Globalization Partners improves forecasting accuracy and pipeline visibility with Clari
The problem
Before Clari, Globalization Partners' forecasting was scattered with constantly changing numbers, and reviewing deal status required going through Salesforce deal by deal, consuming significant time especially at quarter end.
Workflow diagram · grounded in source
1
All deals centralized in Clari
Integration
All deals are tracked in Clari, giving the team an accurate depiction of the number each person and team is sitting on.
▾ source quote
“With Clari, all deals are there, so we know exactly which deals we are looking at. We have an accurate depiction of the number each person and team is sitting on”
2
AI deal scoring and prediction
Ai action
Clari assigns scores to deals and generates predictions used to assess which commits belong in a given stage.
▾ source quote
“Deal commits need good scores, high visibility, and a good reason why they are in that stage.”
3
Manager deal inspection
Human review
Samantha inspects each deal, ensuring numbers roll up and flagging deals with low scores or no activity.
▾ source quote
“I'm ensuring all the numbers are rolling up, the deals are tied, and inspecting each deal. Then I can have a conversation with my managers to pluck out the ones that don't look right (in commit, with low score and/or …”
4
Forecast conversation with managers
Human review
Conversations with managers have improved around the actual forecast number and which specific deals will contribute to it.
▾ source quote
“conversations have improved around the actual forecast number, and which specific deals will get them there”
5
QBR reporting via Pulse and Trend tabs
Output
In QBRs, the team screenshots Clari's Pulse and Trend tabs to show the prediction and quarterly trend comparison.
▾ source quote
“In QBRs, we just screenshot Clari's Pulse and Trend tabs to see the prediction and how we are trending compared to the previous quarter, respectively.”
Reported outcome
Forecasting became more accurate, consistent, and transparent, with end-of-quarter reporting reduced to hitting refresh and the sales cycle improving faster by a day or so.
Reported metrics
Sales cycle improvementfaster by a day or so
Forecasting accuracyimproved
End-of-quarter reporting effortreduced to hitting refresh
Forecasting consistencygotten tighter and consistent
Show all 5 reported metrics
sales cycle improvementfaster by a day or so
forecasting accuracyimproved
end-of-quarter reporting effortreduced to hitting refresh
forecasting consistencygotten tighter and consistent
time savings at quarter endwild difference; can't even compare
Reported stack
ClariTrendSalesforce
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Forecasting became more accurate, consistent, and transparent, with end-of-quarter reporting reduced to hitting refresh and the sales cycle improving faster by a day or so.
What tools did this team use?
Clari, Trend, Salesforce.
What results were reported?
Sales cycle improvement: faster by a day or so; Forecasting accuracy: improved; End-of-quarter reporting effort: reduced to hitting refresh; Forecasting consistency: gotten tighter and consistent (source-reported, not independently verified).
How is this sales ops AI workflow structured?
All deals centralized in Clari → AI deal scoring and prediction → Manager deal inspection → Forecast conversation with managers → QBR reporting via Pulse and Trend tabs.
This case is one data point. Whether its pattern fits you depends on your volumes, your stack, and your exception load — that comparison is the step no case study can do for you.