Revenue intelligence is software that reads every deal, call and email in a sales team's pipeline, estimates how likely each deal is to close, and adds these estimates into a forecast of the quarter's sales. The pipeline is the set of all deals in progress. The forecast is the estimate of how much will be sold in a period, usually a quarter. Revenue intelligence is also called sales forecasting software, or a revenue platform.
Traditionally, the forecast was built from what each salesperson said. Each week, a salesperson marks some deals as "commit", meaning they are sure the deal will close, and others as "best case". The sales leader adds these up and adjusts them from experience. The result depends on how optimistic each person is. Some salespeople always promise too much. Others hide deals until they are certain.
Revenue intelligence adds evidence. It connects to the CRM, the email system, the calendar and the sales engagement platform. From them it learns, for each deal, how many people at the buyer are involved, when the buyer last replied, whether a meeting is booked and how long the deal has been at its current stage. Conversation intelligence adds what was said on recorded calls, for example whether the buyer mentioned a budget or a competitor. A model trained on the company's past deals compares each open deal with the deals that were won and lost. It gives each deal a score: the likelihood that it will close by the end of the quarter. The model's forecast is the total of each deal's value multiplied by its score. The leader can compare it, side by side, with the forecast that the team submitted.
Say a Noida company sells transport management software to Indian manufacturers. Its target for October to December is ₹12 crore. Its salespeople have marked deals worth ₹9.5 crore as commit. The software's forecast is ₹8.1 crore. Most of the difference comes from three deals. In one of them, worth ₹90 lakh, nobody at the buyer has replied for 24 days, and the only contact there is a junior manager. In another, the buyer's purchase head mentioned a rival twice in the last two calls. The sales leader asks the salespeople on these deals to bring in a senior person from each buyer this week. She reports ₹8.4 crore to the chief executive, not ₹9.5 crore.
The forecast is used beyond sales. It goes to the finance team's financial planning and analysis (FP&A) software, which plans spending and cash. The deals that close go on to incentive compensation management, which works out each salesperson's commission.
The scores are only as accurate as the data. If salespeople do not log their meetings or connect their email, the model sees too little.