BirchStreet Systems grows bookings 70% YoY and achieves 3–5% forecast accuracy with Clari AI
The problem
BirchStreet's CRO faced challenges managing revenue predictably and ensuring accurate, dependable forecasts, and found Salesforce too cumbersome to extract the data needed quickly and easily.
First attempt
Salesforce was the incumbent tool but failed to deliver fast, actionable revenue insights, prompting the CRO to prioritize Clari implementation instead.
Workflow diagram · grounded in source
1
Deal activity monitoring
Trigger
Clari tracks when a deal was last interacted with, including emails sent and meetings held.
▾ source quote
“we can see instantly in Clari when a deal was last, interacted with, when the last time we sent an email out or got a meeting”
2
Copilot conversation analysis
Ai action
Clari's Copilot surfaces key points, concerns, and questions from customer conversations to improve engagement.
▾ source quote
“Clari's Copilot will surface up the key points, the concerns, the questions, and also help identify and improve our engagement with that customer so that the conversation is collaborative and not one-sided”
3
AI deal risk identification
Ai action
Clari's AI identifies risks in deals before they become larger issues.
▾ source quote
“Clari's AI in helping his team identify risks in deals before they become larger issues”
4
Stalled deal flagging via Align
Routing
Copilot and Align tools flag stalled deals and keep multi-threaded engagement on track to reduce cycle times.
▾ source quote
“Clari's Copilot and Align tools flagged stalled deals and reduced cycle times by keeping multi-threaded engagement on track”
5
Executive deal intervention
Human review
BirchStreet's CEO, using Clari visibility, identified a deal requiring deeper engagement and met with a key executive onsite.
▾ source quote
“BirchStreet's CEO – who uses Clari extensively – identified a deal that he had a contact at. He recognized that the deal required a deeper level of engagement, and subsequently met with a key executive onsite”
6
ICP pipeline focus with Groove
Ai action
David's team optimized pipeline coverage using Groove and focused energy on the highest-potential ICP deals.
▾ source quote
“David's team optimized pipeline coverage using Groove and focused energy on the highest-potential ICP deals”
7
AI-driven forecast output
Output
Clari's AI-driven insights delivered forecasts within 3–5% of actuals for eight consecutive quarters.
▾ source quote
“landing within 3 - 5% of actuals for an impressive eight consecutive quarters”
Reported outcome
BirchStreet grew bookings by over 70% year-over-year, achieved forecast accuracy within 3–5% of actuals for eight consecutive quarters, improved win rates by 3–7% across sales stages, and reclaimed 2–4 hours per week per sales rep.
Reported metrics
Bookings growth year-over-year70%
Forecast accuracy variance from actuals3 - 5%
Consecutive quarters of accurate forecasteight consecutive quarters
Win rate improvement across sales stages3–7%
Show all 7 reported metrics
bookings growth year-over-year70%
forecast accuracy variance from actuals3 - 5%
consecutive quarters of accurate forecasteight consecutive quarters
win rate improvement across sales stages3–7%
hours reclaimed per sales rep per week2–4 hours per week
slipped dealsDramatic Reduction in Slipped Deals
sales cycle timesreduced cycle times
Reported stack
ClariCopilotAlignGrooveSalesforce
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BirchStreet grew bookings by over 70% year-over-year, achieved forecast accuracy within 3–5% of actuals for eight consecutive quarters, improved win rates by 3–7% across sales stages, and reclaimed 2–4 hours per week…
What tools did this team use?
Clari, Copilot, Align, Groove, Salesforce.
What results were reported?
Bookings growth year-over-year: 70%; Forecast accuracy variance from actuals: 3 - 5%; Consecutive quarters of accurate forecast: eight consecutive quarters; Win rate improvement across sales stages: 3–7% (source-reported, not independently verified).
What failed first in this deployment?
Salesforce was the incumbent tool but failed to deliver fast, actionable revenue insights, prompting the CRO to prioritize Clari implementation instead.
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.