# The 11 Best Sales Forecasting Software Tools

> The best sales forecasting software is Clari for its purpose-built revenue platform, followed by Gong for its conversation intelligence-driven insights and Aviso AI for its predictive accuracy.

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- Last verified: 2026-06-14
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## Ranking

### #1 Clari · 9.2/9.4
- Best for: Enterprise and high-growth RevOps teams needing the most complete, purpose-built platform for managing and predicting revenue.
- Sunnyvale, USA · founded 2013 · $$$$ (Custom Quote)
- Clari is the best sales forecasting software because it provides the most mature and dedicated platform for governing the entire revenue process, from pipeline inspection to board-level reporting.
- Pro: Its RevenueDB technology captures a vast amount of signal data from emails, calendars, and CRM, giving its AI models a rich dataset for highly accurate, real-time predictions.
- Con: The platform's power comes with a high price tag and a level of complexity that can be overkill for smaller sales teams without a dedicated RevOps function.
- Risk signals (none, checked 2026-06-14): No material public risk signals as of 2026-06-14.

### #2 Gong · 9/9.4
- Best for: Sales teams who want forecasting grounded in the reality of customer conversations and rep activities.
- San Francisco, USA · founded 2015 · $$$$ (Custom Quote)
- Gong ranks this high because its best-in-class conversation intelligence provides a qualitative layer to forecasting that quantitative-only tools miss, identifying deal risk based on what is actually said in sales calls.
- Pro: The platform's ability to automatically surface deal warnings, competitor mentions, and buyer sentiment from calls and emails provides managers with early indicators that CRM data alone can't offer.
- Con: While its forecasting is powerful, it's an outcome of its primary conversation intelligence engine, making it a less direct or customizable forecasting tool than a platform like Clari.
- Risk signals (none, checked 2026-06-14): No material public risk signals as of 2026-06-14.

### #3 Aviso AI · 8.8/9.4
- Best for: Data-driven sales organizations looking for highly accurate, AI-powered deal-level predictions and long-range forecasting.
- Redwood City, USA · founded 2012 · $$$$ (Custom Quote)
- Aviso AI earns its spot with a deep focus on predictive AI, using its time-series database to deliver exceptionally accurate win-score predictions and forecast calls at the individual deal level.
- Pro: Its AI models are particularly effective at identifying which deals in the 'commit' category are truly at risk, allowing managers to focus coaching efforts with precision.
- Con: The user interface, while powerful, can feel less intuitive and modern compared to competitors like Gong and Clari, potentially impacting broader sales rep adoption.
- Risk signals (none, checked 2026-06-14): No material public risk signals as of 2026-06-14.

### #4 Salesforce Sales Cloud · 8.5/9.4
- Best for: Companies deeply embedded in the Salesforce ecosystem that prefer a native, highly customizable forecasting solution.
- San Francisco, USA · founded 1999 · $$$ ($75 to $300/user/mo)
- Salesforce provides the best native forecasting solution, leveraging its position as the central CRM to offer unmatched data integrity and infinite customizability for teams that live and breathe its platform.
- Pro: The direct integration with opportunity data, quoting, and custom objects means there are no data sync issues, and forecasting can be tailored precisely to a company's unique sales process.
- Con: Its native capabilities lack the automated activity capture and advanced AI of dedicated tools, often requiring manual data entry and expensive add-ons like Sales Cloud Einstein to approach their accuracy.
- Risk signals (none, checked 2026-06-14): No material public risk signals as of 2026-06-14.

### #5 HubSpot Sales Hub · 8.3/9.4
- Best for: SMB and mid-market companies using the HubSpot platform who need a simple, integrated, and easy-to-use forecasting tool.
- Cambridge, USA · founded 2006 · $$$ ($450 to $1,500/mo for teams)
- HubSpot Sales Hub is the best choice for simplicity and value, offering straightforward forecasting tools directly within its widely adopted CRM platform, making it exceptionally easy for SMBs to adopt.
- Pro: The tool is incredibly intuitive for sales managers, allowing them to set up revenue goals and view forecast submissions in minutes without needing a dedicated administrator or RevOps team.
- Con: Its forecasting capabilities are less sophisticated than dedicated platforms, lacking the deep AI-driven insights and flexibility required for businesses with complex sales hierarchies or multi-channel revenue streams.
- Risk signals (none, checked 2026-06-14): No material public risk signals as of 2026-06-14.

### #6 BoostUp.ai · 8.1/9.4
- Best for: RevOps leaders seeking a unified platform that combines forecasting with deep pipeline and activity risk analysis.
- Santa Clara, USA · founded 2018 · $$$ (Custom Quote)
- BoostUp.ai provides a strong, unified revenue operations and intelligence platform that excels at identifying deal risk through multi-factor analysis, making its forecasts more reliable.
- Pro: The platform's risk intelligence is a key differentiator, flagging issues like single-threaded deals or a lack of recent engagement directly within the forecasting workflow.
- Con: As a smaller player compared to Clari or Gong, its brand recognition is lower, and its product roadmap may evolve more rapidly, which can be a concern for large enterprise deployments.
- Risk signals (none, checked 2026-06-14): No material public risk signals as of 2026-06-14.

### #7 InsightSquared (by Mediafly) · 7.9/9.4
- Best for: Sales leaders who prioritize deep, visual analytics and historical trend analysis alongside their forecasting.
- Boston, USA · founded 2010 · $$$ (Custom Quote)
- InsightSquared stands out for its powerful sales analytics engine, offering some of the most detailed dashboards for pipeline health, sales cycle analysis, and rep performance to support forecast assumptions.
- Pro: Its pre-built reports and visualizations are excellent for diagnosing the 'why' behind a forecast, quickly showing metrics like pipeline coverage, stage conversion rates, and deal velocity.
- Con: Since its acquisition by Mediafly, the product focus has broadened to the full revenue enablement lifecycle, with less singular focus on being a best-of-breed forecasting tool.
- Risk signals (none, checked 2026-06-14): No material public risk signals as of 2026-06-14.

### #8 People.ai · 7.7/9.4
- Best for: Enterprise sales teams focused on improving rep productivity and data hygiene as the foundation for accurate forecasting.
- San Francisco, USA · founded 2016 · $$$$ (Custom Quote)
- People.ai earns its place by focusing on the root cause of bad forecasts: poor data. Its core strength is automatically capturing all sales activity and mapping stakeholder relationships to build a clean data foundation in the CRM.
- Pro: The platform is unmatched in its ability to automatically create and enrich contacts in the CRM based on email and calendar activity, saving reps hundreds of hours of manual data entry.
- Con: The forecasting and analytics features are less mature than the data capture engine, serving more as a valuable output of the clean data rather than a standalone, best-in-class forecasting module.
- Risk signals (none, checked 2026-06-14): No material public risk signals as of 2026-06-14.

### #9 Xactly Forecasting · 7.5/9.4
- Best for: Organizations that want to tightly couple their sales forecasts with sales compensation and territory planning.
- San Jose, USA · founded 2005 · $$$ (Custom Quote)
- Xactly Forecasting is a strong contender for companies already using its industry-leading sales performance management (SPM) tools, as it connects forecasting directly to quota and compensation planning.
- Pro: The ability to model the impact of different forecast scenarios on commission payouts and attainment is a unique feature that directly links planning to rep motivation.
- Con: As a standalone forecasting tool, it lacks the deep AI-driven deal insights and automated activity capture of the revenue intelligence platforms that lead this list.
- Risk signals (none, checked 2026-06-14): No material public risk signals as of 2026-06-14.

### #10 Zoho CRM · 7.2/9.4
- Best for: Small businesses and cost-conscious teams looking for an all-in-one CRM with capable, built-in forecasting features.
- Chennai, India · founded 1996 · $ ($14 to $52/user/mo)
- Zoho CRM provides the best value for small businesses by including a solid, customizable forecasting module as part of its affordable, all-in-one CRM suite.
- Pro: Its AI-powered assistant, Zia, can provide forecast predictions and identify anomalies, offering a level of intelligence not typically found in CRMs at this price point.
- Con: The forecasting is entirely dependent on manually entered CRM data and lacks the automated activity capture and deep analysis to be truly predictive for complex sales cycles.
- Risk signals (none, checked 2026-06-14): No material public risk signals as of 2026-06-14.

### #11 [WILDCARD] Tableau · 7/9.4
- Best for: Highly analytical RevOps or data science teams that want to build completely custom forecasting models from the ground up.
- Seattle, USA · founded 2003 · $$ ($70/user/mo for Creator)
- Our wildcard pick, Tableau, is not a sales forecasting tool but a powerful business intelligence platform that allows expert users to build bespoke, sophisticated forecasting models that are impossible with out-of-the-box software.
- Pro: Its unparalleled flexibility allows you to connect and blend data from dozens of sources (CRM, ERP, marketing automation) to create predictive models that precisely match your business logic.
- Con: It requires significant data science and analytics expertise to build and maintain, is not a plug-and-play solution, and provides none of the sales-specific workflows like pipeline inspection or activity capture.
- Risk signals (none, checked 2026-06-14): Tableau is owned by Salesforce, a stable, publicly traded company.

## FAQ

**What are the most common sales forecasting methods?**

The most common methods include opportunity stage forecasting (based on deal progression), historical forecasting (based on past performance), and intuitive forecasting (based on sales rep judgment). Modern software often blends these with AI-driven predictive models for higher accuracy.

**How can I improve my sales forecast accuracy?**

You can improve accuracy by enforcing consistent CRM data entry, using a weighted pipeline based on historical conversion rates, and incorporating activity data (emails, meetings) as leading indicators. Adopting a dedicated forecasting tool automates much of this process.

**Is Excel good enough for sales forecasting?**

Excel can work for very small teams with simple sales cycles, but it is not ideal. It's manual, prone to errors, lacks real-time data, and cannot provide the AI-driven insights or automated data capture of specialized software.

**What is 'revenue intelligence' and how does it relate to forecasting?**

Revenue intelligence is a broader category of software that captures and analyzes customer interaction data (emails, calls, meetings) to provide insights across the entire revenue process. Sales forecasting is a key output of a revenue intelligence platform, using that rich data to make more accurate predictions.