks and to ActualStart/ActualEnd for events. The Activity pointer to the linked Contact or Deal record is preserved as RegardingObjectId in Dataverse.

Floww.ai

Custom Object

maps to

Microsoft Dynamics 365 Sales

Custom Entity (Dataverse)

1:1
Fully supported

Floww.ai Custom Objects with one-to-many and many-to-many relationships map to Dataverse custom entities. We request a schema map from the customer before migration, pre-create the destination schema in Dataverse (including all custom columns, lookup relationships, and many-to-many intersect entities), then migrate records after the primary object migration completes. Many-to-many relationships in Floww.ai become Dataverse Many-to-Many relationships with a corresponding intersect entity; one-to-many relationships become Lookup columns on the child entity. The customer confirms the Dataverse entity naming convention during scoping.

Floww.ai

Owner

maps to

Microsoft Dynamics 365 Sales

User

1:1
Fully supported

Floww.ai Users referenced on Contacts, Deals, and Activities map to Dynamics 365 User records by email address match. Any Floww.ai Owner without a matching Dynamics 365 User is held in a reconciliation queue for the customer's admin to provision before record import resumes. We do not migrate Floww.ai user roles or permissions; these are reconfigured in Dynamics 365 Security Roles and Teams post-migration.

Floww.ai

Tag

maps to

Microsoft Dynamics 365 Sales

Custom Field (Text or Option Set)

lossy
Fully supported

Floww.ai Tags used for segmentation migrate as a text field on the relevant record (Contact or Deal) storing comma-separated tag values, or as a multi-select option set if the Dynamics 365 org supports that field type. The customer chooses the tag strategy during scoping. Tags used for Contact Hit List (telesales sequencing) require a separate rebuild plan in Microsoft Dynamics 365 Sales using Sales Process stages or a custom entity if the sequence logic is complex.

Gotchas + challenges

What specifically takes care here

Platform-specific issues from each side, plus the pair-specific challenges that don't show up on either platform's page on its own.

Floww.ai logo

Floww.ai gotchas

High

No public API forces reliance on manual CSV exports

Medium

Pipeline stage filters do not persist across stage changes

Medium

Pro-rated account billing requires careful license reconciliation

Medium

Custom Objects use non-standard relationship cardinalities

Low

Recording and attachment storage not accessible via bulk export

Microsoft Dynamics 365 Sales  logo

Microsoft Dynamics 365 Sales gotchas

High

Professional tier 15-table custom table limit blocks migrations

High

October 2024 pricing increase applies at renewal for all customers

Medium

Custom fields must be created in the UI before API writes

Medium

Power Platform request limits apply to bulk migrations

Medium

Activity records orphaned to inactive owners fail silently

Pair-specific challenges

  • No public API forces reliance on manual CSV exports

    Floww.ai does not publish a REST API or bulk export endpoint for programmatic data retrieval. All migration reads require the customer to manually trigger exports from within the platform. Where Floww.ai imposes row limits on exports, we request multiple filtered exports segmented by pipeline, stage, or date range and merge them before writing to Dynamics 365. This adds coordination overhead and a manual verification step at each batch. We recommend scheduling export sessions with the customer's Floww.ai admin early in the engagement to avoid blocking the migration timeline on export availability.

  • Pipeline stage filters cannot be exported and must be reconstructed

    Floww.ai stage-level filter definitions do not persist across pipeline navigation in the platform and cannot be retrieved via export. We capture the active filter state per stage during the configuration inventory phase by reviewing the pipeline definitions with the customer's admin. These filter rules must be reconstructed in Dynamics 365 using Sales Process stage entry criteria or Power Automate cloud flows. We document the filter logic in plain language during scoping so the admin can implement the equivalent behavior without reverse-engineering the original rule structure.

  • Custom Object many-to-many relationships require schema pre-creation in Dataverse

    Floww.ai Custom Objects support non-standard relationship cardinalities including many-to-many links that may not map directly to Dynamics 365's entity model. We require a complete schema map from the customer covering all Custom Object definitions and relationship types before migration. The destination Dataverse schema (custom entities, columns, lookup relationships, and intersect entities) must be provisioned before any Custom Object data migrates. If the customer has not yet provisioned the Dynamics 365 environment, we coordinate schema creation in parallel with export scoping to avoid a sequencing bottleneck at migration time.

  • Recording and attachment storage requires a separate file migration pass

    Call recordings and file attachments stored within Floww.ai are not accessible via the bulk export utility. We schedule a separate file migration pass, pulling files from the platform's storage layer where the customer grants access credentials. Recordings are optional migration targets and are flagged for explicit customer confirmation before inclusion in the migration scope. File attachments are migrated as Note (Annotation) records in Dynamics 365 with the file content stored in Dataverse or SharePoint depending on the org's document management configuration.

Migration approach

Six steps for a successful Floww.ai to Microsoft Dynamics 365 Sales data migration

  1. Discovery and environment provisioning

    We audit the source Floww.ai environment with the customer's admin, covering Contacts, Leads, Deals, Pipelines, Stages, Custom Object definitions, Activity types, and record volume. We also inventory active Flows, pipeline filter configurations, and any Custom Object relationship schemas. In parallel, we confirm the destination Microsoft Dynamics 365 Sales environment provisioning: which tier (Essentials, Professional, Premium), whether Dataverse is enabled, and whether the customer has an existing Power Platform environment. The discovery output is a written migration scope and a Dataverse schema requirements document.

  2. Export coordination and CSV validation

    Because Floww.ai has no API, we coordinate with the customer's admin to run manual exports in sequence. We request segmented exports by pipeline, stage, and record type to work around any pagination limits the platform imposes. Each export batch is validated for row count, column completeness, and date-range consistency before we proceed to transformation. We flag any gaps (missing fields, truncated records, date format inconsistencies) for the admin to re-export before the transformation pass begins.

  3. Dataverse schema design and provisioning

    We design the destination schema in Dynamics 365 Dataverse based on the Floww.ai schema map. This includes creating custom entities for Floww.ai Custom Objects, custom columns on standard entities (Contact, Account, Opportunity, Lead), many-to-many intersect entities for non-standard relationships, and the Sales Processes and Stage definitions that map to each Floww.ai Pipeline. Schema is validated in a Dynamics 365 Sandbox environment before production migration begins. We do not deploy schema directly to production without a sandbox validation sign-off from the customer's admin.

  4. Owner reconciliation and User provisioning

    We extract every distinct Floww.ai Owner referenced on Contacts, Deals, Activities, and Custom Objects and match by email against the Dynamics 365 destination org's User table. Owners without a matching User go to a reconciliation queue. The customer's Dynamics 365 admin provisions any missing Users and assigns appropriate Security Roles. This step must complete before record migration begins because OwnerId references are required on most standard entities in Dynamics 365.

  5. Production migration in dependency order

    We run production migration in record-dependency order: Users (provisioned, validated), Accounts (from Floww.ai Companies), Contacts (with CustomerId resolved to Account), Leads (with OwnerId resolved), Opportunities (with AccountId, OwnerId, and Sales Process resolved), Activities (Tasks, Emails, Annotations via Dynamics 365 Dataverse API with batch chunking), then Custom Objects last because they often have lookups to standard entities. Each phase emits a row-count reconciliation report before the next phase begins. We use Dataverse Web API with rate-limit handling and exponential backoff for all writes.

  6. Cutover, validation, and configuration inventory handoff

    We freeze Floww.ai writes during cutover, run a final delta migration of any records modified during the migration window, then enable Microsoft Dynamics 365 Sales as the system of record. We deliver the Flow, pipeline filter, and Custom Object relationship inventory document to the customer's admin team with recommended Dynamics 365 equivalents (Sales Processes, Power Automate cloud flows, Dataverse relationship definitions). We support a one-week hypercare window where we resolve reconciliation issues. We do not rebuild Floww.ai Flows as Power Automate or Microsoft Dynamics 365 Sales Processes inside the migration scope; that is a separate engagement or an internal admin task.

Platform deep dives

Context on both ends of the pair

Floww.ai logo

Floww.ai

Source

Strengths

  • Per-account subscription with pro-rated billing accommodates mid-growth headcount additions without billing surprises.
  • Ranked #1 Enterprise Usability Index on G2 Winter 2024 reflects genuine ease of onboarding for non-technical sales teams.
  • Hyper-flexible pipelines support non-linear B2C sales processes that standard CRM stage models cannot represent cleanly.
  • Native AI Copilots for sales and analytics are embedded at the workflow level rather than bolted on as third-party integrations.
  • 14-day free trial with guided onboarding lets teams validate pipeline configuration before committing to a paid plan.

Weaknesses

  • No public REST API or documented bulk export endpoints means all data extraction relies on manual in-platform exports.
  • Recording feature lacks adequate delete and storage management controls, complicating data hygiene during migration scoping.
  • Filters do not carry across stages automatically, making large-scale pipeline restructuring a manual, error-prone process.
  • Slow loading times when handling large data volumes suggest the platform's query performance degrades at enterprise scale.
  • Steep learning curve combined with insufficient in-platform tutorials makes independent onboarding difficult without vendor support.
Microsoft Dynamics 365 Sales  logo

Microsoft Dynamics 365 Sales

Destination

Strengths

  • Native integration with Microsoft 365, Teams, Outlook, and SharePoint for unified productivity workflow
  • Unlimited custom tables and complex workflows on Enterprise tier enable deep customization for complex sales processes
  • AI-driven predictive analytics and deal intelligence on Enterprise and Premium tiers help sales teams prioritize pipeline
  • Dataverse unified data layer provides a consistent API and data model across all Dynamics 365 and Power Platform apps
  • Strong security model with Field-Level Security and Record Ownership rules for governance-conscious enterprises

Weaknesses

  • Sales Professional tier caps custom tables at 15, creating a migration ceiling for highly customized SMB environments
  • October 2024 pricing increases of $15 per user across all tiers apply to existing customers upon renewal
  • Implementation typically requires costly certified partners, adding 30–50% to total project cost
  • Updates and platform releases can disrupt customizations and plugins, requiring regression testing after each wave
  • Non-Microsoft integrations require additional configuration or middleware, limiting flexibility for heterogeneous tech stacks

Complexity grading

How hard is this migration?

Standard CRM migration. 1 of 8 objects need a mapping; the rest are 1:1.

B

Overall complexity

Standard migration

Derived from compatibility, mapping clarity, API constraints, and data volume across Floww.ai and Microsoft Dynamics 365 Sales .

  • Object compatibility

    B

    1 of 8 objects need a mapping; the rest are 1:1.

  • Field mapping clarity

    C

    Field mapping is derived from defaults — final spec confirmed during the sample migration.

  • Timeline complexity

    B

    8-object category — typical timelines run 2–7 days end-to-end.

  • API constraints

    B

    Floww.ai: Not publicly documented.

  • Data volume sensitivity

    B

    Floww.ai doesn't expose a bulk API — REST + parallelization used for high-volume runs.

Estimator

Estimate your Floww.ai to Microsoft Dynamics 365 Sales migration cost

Rule-based pricing — no per-record fees, no manual quotes. Migrations over 2M records are scoped individually.

Step 1

What are you migrating?

Pick a category, then your source and destination platforms.

Category

FAQ

Frequently asked questions about Floww.ai to Microsoft Dynamics 365 Sales data migrations

Answers to the questions buyers ask most during Floww.ai to Microsoft Dynamics 365 Sales migration scoping. Not seeing yours? Book a call.

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Most migrations land between four and eight weeks for accounts under 15,000 Contacts, 3,000 Deals, and no Custom Objects with complex relationships. Migrations with multiple Pipelines, Custom Objects with many-to-many relationships, large Activity histories (over 200,000 records), or environments requiring manual CSV chunking move to eight to fourteen weeks because of export coordination overhead, Dataverse schema provisioning, and relationship resolution work. The manual CSV export dependency in Floww.ai is the primary timeline variable; API-accessible source platforms run significantly faster.

Adjacent paths

Related migrations to explore

Ready when you are

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