SalesQL vs Planhat
Side-by-side trajectory, velocity, and editorial themes.
SalesQL is shipping prospecting depth at a measured pace — saved searches, team seats, multilingual UI.
SalesQL focuses on contact enrichment and prospecting on top of LinkedIn data. The recent shipping cadence is sparse but coherent: saved searches and richer company filters in Prospector, extra seats for team subscriptions at $10/seat, Spanish UI as a first step toward multilingual support, expanded contact export fields, and earlier this year a Reverse Email Lookup capability inside CSV Enrichment. There's no visible move into AI-driven outreach or scoring — the product remains a data-extraction-and-enrichment tool, not a sequencing or signals platform.
SalesQL is making the existing surface more useful for power users (saved filter sets, exportable enrichment fields) and starting to widen its addressable market through team plans and localization. Compared to the broader prospecting category — Apollo, Clay, Lusha, ZoomInfo — SalesQL's positioning looks deliberately narrower: a focused enrichment tool that doesn't try to become a workflow engine. That can be a defensible niche or it can be a slow squeeze depending on how much pricing pressure the larger tools apply.
The most likely next moves are more language additions to Prospector, deeper export/integration capabilities (Salesforce, HubSpot, CRM-native pushes), and possibly an enrichment-API tier that widens the developer-facing surface. AI-assisted outreach features would be a natural step but the cadence so far doesn't suggest urgency.
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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