Revenue forecasting software for B2B companies: how to pick one (2026)

For a B2B company, the revenue forecast is a model finance keeps and revises every month, so the right revenue forecasting software reads your CRM and billing data and still lets finance own the formulas. That rules out most planning suites as they're usually deployed, and it means the sales-side forecasting tools only solve half the problem.

The market splits in two. Sales-side tools (Clari, Gong Forecast, Aviso, and the forecasting built into Salesforce and HubSpot) predict which deals close this quarter. Finance-side tools (Aleph, Cube, Datarails, Drivetrain, Pigment, Anaplan, Workday Adaptive Planning, Planful) turn bookings, renewals, churn and capacity into a revenue line for the P&L, 12 to 24 months out. Once renewals make up a real share of revenue, a B2B company needs the second kind, fed by the first.

Bottom line: Pick finance-side revenue forecasting software that connects to your CRM and billing system directly and keeps the model somewhere finance can edit it. Aleph is our pick for teams that want live Salesforce, HubSpot and Stripe data inside the Excel and Google Sheets models they already run. Keep a sales-side tool like Clari or Gong for the in-quarter commit call, and feed its number into the finance model rather than replacing it.

What makes B2B revenue forecasting different?

B2B revenue arrives through contracts, and contracts have timing: a signed deal, a start date, a ramp, a renewal date, maybe an expansion. So a B2B forecast is really three forecasts added together, and each one needs a different method.

• Pipeline-weighted (new business). Open opportunities multiplied by the historical conversion rate for their stage, then phased by expected close date and start date. This is what sales-side tools do best.
• Bookings- or contract-based (what's already signed). Revenue from contracts you have, spread over their terms. It's the most reliable piece and the one most often rebuilt by hand from a billing export.
• Cohort and retention-driven (the installed base). Renewals, churn and expansion projected from how past customer cohorts behaved. Once a company has a few years of customers, this is usually the biggest part of next year's revenue.

The third piece is where a forecast usually goes wrong, because retention doesn't stay put. In the 2026 SaaS and AI benchmarks report we co-published with Benchmarkit, gross revenue retention dropped 4 points at every quartile. A model that hard-codes last year's renewal rate will overstate the base. Our pages on gross revenue retention benchmarks and net revenue retention benchmarks show where your numbers sit against peers.

What data does a B2B revenue forecast need?

A forecast you can defend in a board meeting needs four inputs, and they live in four different systems:

1. CRM pipeline: opportunities, stages, amounts, close dates and history (Salesforce or HubSpot).
2. Billing and invoicing actuals: subscriptions, invoices, plan changes and cancellations (Stripe, Chargebee, Maxio, or the ERP).
3. Renewal and churn history: contract end dates and what happened at each past renewal, by cohort.
4. Headcount-driven capacity: how many ramped reps you'll have and what each can close. A sales capacity model template is the usual starting point.

Sales-side tools see input 1 well and the others barely at all. Finance-side tools can hold all four, but only if they connect to the CRM and billing system directly instead of waiting for a monthly export. That's the first thing to test in a demo.

Sales-side vs finance-side revenue forecasting tools

These two categories answer different questions, and buying one when you need the other is the most common mistake in this market.

Sales-side forecasting tools answer "what will we close this quarter?" They score deals from CRM activity, call data and history, and they roll up rep commits into a number for the CRO. They're built for sales and RevOps, they live in a web app, and they're priced per user. They don't model renewals by cohort, spread contracts over their terms, or tie revenue to headcount and the P&L.

Finance-side revenue forecasting software answers "what revenue goes in the plan for the next 12 to 24 months, and what drives it?" These are FP&A platforms with driver-based models. They pull pipeline from the CRM, but they also hold billing actuals, retention assumptions and capacity, and they connect the revenue line to the rest of the plan. This is the category most finance leaders are shopping for, even when they search for "revenue forecasting software."

The split also explains why so many revenue forecasts still live in a spreadsheet next to an expensive planning tool. If the platform makes finance wait on an admin to change a revenue driver, the analyst rebuilds the forecast in Excel and pastes the result back in. Whether a tool is spreadsheet-native or web-based decides how often that happens.

Revenue forecasting software compared (2026)

Of the 14 tools below, the sales-side tools forecast the quarter from CRM data, and only the finance-side tools that connect CRM and billing directly can carry a full B2B revenue model. Details come from each vendor's own site, checked October 2026.

A few notes on the table. "Through ERP or warehouse" means the vendor doesn't list a billing connector, so subscription detail reaches the model only after the GL or a data team has reshaped it. Published prices are from Salesforce's pricing page and HubSpot's Sales Hub pricing as of October 2026; HubSpot's forecasting tool needs Pro or above. None of the finance-side vendors publish a list price.

Which revenue forecasting tool is best for which company?

• Aleph: best for finance teams that want CRM, billing and ERP data live in the Excel and Google Sheets models they already own, with no rebuild in a new interface.
• Cube: best for spreadsheet-first teams that want a planning layer over Excel or Sheets and start the forecast from bookings.
• Datarails: best for Excel-heavy teams whose first problem is consolidating actuals, with revenue forecasting layered on top.
• Drivetrain: best for SaaS finance teams that want a web-based driver model with Stripe and Chargebee connected. Its FAQ says most implementations take 4 to 6 weeks.
• Pigment: best for larger companies running sales and finance planning in one web app, with a warehouse feeding it.
• Anaplan: best for enterprises that want connected planning across sales capacity, territories and finance, and can staff model builders.
• Workday Adaptive Planning: best for companies already on Workday HCM or Financials that want planning from the same vendor.
• Planful: best for mid-market teams that want structured CPM workflows (close, consolidation, planning) in one suite.
• Bob Finance: best for HiBob customers who want headcount and revenue planning near their HR data. HiBob acquired Mosaic in 2025 and relaunched it under this name.
• Clari (Salesloft): best for CROs running a weekly commit call across a large sales team. Clari merged with Salesloft in December 2025; the forecasting product keeps the Clari name.
• Gong Forecast: best for teams already on Gong that want forecasts scored from call and email activity.
• Aviso: best for enterprise sales orgs that want AI deal scoring and also need consumption forecasting from warehouse data.
• Salesforce or HubSpot forecasting: best for smaller teams whose forecast is still mostly new-business pipeline and who want it in the CRM they already pay for.

Two name changes are worth knowing if you're comparing older lists. Runway now operates as cfo.ai and is aimed at founders, and Causal is now part of Lucanet.

How to build a pipeline-weighted revenue forecast: a worked example

Here's the new-business piece for one quarter, in the shape any of the finance-side tools above should let you build:

1. Pull open pipeline by stage from the CRM. Say $4.0M sits in discovery, $2.5M in evaluation and $1.5M in contracting.
2. Apply historical stage-to-close rates from your own last four quarters, not the CRM's default probabilities. If those are 10%, 30% and 70%, expected bookings are $0.4M + $0.75M + $1.05M = $2.2M.
3. Phase by start date. A deal that closes in month 3 with a 30-day start contributes nothing to this quarter's revenue, but it does go into next quarter's.
4. Add the base. Contracted revenue from billing, minus expected churn and plus expected expansion, using cohort renewal rates rather than one blended number.
5. Check it against capacity. If $2.2M of bookings needs more ramped reps than the hiring plan delivers, the pipeline number is the one that's wrong.

The numbers are illustrative. The structure is the point: steps 1 and 2 come from the CRM, step 4 comes from billing, and step 5 comes from the headcount plan. A tool that can't hold all three in one model leaves you stitching them together in a spreadsheet. If you want to start there anyway, Aleph's rolling forecast template already has an ARR bridge built in, and our guide to building a rolling forecast covers the refresh cycle.

When is a CRM forecast or a BI tool enough?

A CRM's built-in forecasting is enough when nearly all your revenue is new business closing inside the quarter and nobody needs the forecast beyond it. It stops being enough once renewals and expansion make up most of next year's revenue, because the CRM doesn't model cohorts or contract terms.

A BI tool is enough for reporting what happened: bookings by segment, pipeline coverage, churn last quarter. It isn't built to hold assumptions, versions and scenarios, which is what a forecast is. Our comparison of FP&A software vs BI tools goes through where that line falls.

What to ask in a revenue forecasting software demo

• Connect our CRM and billing system live in the demo. Which objects come through (opportunities, contracts, subscriptions, invoices)?
• Show a revenue driver being changed by someone in finance, without an admin.
• How do you model renewals and churn by cohort, not as one blended rate?
• How do contract start dates and ramps flow into monthly revenue?
• Can we keep our existing revenue model, or do we rebuild it in your tool?
• What does the forecast-vs-actual comparison look like after close?

If a vendor can only answer the first question with a CSV upload, you'll be rebuilding the forecast by hand every month. For the Salesforce-specific version of this checklist, see the best FP&A tools for Salesforce; for billing, see the best FP&A tools for Stripe and billing systems.

Where Aleph fits

Aleph connects Salesforce, HubSpot, Stripe and your ERP, and puts that data into the Excel and Google Sheets models your team already uses through two-way add-ins. The revenue model stays yours: finance changes the drivers, and the pipeline, billing and actuals underneath it refresh on their own. If your revenue forecast already lives in a spreadsheet next to a planning tool, Aleph lets you keep the spreadsheet and drop the copy-paste. Book a demo to see it on your own data.