CRM migration

Migrate from Dashly to Salesforce Sales Cloud

Field-level mapping, validation, and rollback between Dashly and Salesforce Sales Cloud. We move data and schema; workflows are rebuilt natively in Salesforce Sales Cloud.

Dashly logo

Dashly

Source

Salesforce Sales Cloud

Destination

Salesforce Sales Cloud logo

Compatibility

54%

7 of 13

objects map 1:1 between Dashly and Salesforce Sales Cloud.

Complexity

BStandard

Timeline

3-5 weeks

Rollback included Accuracy guarantee Field-level validation

Overview

What this migration involves

Moving from Dashly to Salesforce is a platform-type migration: Dashly is a chat-first conversational marketing and customer service tool, while Salesforce Sales Cloud is a full relationship CRM. The core migration work centers on converting Dashly's Lead records (with their behavioral data and custom properties) into Salesforce's dual Lead/Contact model, preserving the full conversation thread history as Activity records, and mapping Company records to Accounts. Dashly has no bulk export endpoint, so we pull all data via paginated API requests with field-level inclusion parameters and handle 429 rate-limit responses with backoff. Leadbot configurations, triggered message rules, and routing logic do not migrate as code; we export them as JSON and deliver a written inventory for your admin to rebuild in Salesforce Flow or Assignment Rules. Visitor session data is not migratable because it is ephemeral analytics aggregated by Dashly's engine.

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

Dashly logo

Dashly

What's pushing teams away

  • G2 reviewers report that Dashly's interface is not intuitive, with a steep learning curve that makes basic tasks like editing workflows and navigating the inbox time-consuming.
  • Users encounter difficulties deleting records and contacts cleanly, leading to data clutter and frustration when attempting to maintain accurate contact databases.
  • The platform's editing workflow for conversations and automations is described as cumbersome, forcing support teams to work around UI limitations rather than through them.
  • Email deliverability and sending issues appear in negative reviews, with some users reporting that outbound email features fail without clear explanation or workaround.

Choosing

Salesforce Sales Cloud logo

Salesforce Sales Cloud

What's pulling them in

  • The AppExchange marketplace with 5,000+ prebuilt apps gives enterprises integrations for nearly every business workflow without custom development.
  • Native Einstein AI for lead scoring, opportunity insights, and predictive forecasting adds intelligence without a separate platform purchase.
  • Territory management, multi-currency support, and advanced forecasting satisfy the needs of complex B2B sales organizations with structured revenue teams.
  • Slack, Tableau, and CPQ are deeply integrated into the core platform, keeping the sales stack unified for teams already in the Salesforce ecosystem.
  • Organizations with a large, established Salesforce implementation choose it because switching costs — integrations, custom code, trained admins — are prohibitive.

Object mapping

How Dashly objects map to Salesforce Sales Cloud

Each row shows how a Dashly object lands in Salesforce Sales Cloud, including any object-level transformations, lookup resolution, or schema-design dependencies.

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

Dashly

Lead

maps to

Salesforce Sales Cloud

Lead (or Contact after split)

1:many
Fully supported

Dashly Leads with qualification indicators (company name populated, multiple conversations, meeting booked) map to Salesforce Contact attached to an Account. Leads without qualification signals (anonymous or single-message visitors) map to Salesforce Lead. We compute the split using Dashly's conversation_count, company_association, and any custom qualification score properties, and preserve the original Dashly Lead ID in a custom field dashly_lead_id__c on both Lead and Contact for audit and reconciliation.

Dashly

Company

maps to

Salesforce Sales Cloud

Account

1:1
Fully supported

Dashly Company records map directly to Salesforce Account. The company domain and industry fields map to Account Website and Industry. Custom company properties migrate to Account custom fields. We create the Account before any Contact import so that the AccountId Lookup is satisfied at insert time.

Dashly

Conversation

maps to

Salesforce Sales Cloud

Case (Service Cloud) or Task

lossy
Fully supported

Dashly Conversations migrate to Salesforce Case if the destination org includes Service Cloud licensing, using Case Status and Record Type to represent conversation state (open, pending, resolved). If Service Cloud is not licensed, Conversations migrate as Activity Task records with a custom conversation_status__c picklist. Conversation metadata (source channel, assignee, created timestamp) transfers as Case or Task fields.

Dashly

Message

maps to

Salesforce Sales Cloud

EmailMessage or Task

1:1
Fully supported

Dashly Messages embedded within Conversations migrate to Salesforce EmailMessage records (for chat-to-email continuity) or Task records (for activity timeline display). Author attribution (agent vs visitor) preserves in the sender field. We link each Message to the parent Case or Task by resolving the Dashly conversation_id at migration time. Timestamps are preserved on ActivityDate or CreatedDate as applicable.

Dashly

User

maps to

Salesforce Sales Cloud

User

1:1
Fully supported

Dashly User accounts (agents and admins) map to Salesforce User by email address match. Agent roles and permission levels export as structured metadata. Any Dashly User without a matching Salesforce User is held in a reconciliation queue for the customer's admin to provision before record import resumes.

Dashly

Leadbot

maps to

Salesforce Sales Cloud

Configuration (manual rebuild)

lossy
Fully supported

Dashly Leadbots are automation configs with trigger conditions, dialogue trees, and action sequences stored in Dashly's JSON schema. We export the full bot configuration as structured JSON including trigger rules, conditional branches, message content, and delay actions. There is no direct Salesforce Flow equivalent for visitor-facing chatbot logic; the exported config and mapping guide serve as the blueprint for rebuilding in Salesforce Einstein Bots, Flow, or a third-party bot platform.

Dashly

Triggered Message

maps to

Salesforce Sales Cloud

Configuration (manual rebuild)

lossy
Fully supported

Triggered messages define automated outbound sequences tied to visitor behavior or time delays. We export the trigger rules, message content, delay settings, and audience filters as structured automation data. Salesforce Flow or Sales Engagement tools (High Velocity Sales, Sales Cloud Engagement) serve as the rebuild target; the exported config documents the intent and sequencing for the customer's admin or a Salesforce partner to implement.

Dashly

Knowledge Base Article

maps to

Salesforce Sales Cloud

KnowledgeArticle or Custom Object

1:1
Fully supported

Dashly Knowledge Base articles (title, body content, SEO settings, category associations) migrate to Salesforce Knowledge Articles if Service Cloud is licensed, using Article Type and custom fields to preserve SEO metadata and category structure. If Knowledge is not available, articles migrate as a custom object with rich-text body and category picklists. Deep SEO field mapping (meta title, meta description, URL slug) is preserved as custom fields on the destination article record.

Dashly

Tag

maps to

Salesforce Sales Cloud

Custom Field (multiselect picklist) or Topic

lossy
Fully supported

Tags applied to Leads, Conversations, or Companies export as flat label arrays. We map them to Salesforce custom multi-select picklist fields on the target object. For tagging strategies used for content classification, we map to Salesforce Topics with TopicAssignment records. The customer chooses the tag strategy during scoping.

Dashly

Custom Properties (Lead)

maps to

Salesforce Sales Cloud

Custom Fields on Lead or Contact

1:1
Fully supported

Dashly per-account custom properties on Leads are inventoried during discovery with data type, values, and usage frequency. We map them to Salesforce custom fields using type-appropriate Salesforce field types (text, number, date, picklist, checkbox, URL). Custom properties present on more than 30 percent of records are flagged as high-priority mappings; low-frequency or empty custom properties are mapped but flagged for the customer's admin to validate post-migration.

Dashly

Custom Properties (Company)

maps to

Salesforce Sales Cloud

Custom Fields on Account

1:1
Fully supported

Dashly custom company properties map to Salesforce Account custom fields. Domain and industry standard fields serve as anchors; custom fields carry over as typed Salesforce fields. Dedupe is handled by domain match to Account Website.

Dashly

Team Inbox Assignment

maps to

Salesforce Sales Cloud

Queue and Assignment Rules

lossy
Fully supported

Dashly conversation assignee data and routing rules export as configuration data. We map assignee email to Salesforce User and routing conditions to Assignment Rules on Case (or Task if no Service Cloud). The exported routing config documents the original condition logic (round-robin, load-based, skill-based) for the customer's admin to implement as Salesforce Case Assignment Rules or Omni-Channel Routing.

Dashly

Visitor Sessions

maps to

Salesforce Sales Cloud

None

1:1
Not supported

Visitor session data (page views, referrer, UTM parameters, session duration) is ephemeral analytics aggregated by Dashly's engine and is not migratable as structured records. We flag this as out-of-scope in the discovery document. Customers needing visitor behavior data retain it in Dashly for reporting until contract expiry or configure a separate analytics integration (Google Analytics 4, Mixpanel) to the Salesforce-powered website.

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.

Dashly logo

Dashly gotchas

High

Visitor-based pricing affects migration scoping

High

No public bulk export endpoint

Medium

Leadbot and triggered message configs require manual rebuild

Salesforce Sales Cloud logo

Salesforce Sales Cloud gotchas

High

Workflow Rules and Process Builder are retired

High

Bulk API batch quota exhaustion during large imports

Medium

Storage overage billing is non-obvious

Medium

Account-Contact many-to-many relationship mapping

Low

Territory and team member import ordering dependencies

Pair-specific challenges

  • No bulk export endpoint means API-based extraction with pagination overhead

    Dashly has no documented bulk export endpoint for Leads, Conversations, or Messages. All data retrieval goes through paginated REST API requests using optional field inclusion parameters (include_{field_name}=true). We chunk requests per endpoint, page through results sequentially, and handle 429 rate-limit responses with exponential backoff. For accounts with extensive conversation history (hundreds of thousands of messages), this adds two to four days of extraction time compared to bulk-export-capable platforms. We scope this overhead into the migration timeline before any data movement begins.

  • Leadbot and triggered message configs require manual rebuild in Salesforce Flow

    Dashly Leadbots and triggered messages are stored as structured automation configurations in JSON. No destination platform shares the same automation schema, so the bot logic, dialogue trees, trigger conditions, and delay sequences must be manually recreated. We export the full configuration as structured JSON and deliver a mapping guide that documents trigger types, conditions, actions, and recommended Salesforce Flow equivalents (record-triggered Flow for post-conversation updates, Scheduled Flow for time-based sequences, or Einstein Bots for visitor-facing chat). The automation rebuild is outside the data migration scope.

  • Conversation-to-Case threading requires Salesforce Service Cloud licensing

    Dashly Conversations are top-level threads that map most naturally to Salesforce Case objects. However, Salesforce Case is a Service Cloud object and requires a separate Service Cloud license beyond Sales Cloud. If the destination org has only Sales Cloud, we thread conversation history to Activity Tasks instead, which preserves the timeline but does not support the same SLA, entitlement, or case escalation features. We confirm Service Cloud licensing status during scoping and configure the mapping accordingly.

  • Dashly visitor-based pricing has no Salesforce analog for contact-level billing

    Dashly prices by monthly unique website visitors, not by seats or contacts. Salesforce Sales Cloud prices per user. When migrating Leads and Companies, the volume of visitor-derived contacts does not directly affect Salesforce licensing cost. However, customers who used Dashly's visitor volume as a heads-down capacity metric may need to adjust how they track agent workload and contact volume in Salesforce. We flag this distinction in the pricing impact section of the discovery document.

  • Custom property inventory and type mapping must complete before schema deployment

    Dashly custom properties are defined per-account with data types that may not map directly to Salesforce field types (e.g., Dashly stores phone numbers as string fields; Salesforce phone fields enforce format). We inventory all custom properties during discovery, validate type compatibility, and pre-create Salesforce custom fields in a Sandbox org for validation before production migration. Skipping this step results in failed inserts when legacy data does not conform to Salesforce validation rules at migration time.

Migration approach

Six steps for a successful Dashly to Salesforce Sales Cloud data migration

  1. Discovery and custom property inventory

    We audit the Dashly account across plan tier (Conversation, Support, Growth, Scale), total Leads, total Companies, conversation count, message volume, active Leadbots, active triggered messages, Knowledge Base article count, and custom property definitions. We pair this with a Salesforce edition check (Sales Cloud Professional vs Enterprise vs Unlimited) and Service Cloud licensing confirmation for Case-based conversation threading. The discovery output is a written migration scope with object counts, custom property inventory, and automation rebuild inventory.

  2. Destination schema design and sandbox validation

    We design the Salesforce destination schema including custom fields on Lead, Contact, Account, Case/Task, and Knowledge Article; Record Types and page layouts for case routing; Assignment Rules for conversation distribution; and the Lead-Contact split rule based on the qualification indicators present in the Dashly data. Schema is deployed via metadata API or change set into a Salesforce Sandbox first. We validate that all custom field types accept the incoming Dashly data format before touching production.

  3. API-based data extraction from Dashly

    We extract data from Dashly via paginated REST API requests with field-level inclusion parameters. Each object type (Lead, Company, Conversation, Message, User) is extracted in its own pipeline with sequential pagination, 429 backoff handling, and checkpointing for resumable extraction. For large accounts, extraction runs in parallel with schema validation to reduce wall-clock time. We capture all historical timestamps and author attribution during extraction.

  4. Sandbox migration and reconciliation

    We run a full migration into the Salesforce Sandbox using production-like data volume. The customer's RevOps or admin lead reconciles record counts (Leads in, Contacts in, Accounts in, Cases/Tasks in, Knowledge Articles in), spot-checks 25-50 random records against the Dashly source, and validates conversation thread continuity. Any field mapping corrections and type-cast issues surface here. Sign-off on the sandbox reconciliation gates production migration.

  5. Production migration in dependency order

    We run production migration in record-dependency order: Users (provisioned and validated), Accounts (from Dashly Companies), Leads and Contacts (with the qualification split applied), Cases or Tasks (from Dashly Conversations), Messages (linked to parent Case or Task), Knowledge Articles (if Service Cloud is licensed), Tags (as multi-select picklists or Topics), and custom property fields (mapped and validated). Each phase emits a row-count reconciliation report before the next phase begins.

  6. Cutover, validation, and automation rebuild handoff

    We freeze Dashly writes during the final cutover window, run a delta migration of any records modified during the migration, then enable Salesforce as the system of record. We deliver the Leadbot and triggered message configuration export with a mapping guide for rebuilding in Salesforce Flow or Einstein Bots. We support a one-week hypercare window where we resolve any reconciliation issues. Automation rebuild, workflow configuration, and admin training are outside the data migration scope and are handled separately.

Platform deep dives

Context on both ends of the pair

Dashly logo

Dashly

Source

Strengths

  • All-in-one platform combining live chat, AI leadbots, triggered messaging, and knowledge base in a single tool.
  • Unlimited seats across all paid plans, making it cost-effective for growing support teams without per-user licensing.
  • Visitor-based pricing allows small teams to start at a low monthly cost with overage flexibility.
  • Built-in knowledge base with unlimited articles and SEO settings supports both agent reference and self-service content.
  • Offers a free trial and free Conversation starter plan for evaluation.

Weaknesses

  • G2 reviews consistently describe the interface as unintuitive with a steep learning curve for new users.
  • Deletion workflows are reported as problematic, making it difficult to remove stale records cleanly.
  • Email sending and deliverability features receive recurring complaints in negative reviews.
  • No documented bulk data export endpoint means migration requires API-based extraction or manual workarounds.
Salesforce Sales Cloud logo

Salesforce Sales Cloud

Destination

Strengths

  • Largest enterprise app ecosystem in CRM with 5,000+ AppExchange integrations covering nearly every vertical workflow.
  • Native Einstein AI delivers lead scoring, opportunity insights, and predictive forecasting without a third-party layer.
  • Advanced territory management, multi-currency, and flexible forecasting satisfy complex B2B revenue structures.
  • Deep platform extensibility: Custom Objects, Apex, Flow, and the Metadata API allow full schema customization.
  • Well-documented REST API, Bulk API, and Composite API with published rate limits for programmatic migration.

Weaknesses

  • Pricing model is layered and opaque in practice: per-seat fees plus storage overages, add-on subscriptions, and annual uplifts compound to 30–40% above sticker price.
  • Workflow Rules and Process Builder are deprecated, forcing all orgs onto Salesforce Flow — a migration task that catches many teams by surprise.
  • Steep administrative complexity: meaningful configuration requires a dedicated Salesforce admin or consultant.
  • API rate limits are edition-gated (100k/day base for Enterprise) and easily exhausted by large historical imports without throttling.
  • Data export is exportable via Data Loader but preserving relationship integrity across 30+ objects requires careful ETL sequencing.

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 Dashly and Salesforce Sales Cloud.

  • 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

    Dashly: Not publicly documented.

  • Data volume sensitivity

    B

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

Estimator

Estimate your Dashly to Salesforce Sales Cloud 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 Dashly to Salesforce Sales Cloud data migrations

Answers to the questions buyers ask most during Dashly to Salesforce Sales Cloud migration scoping. Not seeing yours? Book a call.

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Small migrations under 5,000 Leads, 1,000 Companies, and 20,000 conversation messages with no Service Cloud dependency complete in three to five weeks. Medium migrations with large engagement histories (100,000+ messages), custom property mappings across multiple objects, or Salesforce orgs requiring Service Cloud configuration for Case-based threading extend to six to eight weeks. Large migrations with multi-year conversation history, Knowledge Base article sets, and custom automation rebuild coordination reach eight to twelve weeks.

Adjacent paths

Related migrations to explore

Ready when you are

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