Dubsado vs Planhat
Side-by-side trajectory, velocity, and editorial themes.
Dubsado is in heads-down polish mode, shipping QoL fixes weekly for service-business owners.
Dubsado is on a fast cadence of small, customer-driven improvements: calendar reliability rebuilds, template tagging and archiving, prevent-reschedule controls, custom field reordering, smart fields in invoices, expanded bulk actions. Releases are typically bundled changelogs with dozens of fixes. Several are re-published across feeds with minor copy variants.
The team is investing in quality-of-life work over new categories — making the existing CRM stickier for solo and small-team service businesses. Many releases trace back to direct customer requests, including the recent ambassador event, suggesting a deliberate close-the-loop approach to roadmap. There is no visible push toward AI features or platform extension.
Expect this rhythm to continue with calendar/scheduling and template-management as the primary lanes. Customer-vertical specialization (hair, makeup, photography) will likely surface as preset templates or industry packages, given the ambassador-driven feedback loop.
Planhat doubles down on automation — Portals, Task dependencies, AI steps, OAuth — for scaled CS ops.
Planhat's recent stream skews heavily toward automation infrastructure for customer-success teams. New advanced Task dependencies, automated end-to-end Portal setup, full execution logs for Automation Runs, and live company-field merge tags in Dashboards and Presentations all reduce the manual per-account work that defines mid-tier CSM tooling. OAuth connections enter Labs, replacing API-key plumbing for integrations.
The product is moving from a health-score-and-playbook CS platform toward a low-code automation backbone for customer-success orgs. Recent additions of frontier LLMs (Claude Sonnet/Opus 4.6, GPT 5.4) into AI Automation steps, combined with portal-creation building blocks, position Planhat as a CS workflow engine that runs without per-account human babysitting.
Expect more native AI step types (action-taking, deeper retrieval), OAuth graduating out of Labs into the standard integrations surface, and continued investment in automation observability — failure analytics, retry policies, version history.
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