<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/6a4c5826d3874a3dab5a3a9962e40bfe&quot; frameborder=&quot;0&quot; width=&quot;1920&quot; height=&quot;1440&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1440</height><width>1920</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1440</thumbnail_height><thumbnail_width>1920</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/6a4c5826d3874a3dab5a3a9962e40bfe-9ff687ea68a4cf63.gif</thumbnail_url><duration>1338.01</duration><title>Pipeline Forecasting</title><description>This Loom explains how to use forecasting in pipelines to get a more realistic view of revenue and spot opportunities slipping through the cracks. It shows the Forecast summary metrics including max potential revenue (all open opportunities value), expected revenue (open opportunity values weighted by stage probabilities such as a $10,000 deal in proposal with 50 percent probability contributing $5,000), one revenue (value marked as one), and total open opportunities. It also highlights at-risk opportunities using warning signals based on expected close date slips and how many times close dates are pushed forward, plus a Fix your forecast data area for missing expected close dates, opportunity values, and overdue items. The Loom concludes with guidance to enable opportunity level pipeline probability and configure stage and opportunity-level probabilities for accuracy.</description></oembed>