Cirrus Insight for Gmail
Cirrus Insight is the seller-led, AI-orchestrated Sales Operating System that runs natively alongside Salesforce. For over a decade, we’ve captured and cleaned the relationship history you depends on; automatically logging emails, calendar events, and tasks from Gmail straight into Salesforce, across one or many orgs. The result is trustworthy data that powers real pipeline growth, tighter deal management, and forecasts you can stand behind. Inside the inbox, reps get scheduling, meeting prep briefs, live coaching, and automated follow-ups that keep momentum high. Inside Salesforce, admins and leaders get pristine activity data, configurable capture policies, and native reporting that surfaces what truly drives wins. Cirrus turns everyday GTM activity into a clean, continuous signal, so your Salesforce instance becomes the engine of your revenue, not just a system of record. Cirrus Insight supports all editions of Salesforce including Unlimited, Enterprise, Professional, Group, Contact Manager, and Developer. Cirrus Insight supports Gmail; Outlook 2010, 2013, 2016; Office 365; iOS; Android; and Citrix. Compare to: Revenue Grid Match My Email Gong Chili Piper
Top keywords
- salesforce5×2.94%
- cirrus4×2.35%
- cirrus insight3×1.76%
- insight3×1.76%
- activity2×1.18%
- cirrus insight supports2×1.18%
- data2×1.18%
- gmail2×1.18%
- inside2×1.18%
- insight supports2×1.18%
- revenue2×1.18%
- supports2×1.18%
Einstein Discovery Writeback
READ BEFORE INSTALLING. Einstein Discovery is best used out of the box. We encourage you to use native, no code write-back functionality. Use this managed package only if the native write-back functionality does not meet your business needs. A story includes what happened, why it happened, predictions and recommendations for a given outcome variable. A model is the portion of a story that includes: explanations (why it happened) predictions (what could happen) recommendations (what to do to improve a predicted outcome) Every story includes a desired goal to maximize or minimize the outcome. For example, if you want to predict time to close on an opportunity, you can have separate models for small and large opportunities. You can use this approach if the behavior of your opportunities changes depending on their size. You could create a model on your large opportunities dataset and deploy that to Salesforce. Then you could create a model on your small opportunities dataset and append your small model to the same prediction and recommendation settings. In this context, the model is the segment.
Top keywords
- model5×2.81%
- opportunities4×2.25%
- happened3×1.69%
- includes3×1.69%
- outcome3×1.69%
- small3×1.69%
- story3×1.69%
- dataset2×1.12%