Eftsure exceeds targets by 35% and accelerates onboarding with Gong
The problem
Eftsure needed to accelerate new hire time-to-win and gain critical visibility into roughly 600 monthly sales meetings so it could keep deals on track and forecast outcomes more accurately.
First attempt
Traditional CRM tools like HubSpot provided only surface-level pipeline dashboards and could not explain why deals moved forward or stalled, leaving leadership without the insight needed for strategic decisions.
Workflow diagram · grounded in source
1
New hire call library access
Trigger
New hires are given access to a wealth of customer interaction data for on-demand learning from real sales conversations.
▾ source quote
“providing new hires access to a wealth of customer interaction data, offering them invaluable exposure to real-life sales conversations”
2
Call insights for BDMs
Ai action
Gong call insights give BDMs the information they need to close deals, with half now closing within the first 30 days.
▾ source quote
“Thanks to call insights that BDMs get from Gong, half of deals now close within the first 30 days, with an average deal size of around $10,000”
3
Activity scoring and deal warnings
Ai action
Activity scores, call analytics, and deal warnings alert the sales team to potential issues so managers can intervene in time.
▾ source quote
“Activity scores, call analytics, and deal warnings alert them to potential issues, allowing managers to intervene in time to keep deals on track”
4
Deal prioritization by score
Routing
Gong’s scoring system prioritizes deals based on activity levels and the number of stakeholders engaged.
▾ source quote
“Eftsure also relies on Gong’s scoring system to prioritize deals based on activity levels and the number of stakeholders engaged”
5
Forecast insights for leadership
Ai action
Gong Forecast provides leadership with insight into why customers are buying and the dynamics of the sales cycle.
▾ source quote
“Gong Forecast’s insights also directly impacted strategic decision-making at the executive level. The platform provided Sam with essential information about why customers were buying, the value they saw, and the dynamics of the sales cycle”
6
Strategic price increase
Output
Armed with Gong data, leadership implemented a 20 percent price increase that let the company reach 135 percent of its forecast target.
▾ source quote
“we were able to increase prices by about 20 percent overnight, which allowed us to reach 135 percent of our forecast target”
Reported outcome
Eftsure reached 135 percent of its forecast target after implementing a 20 percent price increase, with half of deals closing within the first 30 days at an average deal size of around $10,000, and reduced ramp-up times for new hires.
Reported metrics
Forecast target attainment135 percent
Price increase implemented20 percent
Deals closing within first 30 dayshalf of deals now close within the first 30 days
Average deal size in first 30 days$10,000
Show all 6 reported metrics
forecast target attainment135 percent
price increase implemented20 percent
deals closing within first 30 dayshalf of deals now close within the first 30 days
average deal size in first 30 days$10,000
monthly sales meetings volume600
new hire ramp-up timereduced ramp-up times
Reported stack
GongGong ForecastHubSpot
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Eftsure reached 135 percent of its forecast target after implementing a 20 percent price increase, with half of deals closing within the first 30 days at an average deal size of around $10,000, and reduced ramp-up tim…
What tools did this team use?
Gong, Gong Forecast, HubSpot.
What results were reported?
Forecast target attainment: 135 percent; Price increase implemented: 20 percent; Deals closing within first 30 days: half of deals now close within the first 30 days; Average deal size in first 30 days: $10,000 (source-reported, not independently verified).
What failed first in this deployment?
Traditional CRM tools like HubSpot provided only surface-level pipeline dashboards and could not explain why deals moved forward or stalled, leaving leadership without the insight needed for strategic decisions.
How is this sales ops AI workflow structured?
New hire call library access → Call insights for BDMs → Activity scoring and deal warnings → Deal prioritization by score → Forecast insights for leadership → Strategic price increase.
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.