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Clari
Enterprise Revenue Orchestration
VS
Gong
Revenue AI OS
The Economics
Pricing Model
enterprise-only
per-seat
Starting Price
—
Custom (per-user licensing + platform fee)
Price per Seat
—
Estimated $100-150+/user/month
Cost at Scale
Enterprise pricing — contact sales
Estimated $100-150+/user/month + platform fee; $50K-$300K+/year for teams
Free Trial
No
No
The GTM Utility
Category
Analytics & Revenue Intelligence
Conversation Intelligence
Workflow Stage
Analyze → Close
Analyze
Key Features
- • Revenue forecasting with AI
- • Pipeline management & prospecting
- • Sales engagement & productivity
- • Customer retention & growth
- • Revenue context across all signals
- • Deal inspection and coaching
- • Forecast accuracy optimization
- • Revenue leak identification
- • Cross-functional alignment
- • AI-powered conversation recording and analysis
- • Deal intelligence and pipeline management
- • Revenue forecasting
- • Sales coaching and rep performance tracking
- • Specialized AI agents for workflows
- • Revenue graph (world's richest interaction data)
- • Email and web conference capture
- • Prospecting to expansion coverage
Platforms
Web
Web, Mobile
Ease of Use
Moderate — enterprise platform requiring implementation
Moderate — powerful platform that requires onboarding but intuitive for daily use
The AI Edge
AI Features
AI-powered revenue forecasting, predictive deal scoring, AI pipeline analysis, conversational intelligence
Revenue AI with specialized AI agents, AI-powered forecasting, deal risk scoring, conversation analysis, automated action items
Market Position
Tagline
Enterprise Revenue Orchestration
Revenue AI OS
Best For
Enterprise organizations needing a single platform for revenue forecasting, pipeline management, and sales execution.
Mid-to-large sales organizations that want AI-powered conversation intelligence and revenue forecasting to systematically improve win rates.
Not Great For
Small startups or SMBs — enterprise-focused pricing and complexity make it overkill for small teams.
Solo founders or small teams that can't justify the enterprise pricing for conversation intelligence.
Team Size
enterprise
mid-market/enterprise
Intelligence
Pros
- • 398% ROI validated by Forrester
- • Industry-leading forecasting accuracy
- • Comprehensive revenue orchestration platform
- • Trusted by Fortune 500
- • Strong AI capabilities with revenue context
- • Category-defining conversation intelligence platform
- • Named Leader in 2025 Gartner Magic Quadrant
- • World's richest revenue interaction data
- • Excellent AI agents and forecasting
Cons
- • Enterprise-only — no transparent pricing
- • Complex implementation
- • Overkill for small teams
- • Heavy enterprise sales process
- • Competing with both point solutions and platforms
- • Very expensive — enterprise-only pricing
- • Platform fee + per-user adds up quickly
- • Requires significant call volume to be valuable
- • Can feel intrusive to some sales reps
Reddit Sentiment
mixed
Strong but polarizing. Very well-known on r/sales. Product widely respected for call intelligence, but company culture perceived as cult-like. Sales reps on LinkedIn seen as cringeworthy. Expensive for startups. Frequently compared to cheaper alternatives.
Integrations
- • Salesforce
- • HubSpot
- • Microsoft Dynamics
- • Gmail
- • Outlook
- • Salesforce
- • HubSpot
- • Microsoft Dynamics
- • Zoom
- • Google Meet
- • Microsoft Teams
- • Slack
- • Outreach
- • SalesLoft
Editorial Face-off
The Case for Clari
“Clari is the enterprise standard for revenue orchestration. Its forecasting accuracy and comprehensive platform make it essential for large organizations. The Forrester-validated 398% ROI is compelling. However, it's firmly an enterprise play — startups and SMBs should look elsewhere.”
The Case for Gong
“Gong is the undisputed leader in conversation intelligence and revenue AI, recognized by Gartner as the top platform in the category. It's a transformative tool for mid-to-large sales organizations, but the significant investment only pays off for teams with enough call volume and deal complexity to benefit from the insights.”
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