Sales ops ·

How Proposify cut its time spent on forecasting by 25% with help from Gong

The problem

Proposify's sales team lacked alignment on forecasting because data was scattered across Chorus, Salesforce, and their own tool; reps made decisions based on gut feelings and managers had no clear picture of the pipeline.

First attempt

Proposify had been using Chorus for call recording alongside Salesforce, but cross-referencing data across all three systems kept call coaching and forecast coaching separate, and reps were never properly taught to forecast.

Workflow diagram · grounded in source
1
Pipeline review question triggers process
trigger
“how are you feeling about the pipeline?”
2
Centralize deal data across platforms
integration
“Gong integrates with multiple platforms, reps get one dashboard view for all the interactions across an opportunity”
3
Proposal activity pulled into Gong
integration
“Rather than having to go into our software to see the activity on a proposal that's out, we have that information pulling right into Gong”
4
Leaders call accurate forecast numbers
output
“In the first month of using Gong Forecast, Proposify leaders were able to jump in and start calling the numbers with greater accuracy and ease than ever before”
5
Coach reps based on forecasting patterns
feedback_loop
“As we got more data from Gong, you could see on your team who is a bullish forecaster and who's maybe a little too conservative”
Reported outcome

Proposify reduced pipeline review time by 25%, cut its sales cycle by 2.5 weeks, and raised its close rate from 23% to 30%, with the whole organization aligned on a single source of truth for revenue in Gong.

Reported metrics
Pipeline review time25%
Sales cycle length2.5 weeks
Close ratefrom 23% to 30%
Reported stack
GongGong ForecastChorusSalesforce
Source
https://www.gong.io/customers/case-studies/how-gong-helped-proposify-cut-their-sales-cycle-in-half
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

Proposify reduced pipeline review time by 25%, cut its sales cycle by 2.5 weeks, and raised its close rate from 23% to 30%, with the whole organization aligned on a single source of truth for revenue in Gong.

What tools did this team use?

Gong, Gong Forecast, Chorus, Salesforce.

What results were reported?

Pipeline review time: 25%; Sales cycle length: 2.5 weeks; Close rate: from 23% to 30% (source-reported, not independently verified).

What failed first in this deployment?

Proposify had been using Chorus for call recording alongside Salesforce, but cross-referencing data across all three systems kept call coaching and forecast coaching separate, and reps were never properly taught to fo…

How is this sales ops AI workflow structured?

Pipeline review question triggers process → Centralize deal data across platforms → Proposal activity pulled into Gong → Leaders call accurate forecast numbers → Coach reps based on forecasting patterns.

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