Best Sales Forecasting Software 2026: Top 10 Reviewed
93% of sales leaders can't forecast within 5% accuracy. The right software changes that with AI and data.
Key Takeaways
- Best overall: Clari (revenue intelligence leader)
- Best for conversation data: Gong (call-based forecasting)
- Best native to CRM: Salesforce Einstein (built-in AI)
- Best for mid-market: InsightSquared (analytics focus)
- Best for startups: HubSpot Forecasting (included free)
- Best spreadsheet alternative: BoostUp (rep-friendly)
Top 10 Sales Forecasting Software
1. Clari
Best overall
- Revenue intelligence platform
- AI-based predictions
- Pipeline analytics
- Deal inspection
- Price: Custom ($50K+/year)
2. Gong Forecast
Best conversation intelligence
- Call data + forecasting
- Reality vs. rep opinion
- Deal warnings
- Board-ready reports
- Price: Custom (add-on to Gong)
3. Salesforce Einstein
Best native to CRM
- Built into Salesforce
- Opportunity scoring
- AI predictions
- Pipeline inspection
- Price: Included in higher tiers
4. InsightSquared
Best analytics
- Pre-built reports
- Pipeline analytics
- Historical trends
- Rep performance
- Price: Custom
5. HubSpot Forecasting
Best for startups
- Free in HubSpot CRM
- Simple interface
- Team views
- Historical tracking
- Price: Included in Sales Hub
6. BoostUp
Best rep-friendly
- Replaces spreadsheets
- Buyer engagement signals
- Risk identification
- Mobile-friendly
- Price: Custom
7. Aviso
Best AI-native
- AI-first architecture
- WinScore predictions
- Time series analysis
- Coaching insights
- Price: Custom
8. People.ai
Best activity capture
- Automatic data capture
- Relationship mapping
- Activity analytics
- AI recommendations
- Price: Custom
9. Revenue.io (formerly RingDNA)
Best real-time
- Real-time guidance
- Conversation intelligence
- Pipeline management
- Coaching
- Price: Custom
10. Xactly Forecasting
Best for comp data
- Forecasting + compensation
- Performance analytics
- Planning integration
- Territory optimization
- Price: Custom
Comparison Table
| Software | Best For | AI Forecasting | Starting Price |
|---|---|---|---|
| Clari | Overall | Yes | Custom |
| Gong | Conversations | Yes | Add-on |
| Einstein | Salesforce users | Yes | Included |
| InsightSquared | Analytics | Yes | Custom |
| HubSpot | Startups | Basic | Free |
| BoostUp | Ease of use | Yes | Custom |
| Aviso | AI-native | Yes | Custom |
| People.ai | Activity data | Yes | Custom |
| Revenue.io | Real-time | Yes | Custom |
| Xactly | Comp + forecast | Yes | Custom |
Key Features to Compare
Forecast Methods
- Rep roll-up: Sum of rep forecasts
- AI prediction: Machine learning models
- Weighted pipeline: Probability × amount
- Historical trending: Past performance patterns
Data Sources
- CRM data (opportunities, activities)
- Email and calendar
- Call recordings
- Buyer engagement signals
Inspection Tools
- Deal health scoring
- Risk identification
- Next step suggestions
- Commit vs. best case views
Reporting
- Board-ready decks
- Trend analysis
- Team comparisons
- Scenario modeling
Forecasting Best Practices
Weekly Forecast Process
- AI baseline: Start with model prediction
- Rep input: Adjust based on deal knowledge
- Manager review: Challenge assumptions
- Call review: Verify with conversation data
- Commit: Final number with confidence range
Common Forecast Categories
- Commit: Will close this period (90%+ confidence)
- Best case: Could close with everything going right
- Pipeline: Total opportunities in period
- Upside: Deals that could pull in
Avoiding Sandbagging
- Track historical accuracy by rep
- Use AI as independent benchmark
- Inspect deals individually
- Tie accuracy to performance reviews
Forecast Accuracy Benchmarks
| Accuracy Level | Typical Result |
|---|---|
| Excellent | Within 5% |
| Good | Within 10% |
| Average | Within 15% |
| Poor | Over 15% variance |
Most companies: 10-20% variance With AI tools: 5-10% variance achievable
FAQ
Can forecasting software really improve accuracy?
Yes. AI-based tools typically improve accuracy by 20-30% by removing rep bias and analyzing more data signals than humans can process.
How much historical data do I need?
Minimum 1-2 years for meaningful AI predictions. Less data = less accuracy. Start with simpler methods while building history.
Should forecasting be separate from CRM?
Depends on complexity. Built-in tools (HubSpot, Einstein) work for simple needs. Dedicated tools (Clari, Gong) add AI and inspection for enterprise.
What's the biggest forecasting mistake?
Over-relying on rep input. Reps are optimistic. Use multiple data sources and AI to balance subjective assessments.
How often should forecasts update?
Weekly minimum. Real-time for high-velocity sales. The best tools update automatically as deal data changes.
Want AI-powered pipeline intelligence? Dewx GTM Hub tracks deals and predicts close probability based on engagement signals.
