How Hivebrite Uses Gong Revenue AI OS to Cut Forecast Slippage

Hivebrite built a platform that helps organizations create and manage engaged communities, growing to serve customers in more than 25 countries out of its Paris headquarters. With 150 employees and ambitions to scale globally, the company’s commercial operations needed to keep pace with its product growth. Revenue predictability became a strategic priority as regional teams multiplied and deal complexity increased.

Before implementing Gong, Hivebrite’s sales leadership operated with limited visibility into deal health. Forecasting relied on subjective rep updates and often-stale CRM data, which meant quarter-end surprises were a recurring problem. Coaching practices varied from one regional team to another, and identifying at-risk opportunities early enough to intervene was more guesswork than process.

Hivebrite deployed the Gong Revenue AI Operating System, which unified conversation intelligence, deal tracking, and forecasting across the team. Gong Forecast replaced manual spreadsheet-driven update cycles by surfacing deal progress signals and risk indicators in real time. Gong Engage gave sellers contextual data on prospect interaction frequency and decision-maker involvement, allowing for more targeted and timely outreach.

The impact was clearest in forecasting: managers gained the ability to identify at-risk deals weeks before they would previously have surfaced, eliminating late-quarter surprises. Forecast preparation time dropped by several hours per manager per week. The team also discovered through Gong’s analytics that involving customer success earlier in the sales process consistently improved close rates and post-sale adoption—a finding they formalized into their standard sales process.

Hivebrite’s shift from reactive to evidence-based sales operations positions the company to scale its commercial organization more confidently as it expands into new markets. The underlying pattern—using AI-derived conversation intelligence to standardize what top performers do and apply it across the team—is increasingly how fast-growing SaaS companies build durable revenue machines.