Your forecast
should be a number
you'd bet on.

You have probably evaluated a few sales forecasting tools already. Maybe you are running one now. The pitch is always the same: connect your CRM, flip on the AI, watch the magic happen.

Then reality sets in.

The model does not understand your sales cycle. It treats a 14-day transactional deal and a 9-month enterprise deal the same way. It cannot distinguish between a pipeline that is healthy and one that is stuffed with stale opportunities your reps forgot to close out. It spits out a number, and your VP of Sales still builds a separate forecast in their head because they do not trust it.

The problem is not the software. The problem is the approach. Off-the-shelf forecasting platforms are built to work "well enough" across thousands of companies. That means they optimize for breadth, not depth. They cannot account for how your deals actually move, which stages matter in your pipeline, or what your conversion patterns look like by segment.

So you end up with a tool that is technically "forecasting" but nobody trusts the number. Your finance team still haircuts it by 25%. Your CRO still runs a parallel forecast in a spreadsheet. And you are paying six figures a year for a dashboard that collects dust.

ORM connects to your existing CRM. Salesforce, HubSpot, Dynamics. No data migration. No integration project. No new workflow for your team to learn.

Within 4-6 weeks, you have a calibrated model delivering weekly forecasts. Each forecast is tracked through time so you can see how the picture changes week over week. And every forecast comes with specific actions your team can execute.

Here is what that looks like in practice:

• Weekly revenue forecasts with 85-95% accuracy, tracked through time
• Prescriptive actions telling your team exactly where to focus
• Pipeline diagnostics broken down by segment, rep, deal source, and stage
• Scenario modeling for headcount planning and quota setting
• A dedicated analyst who knows your business and owns the accuracy of the number
• Board-ready outputs with full methodological transparency

The result: your finance team stops haircutting the sales forecast. Your CRO stops maintaining a shadow forecast in a spreadsheet. And your RevOps team gets their time back from manual pipeline scrubs to focus on actually improving the pipeline.

How ORM compares to other sales forecasting software

The sales forecasting software market is crowded. Clari, Gong, Aviso, HubSpot's built-in forecasting, InsightSquared. They all take a similar approach: give you a platform, let you configure it, and hope your team adopts it.

ORM takes a fundamentally different approach. We do not sell you software. We build a custom model on your data and operate it for you. That means you get the accuracy of a purpose-built forecasting system without the implementation overhead, the adoption risk, or the ongoing maintenance burden.

Want the detailed breakdown? See our full competitive comparison, or read the deep dive on ORM vs. Clari.

For more on how forecasting works at a fundamental level, start with our complete guide to sales forecasting. If you want to understand the metrics that matter, check out forecast accuracy in our glossary. And if you want to see where your current process stands, run your numbers through our Forecast Accuracy Scorecard.