Best Sales Forecasting Tools for GTM Teams

Best Sales Forecasting Tools for GTM Teams

Updated June 21, 20262,750 words6 tools compared

Sales forecasting accuracy directly impacts your ability to hit revenue targets and secure investor funding. Yet most GTM teams still rely on spreadsheets and manual pipeline reviews to predict quarterly outcomes. The gap between forecast and actual results costs companies millions in missed opportunities and credibility damage.

Modern sales forecasting tools use AI-driven insights, deal-level visibility, and real-time pipeline data to dramatically improve prediction accuracy. The right platform integrates directly into your sales process, eliminating manual data entry while providing leadership with confidence in revenue projections.

In this guide, we'll review the leading sales forecasting solutions built specifically for go-to-market teams, comparing features, pricing, and use cases to help you select the tool that fits your stage and revenue goals.

Quick Comparison

ProductBest ForStarting PriceRatingKey Feature
ClariEnterprise revenue orchestrationContact sales4.6/5AI-powered pipeline intelligence with deal risk scoring
GongEnterprise conversation intelligenceContact sales4.7/5Revenue AI OS with multimodal signal processing
AvisoMid-market sales forecastingContact sales4.5/5Predictive AI forecasting with deal health scoring
People.aiSales intelligence and forecastingContact sales4.4/5Engagement-based forecasting and deal analytics
DoolySales rep productivity and visibility$50/user/mo4.3/5One-pane-of-glass pipeline management
ChorusEnterprise conversation analysisContact sales4.2/5Call recording and transcription for deal insights
ScratchpadSales execution and forecastingContact sales4.1/5CRM collaboration and deal management
WeflowSales process optimizationContact sales4.0/5Workflow automation and deal tracking
BoostUpSales team enablementContact sales3.9/5Deal tracking with team collaboration features

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Detailed Reviews

In-depth analysis of each platform to help you make the right choice.

#1

Clari

Top Pick

Best For: Enterprise companies with $50M+ ARR requiring predictive revenue forecasting and deal risk management

Clari stands out as the most comprehensive revenue orchestration platform for enterprise GTM teams managing complex, multi-stakeholder deals. Built specifically for large organizations with intricate sales processes, Clari combines AI-powered pipeline intelligence with deal risk scoring to deliver forecast accuracy that rivals human intuition paired with data science. The platform processes deal context across your entire revenue organization, enabling leadership to understand not just what's in the pipeline, but why deals are moving or stalling.

Pricing: Contact sales for pricing. Typically $50,000-$200,000+ annually depending on team size and data volume

Key Features

  • AI-driven deal risk scoring and outcome prediction
  • Real-time pipeline intelligence across all deal stages
  • Revenue context and deal health analytics
  • Collaboration workspace for deal reviews
  • Integrations with Salesforce, HubSpot, and other CRMs

Pros

  • +Highest forecast accuracy among reviewed platforms, with many customers reporting 95%+ accuracy within 30 days of close
  • +Deal risk scoring identifies at-risk opportunities before they slip, enabling proactive interventions
  • +Comprehensive revenue organization visibility allows executives to manage pipeline across multiple teams and geographies

Cons

  • -Significant implementation investment required, typically 8-12 weeks for full deployment
  • -Pricing is enterprise-only with no self-serve option, making it inaccessible for seed-stage startups
  • -Steep learning curve requires dedicated admin resources to maintain data quality and configuration

Verdict

Clari is the top choice for enterprise GTM teams where forecast accuracy directly impacts board meetings and investor relations. If your organization has the budget and complexity to justify enterprise software, Clari's AI-powered insights will pay dividends. However, for companies under $50M ARR, the cost and implementation burden may outweigh benefits compared to mid-market alternatives.

#2

Gong

Best For: Enterprise sales organizations prioritizing conversation quality and deal execution visibility

Gong brings conversation intelligence into the forecasting equation, analyzing call recordings, emails, and meeting interactions to surface signals that predict deal outcomes. The platform's Revenue AI OS processes multimodal data to identify leading indicators of success or failure, moving beyond static pipeline stages to behavior-based forecasting. For GTM leaders who want to understand the quality of conversations happening with prospects, Gong provides unprecedented visibility into what's actually driving deals forward.

Pricing: Contact sales. Enterprise pricing typically ranges from $75,000-$250,000+ annually depending on team size and meeting volume

Key Features

  • AI-powered call and email analysis for deal insights
  • Multimodal revenue signal processing across channels
  • Deal prediction based on conversation patterns
  • Specialized AI agents for different revenue roles
  • Real-time guidance during sales calls

Pros

  • +Captures signals invisible to traditional pipeline tools by analyzing actual customer conversations and engagement patterns
  • +Provides reps with real-time coaching during calls, improving deal quality and increasing win rates
  • +Detailed post-call summaries and insights reduce manual note-taking and improve deal records

Cons

  • -Requires integration with video conferencing tools; some customers report occasional sync issues with multiple platforms
  • -Conversation analysis accuracy can vary depending on audio quality and meeting format
  • -Focus on conversation intelligence means less emphasis on predictive pipeline forecasting compared to Clari

Verdict

Gong is ideal for enterprise organizations that want to combine conversation intelligence with forecasting. If your GTM strategy emphasizes deal quality and rep enablement alongside revenue prediction, Gong's multimodal approach delivers unique value. However, if your primary need is pipeline forecasting accuracy, Clari or Aviso may be more focused solutions.

#3

Aviso

Best For: Mid-market companies ($10M-$100M ARR) seeking AI-powered forecasting with manageable implementation

Aviso delivers predictive AI forecasting purpose-built for mid-market sales organizations, striking a balance between functionality and implementation complexity. The platform uses deal data, rep behavior, and historical outcomes to predict forecast accuracy at the rep, manager, and executive level. Aviso's deal health scoring helps identify which opportunities are progressing normally versus those requiring intervention, making it particularly valuable for GTM leaders who want actionable intelligence without enterprise-scale complexity.

Pricing: Contact sales. Mid-market pricing typically $30,000-$80,000 annually based on team size and data complexity

Key Features

  • Predictive AI forecasting with deal-level probability scoring
  • Deal health scoring identifying at-risk opportunities
  • Rep and manager performance analytics
  • Salesforce-native intelligence for easy adoption
  • Quota and territory management capabilities

Pros

  • +Moderate implementation timeline of 6-8 weeks makes it faster to value than enterprise platforms
  • +Deal health scoring provides clear, actionable insights on which deals need attention
  • +Pricing is significantly lower than Clari or Gong while maintaining strong forecasting accuracy

Cons

  • -Conversation intelligence capabilities are less developed compared to Gong
  • -Customization options are more limited than enterprise-grade platforms
  • -Requires clean Salesforce data; customers with poor CRM hygiene may see reduced accuracy

Verdict

Aviso is the smart choice for mid-market GTM teams that want enterprise forecasting capabilities at a realistic price point. If you're between Series A and Series C with 15-50 sales reps and need to improve forecast accuracy, Aviso delivers strong ROI with a faster path to value than larger platforms.

#4

Dooly

Best For: Growth-stage companies (Series A-B) with 10-50 sales reps prioritizing rep adoption and pipeline clarity

Dooly takes a different approach to sales forecasting by prioritizing rep productivity and pipeline visibility as the foundation for accurate forecasting. Rather than layering AI on top of existing CRM data, Dooly creates a unified workspace where reps live during their day, capturing deal information, interactions, and forecast updates in real-time. This emphasis on user adoption and data quality upstream makes forecasting naturally more accurate without requiring heavy lift from reps.

Pricing: $50/user/month for standard tier; typically $600-$2,500/month for teams of 10-50 reps

Key Features

  • One-pane-of-glass pipeline workspace replacing CRM navigation
  • Real-time deal status updates from reps' primary workspace
  • Conversation intelligence integrations for call insights
  • Deal metrics and velocity tracking
  • Manager dashboards for deal reviews

Pros

  • +Significantly lower cost per user ($50/month) makes it accessible for seed-stage and Series A companies
  • +High rep adoption rates because the tool is designed around rep workflow rather than admin burden
  • +Improves data quality naturally through increased engagement, which directly improves forecast accuracy

Cons

  • -Forecasting AI is less sophisticated than specialized platforms like Clari or Aviso
  • -Requires Salesforce license, adding to total cost of ownership for small teams
  • -Limited customization for unique sales processes or methodologies

Verdict

Dooly is the best choice for early-stage GTM teams that want to improve pipeline visibility and forecasting accuracy without significant AI complexity or cost. If you have 10-50 reps and struggle with data quality in your CRM, Dooly's emphasis on adoption will directly translate to better forecasts.

#5

People.ai

Best For: Enterprise and mid-market companies valuing engagement metrics and objective deal scoring over traditional pipeline analysis

People.ai focuses on engagement-based forecasting, using email, meeting, and call data to predict deal outcomes based on actual customer interaction patterns. The platform automatically captures and scores engagement across all channels, creating a data-driven view of deal momentum that goes beyond pipeline stage. For GTM teams that want forecasting grounded in observable customer behavior rather than rep optimism, People.ai provides objective, quantifiable signals.

Pricing: Contact sales. Pricing typically ranges from $40,000-$150,000 annually depending on team size and data volume

Key Features

  • Automatic engagement capture across email, calls, and meetings
  • AI-powered deal scoring based on engagement patterns
  • Predictive analytics for deal outcome forecasting
  • Account-level engagement tracking and insights
  • Integration with Salesforce, Outlook, and Google Workspace

Pros

  • +Engagement-based scoring reduces bias from rep forecasting optimism common in traditional pipeline methods
  • +Automatic data capture eliminates manual logging, improving data quality and adoption
  • +Clear visibility into customer engagement trends helps identify early warning signs of deal slippage

Cons

  • -Engagement metrics can be misleading in longer sales cycles where decision-making happens offline
  • -Implementation requires access to email and calendar data, raising data privacy concerns for some organizations
  • -Less emphasis on deal health and risk scoring compared to specialized forecasting tools

Verdict

People.ai is a strong option for organizations that want objective, engagement-based forecasting signals. If your sales cycle is 6-12 months and you want to move away from subjective rep forecasting, People.ai's automatic engagement tracking provides the visibility you need.

#6

Chorus

Best For: Enterprise companies with large sales teams prioritizing call recording, rep coaching, and conversation-based forecasting

Chorus provides conversation intelligence specifically designed for enterprise sales teams, recording and analyzing sales calls to extract insights about deal progression and customer sentiment. While primarily positioned as a conversation analysis tool, Chorus contributes to forecasting accuracy by capturing deal intelligence directly from customer interactions. For organizations where call quality and rep coaching are primary concerns, Chorus embeds forecasting insights into the call review process.

Pricing: Contact sales. Typically $60,000-$200,000 annually for enterprise teams with 50+ reps

Key Features

  • Automatic call recording and transcription
  • AI-powered analysis of call dynamics and sentiment
  • Rep-specific coaching recommendations
  • Deal insights extracted from customer conversations
  • Competitive intelligence from customer mentions

Pros

  • +Excellent call recording quality and transcription accuracy supports detailed conversation analysis
  • +Coaching recommendations improve rep performance and deal quality over time
  • +Competitive intelligence extracted from calls provides strategic insights beyond forecasting

Cons

  • -Call recording can create cultural friction if not positioned as coaching rather than monitoring
  • -Forecasting capabilities are secondary to conversation intelligence focus
  • -Requires integration with multiple phone and video systems, adding implementation complexity

Verdict

Chorus is best for enterprise organizations that want conversation intelligence as a primary tool with forecasting as a secondary benefit. If your main goal is improving rep performance through call coaching, Chorus delivers that value alongside deal insights.

Frequently Asked Questions about best sales forecasting tools for gtm teams

Sales forecasting tools improve accuracy through three primary mechanisms. First, they capture real-time deal data automatically through CRM integrations or conversation intelligence, eliminating delays between deal updates and forecast calculations. Second, they apply machine learning models to historical sales data, identifying patterns that correlate with deal closure and pipeline progression speed. Third, they reduce human bias by supplementing rep forecasting with objective signals like customer engagement patterns, conversation sentiment, or deal velocity metrics. In practice, GTM teams using these tools typically improve forecast accuracy from 70-75% (typical spreadsheet-based forecasting) to 90-95% within 30-60 days of deal close. The improvement compounds as the system learns from your specific sales cycle and rep behavior patterns.

Pipeline management tools focus on organizing and tracking deals as they move through sales stages, providing visibility into current pipeline composition and opportunities. Sales forecasting tools go deeper by analyzing deal characteristics, historical outcomes, and leading indicators to predict whether deals will close, when they'll close, and at what probability. Pipeline management answers 'What deals do we have?', while forecasting answers 'Which deals will we actually win and when?'. Tools like Dooly and Scratchpad primarily manage pipelines, while Clari, Aviso, and Gong specialize in forecasting. However, many modern platforms combine both functions—they track pipelines accurately while using that data to power forecasting models. For GTM teams, the distinction matters: if your primary challenge is visibility and organization, a pipeline tool may suffice. If your challenge is forecast accuracy and deal prediction, you need dedicated forecasting technology.

Implementation timeline varies dramatically by platform complexity and your data readiness. Enterprise solutions like Clari typically require 8-12 weeks for full deployment, including data migration, CRM mapping, and user training across multiple teams. Mid-market platforms like Aviso usually take 6-8 weeks, while lighter-weight solutions like Dooly can be operational in 2-4 weeks. However, the critical variable is data quality: teams with clean, accurate Salesforce data move 2-3 weeks faster than those requiring data remediation first. Most platforms front-load implementation effort to ensure accurate AI model training; rushing this phase results in poor forecasting accuracy in month one. Budget 15-20% of expected annual software cost for implementation services. Pro tip: use RevAlign.io to audit your current sales data quality and create a data cleaning plan before tool selection—this dramatically accelerates implementations and improves AI model accuracy.

Seed-stage startups should prioritize Dooly or Scratchpad over enterprise platforms, as both are affordable ($50-100/user/month), implement quickly (2-4 weeks), and don't require substantial upfront data cleanup. At this stage, your primary goal is establishing accurate forecasting habits and pipeline discipline, not building sophisticated AI models. Dooly's per-user model means you only pay for actual sales team members, keeping costs proportional to growth. Alternatively, many seed-stage teams successfully use Salesforce's built-in forecasting with spreadsheet analysis for 12-18 months before graduating to specialized platforms. The critical decision point comes at Series A when you have 10-15+ reps and need forecast accuracy for board reporting—that's when Aviso becomes the right investment. Avoid overengineering forecasting at the seed stage; focus on consistent CRM usage and forecasting discipline first, then layer in AI-powered tools once you have the data volume to make them effective.

Conclusion

Choosing the right sales forecasting tool depends on three factors: your company stage, revenue organization complexity, and forecast accuracy requirements. Enterprise organizations with $50M+ ARR should prioritize Clari for comprehensive revenue orchestration, Gong for conversation-driven forecasting, or Aviso for balanced functionality and implementation speed. Mid-market companies between Series B-C should evaluate Aviso, People.ai, or Dooly based on whether you prioritize deal health scoring, engagement metrics, or user adoption. Early-stage teams should start with Dooly to establish forecasting discipline before investing in specialized AI platforms.

Beyond tool selection, successful forecasting requires clean CRM data, consistent sales methodology, and leadership commitment to using forecast insights for pipeline management. Tools amplify discipline—they won't fix broken sales processes. Before implementing any platform, audit your current sales data quality and establish clear forecast governance, such as weekly deal reviews using consistent probability assessments.

Starting your platform evaluation? Request demos from 2-3 finalists and ask specifically about forecast accuracy guarantees, implementation timeline, and customer success metrics. Most vendors will show you internal ROI case studies, but push for independent customer references willing to discuss realistic accuracy improvements and implementation challenges. The right platform will fit your team size, budget, and forecast maturity level today—not force you to grow into capabilities you don't need yet.

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