Sales ops · Production

Hivebrite transforms forecast accuracy and builds evidence-based sales operations with the Gong Revenue AI OS

The problem

Hivebrite's sales team lacked visibility into deals and performance, coaching was inconsistent and opinion-based, and forecasting relied on subjective judgment with outdated CRM data that led to quarter-end surprises.

Workflow diagram · grounded in source
1
Single source of truth adoption
trigger
“Instead of relying on scattered notes and inconsistent reporting, Gong became the single source of truth the team needed to scale confidently”
2
Conversation intelligence analysis
ai_action
“Equipped with the complete conversation intelligence that Gong brought to the table, managers can identify which behaviors drive success and roll them out as standard practice”
3
Deal progression and risk forecasting
ai_action
“We can now see clearly which deals are progressing and which are at risk. This allows us to plan earlier and with greater confidence”
4
Engagement signal surfacing
ai_action
“contextual signals showing customer engagement frequency, decision maker involvement, and discussion topics”
5
Success pattern discovery
ai_action
“Analysis showed that deals involving our customer success team early in the process had higher win rates and stronger adoption after purchase”
6
Evidence-based coaching and process change
output
“Team meetings are shorter and more focused, and coaching sessions are based on real examples”
Reported outcome

Hivebrite achieved improved forecast accuracy with at-risk deals spotted weeks earlier, saved several hours per manager weekly on forecast preparation, shorter sales cycles, improved win rates, and reduced deal slippage through evidence-based operations.

Reported metrics
Manager time saved weekly on forecast preparationseveral hours a week per manager
Early identification of at-risk dealsweeks earlier than before
Sales cycle lengthshorter sales cycles
Win ratesimproved win rates
Show all 7 reported metrics
manager time saved weekly on forecast preparationseveral hours a week per manager
early identification of at-risk dealsweeks earlier than before
sales cycle lengthshorter sales cycles
win ratesimproved win rates
deal slippageReduced deal slippage
funnel conversionBetter conversion throughout the funnel
forecast reliabilitymore reliable
Reported stack
Gong Revenue AI Operating SystemGong ForecastGong EngageCRM
Source
https://www.gong.io/customers/case-studies/hivebrite-transforms-forecast-accuracy-and-builds-evidence-based-sales-operations-with-the-gong-revenue-ai-os
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Hivebrite achieved improved forecast accuracy with at-risk deals spotted weeks earlier, saved several hours per manager weekly on forecast preparation, shorter sales cycles, improved win rates, and reduced deal slippa…

What tools did this team use?

Gong Revenue AI Operating System, Gong Forecast, Gong Engage, CRM.

What results were reported?

Manager time saved weekly on forecast preparation: several hours a week per manager; Early identification of at-risk deals: weeks earlier than before; Sales cycle length: shorter sales cycles; Win rates: improved win rates (source-reported, not independently verified).

How is this sales ops AI workflow structured?

Single source of truth adoption → Conversation intelligence analysis → Deal progression and risk forecasting → Engagement signal surfacing → Success pattern discovery → Evidence-based coaching and process change.

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