Channel forecasting software has become essential for B2B sales leaders who need accurate pipeline visibility and reliable revenue predictions. Whether you're managing a direct sales team, channel partners, or a hybrid go-to-market motion, the right forecasting tool can mean the difference between hitting your number and missing quota by millions.
This guide covers 15 of the best channel forecasting solutions available today, including dedicated forecasting platforms, sales enablement tools, and enterprise revenue intelligence systems. We've analyzed each option based on pricing, core features, ease of implementation, and fit for different company stages. Whether you're a Series A startup looking for your first forecasting tool or a growth-stage company evaluating an upgrade, this comparison will help you identify the solution that matches your specific needs and budget.
In-depth analysis of each platform to help you make the right choice.
#1
Aviso
Top Pick
Best For: Mid-market sales organizations with 50-500 sales reps who need accurate quarterly forecasting and deal coaching
Aviso combines conversation intelligence with predictive forecasting, making it an excellent choice for sales organizations that need both visibility into what's happening in deals and accurate revenue predictions. The platform analyzes sales calls and emails to surface risk factors while simultaneously improving forecast accuracy using machine learning models trained on historical deal data.
Pricing: Custom pricing based on number of users and conversation intelligence volume; typically $20,000-$60,000 annually for mid-market teams
Key Features
Call and email transcription with deal intelligence
Predictive risk scoring on opportunities
Automated forecast adjustments based on conversation signals
Sales team coaching recommendations
Salesforce and other CRM integrations
Pros
+Reduces forecast inaccuracy by identifying hidden deal risks through conversation analysis
+Provides both backward-looking insights (what happened in deals) and forward-looking predictions (will this deal close)
+Enables targeted coaching based on actual conversation gaps rather than assumptions
Cons
-Higher price point than lightweight alternatives; requires commitment from entire sales team for maximum benefit
-Conversation analysis quality depends on sales rep adherence to call recording protocols
Verdict
Aviso is the top choice for mid-market teams that want to move beyond simple pipeline spreadsheets. If your team makes deals by talking and you need to forecast accurately, the conversation intelligence layer delivers measurable accuracy improvements. Best suited for companies with $5M-$50M ARR making complex, multi-stakeholder sales.
#2
Salesforce Einstein Analytics
Best For: Enterprise organizations with 500+ sales reps already using Salesforce who want built-in, low-friction forecasting capabilities
Einstein Analytics is Salesforce's AI-powered analytics engine that brings predictive forecasting capabilities to any organization already invested in Salesforce. Rather than replacing your Salesforce setup, Einstein layers intelligent forecasting on top of your existing CRM data, using machine learning to identify patterns and predict outcomes.
Pricing: Add-on to Salesforce; typically $50-$150 per user monthly depending on Salesforce edition and analytics volume
Key Features
Predictive forecasting on custom objects and opportunities
Anomaly detection to flag unusual pipeline movements
Trendpacking and seasonal adjustment
Einstein Discovery for root cause analysis
Native Salesforce integration without APIs
Pros
+No data integration required; works directly with your Salesforce data
+Scales effortlessly to hundreds or thousands of users within Salesforce
+Includes multiple forecasting methodologies (statistical, AI-driven, and hybrid)
Cons
-Can be complex to configure; requires Salesforce admin resources or consulting
-Less specialized than dedicated forecasting platforms; trades depth for breadth
Verdict
Einstein Analytics is the right answer if you're a Salesforce-first organization and want to add forecasting without introducing another vendor. It won't deliver the same specialized intelligence as a dedicated forecasting platform, but it's the path of least resistance for large Salesforce investments.
#3
Xactly
Best For: Companies with channel partner programs, reseller networks, or hybrid direct-and-indirect sales models
Xactly specializes in channel sales and partner incentive management, making it uniquely positioned for organizations with complex multi-tier go-to-market models. The platform combines territory planning, compensation management, and revenue forecasting in a single system designed for indirect sales structures.
Pricing: Custom enterprise pricing; typically $30,000-$100,000+ annually depending on number of partners and forecast complexity
Key Features
Multi-tier partner compensation modeling and forecasting
Territory planning and optimization
Channel partner performance dashboards
Quota management across direct and indirect
Deal registration and influence tracking
Pros
+Only platform that natively handles the unique forecasting challenges of channel sales (attribution, partner reliability, pipeline stages that differ from direct)
+Combines compensation management with forecasting, reducing data silos
+Proven in complex go-to-market scenarios with 50+ channel partners
Cons
-Overkill for purely direct sales organizations; you'll pay for features you don't use
-Implementation typically takes 4-6 months; requires significant data cleanup
Verdict
If you have a channel partner program, Xactly is worth evaluating. It's one of the few platforms that understands that forecasting through partners is fundamentally different from forecasting direct sales. Best for companies with $50M+ ARR and 25+ active channel partners.
#4
People.ai
Best For: Sales organizations where deal velocity and engagement patterns are strong predictors of close probability
People.ai takes a different approach to forecasting by focusing on deal velocity and engagement patterns. Rather than relying solely on forecast category selection, the platform analyzes buyer engagement signals to predict which deals will actually close and which are at risk of stalling.
Pricing: Custom pricing; typically $15,000-$40,000 annually for mid-market teams
Key Features
Automated deal health scoring based on engagement
Buyer committee analysis and stakeholder mapping
Deal momentum and velocity tracking
Forecast confidence scoring
CRM-agnostic deal intelligence
Pros
+Identifies deals that will slip before your sales team enters them in the forecast
+Works with any CRM (Salesforce, HubSpot, Pipedrive, etc.)
+Surfaces engagement patterns that predict close probability more accurately than reps' opinions
Cons
-Requires consistent email and calendar integration; won't work well if team avoids sharing those
-Focused on deal health over rep coaching; less useful for diagnosing what's wrong with opportunities
Verdict
People.ai is the choice for companies that have experienced the pain of reps over-forecasting based on hopeful thinking rather than actual engagement. If your issue is 'deals are closing slower than forecasted,' this platform will help. Works best for teams selling to committees or having long sales cycles.
#5
Dooly
Best For: Series A-B companies with 10-100 sales reps looking for their first structured forecasting tool
Dooly is the lightweight option for teams that want forecast visibility without the complexity of enterprise platforms. It focuses on making it dead simple for sales reps to update their pipeline, which in turn creates accurate, current forecasts without requiring dedicated admin resources.
Pricing: $20-50 per user per month; typical team of 20 reps costs $400-$1,000/month
Key Features
One-click sales updates that sync to CRM
Visual pipeline board with forecast visibility
Mobile app for on-the-go updates
Automated CRM sync to prevent duplicate entry
Simple forecast rollup by rep, team, and company
Pros
+Lowest implementation burden of any platform; teams typically go live in 1-2 weeks
+Reps actually use it because the UX is designed for their workflow, not admin requirements
+Transparent pricing makes budgeting straightforward
Cons
-Limited forecasting methodology; no AI or predictive elements
-Doesn't solve the problem of reps entering incorrect forecast categories
-Best for teams selling straightforward deals; not suitable for complex, multi-stage enterprise sales
Verdict
Dooly is the right tool if you need forecasting right now and don't have the budget or complexity for an enterprise platform. It's saved many early-stage sales teams from the 'nobody trusts the forecast' problem. Ideal for Series A-B SaaS companies with 20-50 sales reps and deal cycles under 90 days.
#6
Salesforce Revenue Cloud
Best For: Large enterprises with 500+ employees and revenue models requiring coordination between sales, finance, and customer success
Revenue Cloud is Salesforce's platform for unified revenue intelligence across sales, customer success, and finance. It combines forecasting, pipeline management, and revenue recognition in a single system designed for companies with complex revenue models or high forecasting accuracy requirements.
Pricing: Custom enterprise pricing starting at $50,000+ annually; typically $100,000-$300,000+ for full implementation
Key Features
Unified forecasting across multiple sales orgs and business units
Revenue recognition automation for complex contracts
Customer health scoring and expansion forecasting
Integrated sales and customer success pipeline
Advanced reporting and analytics
Pros
+Only solution that natively connects sales forecasting with customer success metrics and revenue recognition
+Enables data-driven decisions across entire customer lifecycle
+Handles complex revenue models (subscriptions, usage-based, multi-year with true-ups)
-Overkill for companies with straightforward revenue models
-High TCO due to licensing, implementation, and ongoing managed services
Verdict
Revenue Cloud is the infrastructure play for enterprise organizations making million-dollar decisions based on forecast accuracy. If you have revenue recognition complexity or multiple business units that need unified forecasting, it's worth the investment. Better suited to companies with $100M+ ARR or complex go-to-market models.
#7
Kantata
Best For: Professional services firms, agencies, and product companies with significant services revenue
Kantata (formerly Mavenlink) is built specifically for project-based and services organizations, where traditional sales forecasting breaks down. It combines project management, resource planning, and revenue forecasting to predict cash flow and project profitability.
Pricing: Custom pricing typically $15,000-$50,000 annually depending on user count and modules
Key Features
Project-based revenue recognition
Resource capacity and utilization forecasting
Project profitability and margin tracking
Integrated time tracking and project management
Cash flow forecasting
Pros
+Natively handles revenue forecasting for time-and-materials and fixed-price projects
+Resource planning component prevents over-forecasting due to capacity constraints
+Integrates time tracking, reducing manual forecasting entry
Cons
-Not suitable for pure product sales; features are wasted if you don't have project services
-More complex than needed for simple transactional selling
Verdict
If 20%+ of your revenue comes from professional services or custom work, Kantata's project-based forecasting is worth evaluating. It prevents the common mistake of forecasting resources you don't have available.
#8
Growblox
Best For: Data-driven organizations with 3+ years of historical sales data looking to improve forecast accuracy incrementally
Growblox uses machine learning specifically trained on sales data to improve forecast accuracy over time. Unlike static forecasting rules, Growblox's models adapt as your sales patterns change, reducing the manual adjustment work required each quarter.
Pricing: Custom pricing; typically $20,000-$50,000 annually
Key Features
Adaptive machine learning models trained on company-specific data
Automated forecast adjustments based on pipeline patterns
Deal scoring by probability
Integration with Salesforce and other CRMs
Forecast accuracy metrics and benchmarking
Pros
+Models improve over time; accuracy typically increases 5-10% quarter-over-quarter
+Reduces reliance on rep intuition and manager opinion for forecast category placement
+Transparent about model confidence for each forecast
Cons
-Requires clean historical data; doesn't work well if CRM was recently overhauled
-Implementation takes 4-8 weeks to gather sufficient data
Verdict
Growblox is right if you're already using a CRM effectively and want to add a layer of machine learning to improve accuracy. Best for companies with $10M-$100M ARR that have 3+ years of data and want continuous improvement in forecast quality.
#9
Zendesk Sell
Best For: Series A-B companies with 5-50 sales reps choosing a CRM from scratch
Zendesk Sell is a lightweight CRM with an integrated forecasting module, making it a complete solution for smaller sales teams that don't want to adopt separate forecasting software. It's designed for simplicity and speed rather than advanced functionality.
Pricing: $19-99 per user per month depending on features; team of 20 typically costs $400-$2,000/month
Key Features
Simple CRM with pipeline and opportunity tracking
Basic forecasting by rep and team
Mobile app for sales updates
Email integration and templates
Activity tracking and goal management
Pros
+All-in-one solution; no CRM+forecasting integration hassles
+Simple, low-friction implementation; usually live in days
+Affordable for early-stage teams
Cons
-Forecasting features are basic; no AI or predictive elements
-Doesn't scale well beyond 50 reps; teams often outgrow it
-Limited integrations compared to Salesforce or HubSpot
Verdict
Zendesk Sell makes sense if you're choosing your first CRM and have fewer than 30 reps. It's better than cobbling together a spreadsheet forecast, but you'll likely outgrow the forecasting capabilities within 12-18 months. Good starting point for pre-Series B companies.
#10
Weflow
Best For: Sales teams with highly variable deal progression where standardization would improve forecast accuracy
Weflow focuses on pipeline workflow management with integrated forecasting, emphasizing the mechanics of moving deals through your sales process. The platform helps teams standardize deal progression and creates accurate forecasts as a byproduct of consistent workflow execution.
Pricing: Custom pricing; typically $10,000-$30,000 annually
Key Features
Customizable pipeline stages and progression rules
Workflow automation and deal routing
Stage-specific forecasting weights
Team collaboration and activity tracking
CRM integration and sync
Pros
+Improves forecast accuracy by enforcing deal progression standards
+Helps identify where deals are getting stuck in the pipeline
+Automation reduces manual updating and data entry
Cons
-Requires discipline from sales team to follow defined workflows
-Less helpful if deals have highly variable sales cycles
Verdict
Weflow is useful for teams that have inconsistent pipeline discipline. If reps are in different deal stages for similar opportunities, standardizing the workflow will improve forecast accuracy. Best for teams with $1M-$20M ARR and 10-50 reps.
Frequently Asked Questions about channel forecasting software
Channel forecasting software focuses specifically on predicting revenue and pipeline outcomes, while a CRM is designed to manage customer data and sales activities. A CRM answers 'what deals do we have,' while forecasting software answers 'what revenue will we recognize.' Many modern solutions combine both, but the distinction matters: dedicated forecasting tools use statistical models, machine learning, and deal intelligence to predict outcomes, while CRM-native forecasting typically relies on reps' manual stage selections. For channel sales specifically, forecasting tools often include partner attribution, multi-tier compensation integration, and indirect pipeline visibility that standard CRMs lack. You typically need both, though solutions like Zendesk Sell or Salesforce Revenue Cloud attempt to do both together.
Implementation timelines vary dramatically based on platform sophistication. Lightweight solutions like Dooly go live in 1-2 weeks because they require minimal CRM data cleanup or customization. Mid-market platforms like Aviso or Growblox typically need 4-8 weeks to integrate your CRM, train reps, and tune the forecasting models. Enterprise solutions like Salesforce Revenue Cloud or Xactly often require 6-12 months because they touch multiple business systems (CRM, ERP, compensation management). The hidden factor is data quality: if your CRM has inconsistent opportunity stages, missing close dates, or inaccurate deal amounts, plan to spend 2-4 weeks cleaning data before the platform can generate accurate forecasts. For channel-specific tools like Xactly, add an extra 1-2 months to model partner tiers and deal attribution rules. Budget more time than the vendor's estimate if this is your first structured forecasting system.
While most major forecasting platforms integrate with Salesforce, HubSpot integration is less universal. Platforms like People.ai work with HubSpot and maintain CRM-agnostic positioning. Dooly integrates with HubSpot at the basic level but focuses more on Salesforce. Zendesk Sell is separate from HubSpot entirely. If you're committed to HubSpot, your best options are to either use HubSpot's native forecasting tools (which are basic) or choose a platform like People.ai that treats HubSpot as a native integration rather than an afterthought. Many Salesforce-first platforms like Aviso or Xactly won't have deep HubSpot integration, so confirm during evaluation. The reality is HubSpot's forecasting features have improved significantly, and for teams under 50 reps, HubSpot's native tools may be sufficient before justifying a separate forecasting tool.
Look for three concrete indicators during evaluation. First, ask the vendor for a forecast accuracy benchmark: what percentage of forecasted deals actually close in the predicted quarter, and how does that compare to your current accuracy? Second, request a proof-of-concept where the tool is tested on your actual historical data before purchase. Tools like Growblox and Aviso should be able to show you what your forecast accuracy would have been if you'd used their system over the past 4 quarters. Third, focus on solutions that reduce forecast variance (the gap between high and low forecasts), not just overall accuracy. Many tools improve consistency even if they don't dramatically increase close rates. Finally, measure your baseline forecast accuracy today: calculate the ratio of forecasted revenue to actual revenue for the past 3-4 quarters. If you're 85%+ accurate, incremental improvements will be marginal. If you're below 75%, a dedicated forecasting tool will likely show noticeable improvement within 2-3 quarters.
Channel forecasting has unique requirements compared to direct sales. First, deal attribution is critical: you need to track which partner influenced a deal and how much credit they deserve, since one customer might work with multiple partners. Second, partner-specific pipeline visibility is essential—your partners may have deals you don't know about until they're ready to close. Third, compensation and forecasting must be aligned; if partners are incentivized to overforecast, your forecast will be inaccurate. Fourth, partner reliability scoring matters: some partners consistently overcommit and underdeliver, so forecasts from unreliable partners should be weighted lower. Finally, multi-tier deal tracking helps because deals may progress through one partner to another before reaching you. Xactly is the only platform that natively handles all five of these. If you're evaluating other solutions for channel use, specifically ask how they handle partner attribution, pipeline visibility from partners, and partner-specific forecast adjustments.
The answer depends on your accountability structure. If your sales organization is flat with no managers, forecasting by rep is sufficient. If you have multiple layers of management (reps → managers → directors → VPs), forecast at every level with appropriate scrutiny. Reps often over-forecast their individual deals, but manager-level forecasts are more accurate because managers have perspective across multiple reps. The industry standard is to forecast at the rep level for operational accountability and to roll up to manager and company level for reporting. Most mature forecasting platforms let you do both simultaneously. For channel sales specifically, forecast at both the partner level and the aggregate company level, because individual partners may be optimistic while the overall partner ecosystem is accurate. A common mistake is trying to improve forecast accuracy by moving all forecasting to the manager level; this removes reps' accountability and actually makes forecasts worse. Keep rep-level forecasting as your source of truth.
Conclusion
Selecting the right channel forecasting software depends on your company stage, go-to-market complexity, and existing technology stack. For early-stage companies (Series A-B) with straightforward direct sales, lightweight solutions like Dooly or Zendesk Sell provide sufficient visibility and accuracy without expensive implementation. Teams with 50-200 reps and seeking measurable accuracy improvements should evaluate Aviso or Growblox, which layer intelligence on top of existing CRM data.
If you have channel partners or a hybrid direct-and-indirect sales model, Xactly is the only platform designed specifically for these challenges. For enterprises with 500+ reps and revenue recognition complexity, Salesforce Revenue Cloud or Einstein Analytics provide infrastructure that justifies the higher cost and longer implementation timeline.
The common thread across all successful implementations is clean CRM data and sales discipline. The best forecasting tool in the world can't fix garbage data. Before buying, audit your current forecast accuracy, document your current forecasting process, and identify which specific problems you're trying to solve: Is your issue that forecasts are consistently too high? Too low? Unpredictable? Is visibility into channel partner pipelines the constraint? Once you're clear on the problem, match it to a platform that directly addresses it. Many companies fail at forecasting software not because they chose the wrong tool, but because they expected technology to solve problems that require process discipline. Implementation partners like RevAlign.io can help bridge that gap, ensuring your new platform drives actual behavior change rather than just adding another reporting layer.
Need Help Implementing These Tools?
RevAlign builds GTM flywheels for B2B startups. We integrate your tools into one system where every channel compounds.