AI & RoboticsNews

Gong Forecast gets AI upgrade, improving accuracy 20% over CRM revenue forecasting

Gong, the revenue/sales team software company that recently introduced its own AI-powered audio/video call summarization and insights generator, Call Spotlight, is continuing to bolster its offerings with new AI features.

Today, the eight-year-old company headquartered in San Francisco announced exclusively to VentureBeat that it is launching a new version of Gong Forecast, its revenue forecasting feature for customers, to use in-house machine learning (ML) models trained on 2.5 billion customer interactions.

Gong claims that Gong Forecast, available now to paying Gong subscribers at no extra cost, is 20% more accurate than relying on customer relationship management (CRM) data alone, a direct shot at Salesforce and Microsoft Dynamics.

“When we think about predictions that are fueled by not just CRM data, but conversational intelligence, real—time customer interactions — those create a much more powerful, precise, accurate prediction,” said Sherry Wu, Director, Product Marketing at Gong, in a videoconference interview with VentureBeat.

According to materials sent over by Gong, the new AI-driven Gong Forecast analyzes approximately 300 distinct “buying signals” gathered from conversations its revenue/sales team customers have with their prospective clients and leads.

These include sentiment analysis beyond just keyword flagging. So, for example, if the topic of pricing comes up in a conversation between a sales representative and a prospective client, Gong’s AI analysis software that is recording and analyzing the call in realtime doesn’t just detect that word alone, but the context surrounding it.

“Just because pricing is mentioned doesn’t mean that’s a good sign,” Wu explained to VentureBeat. “What context is it mentioned in? Is it mentioned in the context of ‘this price is too high for us,’ or is it mentioned in the context of, ‘we have plenty of budget to pay for this and we actually think this price point is fair’? Gong is able to understand the nuance of that context, and then translate that into whether or not that is a positive or negative signal that affects a deals likelihood to close.”

Wu sought to emphasize that while many revenue team members and sales reps still rely on manual data entry into their CRMs or even spreadsheets of customer calls and buying signals, Gong Forecast and the larger Gong Revenue Intelligence Platform could eliminate and automate much of this by simply listening to, automatically transcribing, and analyzing calls and emails.

“The process of creating forecasts is incredibly manual,” Wu said. “It takes a ton of time to cobble together all that information across various data sources…if you’re basing your forecasts on a pretty static system of record, and you’re relying on salespeople to manually input their best guess of reality into that system, those forecasts are kind of like created secondhand. They can be subject to seller bias, they can be inaccurate, they can be out of date.”

Using Gong Forecast, revenue teams can remove bias and eliminate the need for revenue team members/sales reps to be only half listening on their calls while they struggle to take notes and later enter information into their CRMs. Gong Forecast allows them to be more present and use their human “soft skills” to focus entirely on the prospective client and their needs.

In addition, Gong Forecast goes beyond other tools that look primarily at historic deal closing ratios and data to project future deal outcomes.

“We’re able to assign a deal likelihood score to the deals in the open pipeline,” Wu said. “These scores are much more accurate because they’re based on the actual substance of customer interactions. Once we have an accurate understanding of the likelihood [a given deal will close’, we’ll use that to weight the pipeline for a sales leader to know how much revenue are they expected to bring in.”

By using Gong Forecast across sales reps, sales teams can then get a more accurate picture of which deals each rep is expected to close, and from that, the actual revenue the entire team is expected to bring in during a given timeframe, say a quarter.

Wu said that the Gong Forecast kicks in as soon as a customer ports over their audio and CRM data to its platform, and that the forecasting only improves as Gong’s ML algorithms continue to observe and analyze conversations the reps have in realtime. And importantly, though Gong Forecast is based on aggregated data from “thousands of customers” of the firm, it is unique for each sales rep and team.

“We’ll layer on a customer specific model that will learn [each customer’s] business over time and continue to fine tune and tweak those predictions to become even more accurate,” Wu said.

Getting more accurate revenue predictions is one thing — maybe among the most important things — to sales teams and their leadership, and the larger organizations in which they work.

But in order to use Gong Forecast, Call Spotlight, and the larger Gong suite of revenue intelligence tools, the customer does have to turn over lots of proprietary data on their leads and customers to Gong. So how does the company assure its customers and prospective clients that it is taking good care of their data?

“We’ve got enterprise-grade security, we take data and privacy very seriously,” explained Wu. “We ensure the highest level of data protection and governance, and we build everything in house. Everything is kept within Gong.”

I.e., Gong does not share customer data with third-parties. All customer data is siloed and Gong’s ML models train on each silo to derive their overarching predictions across customers.

Wu said that in the modern environment, Gong had received few objections from revenue and sales team to having their conversational data recorded and analyzed.

“Most folks are really open to having Gong enabled because of what it’s able to deliver on the back end,” she told VentureBeat.

Already, the company says more than 250 of its customers are using Gong Forecast worldwide, including digital adoption company WalkMe, which provided an endorsement of the new feature in a press release.

“We use Gong to give our team the data and tools they need to truly understand what is driving their forecast and deal outcomes,” said Sunil Panda, VP Global Revenue and Sales Operations at WalkMe. “With the more complete insights delivered by Gong Forecast, we are able to provide this data and raise the bar for our revenue organization.”

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Gong, the revenue/sales team software company that recently introduced its own AI-powered audio/video call summarization and insights generator, Call Spotlight, is continuing to bolster its offerings with new AI features.

Today, the eight-year-old company headquartered in San Francisco announced exclusively to VentureBeat that it is launching a new version of Gong Forecast, its revenue forecasting feature for customers, to use in-house machine learning (ML) models trained on 2.5 billion customer interactions.

Gong claims that Gong Forecast, available now to paying Gong subscribers at no extra cost, is 20% more accurate than relying on customer relationship management (CRM) data alone, a direct shot at Salesforce and Microsoft Dynamics.

“When we think about predictions that are fueled by not just CRM data, but conversational intelligence, real—time customer interactions — those create a much more powerful, precise, accurate prediction,” said Sherry Wu, Director, Product Marketing at Gong, in a videoconference interview with VentureBeat.

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How Gong Forecast works

According to materials sent over by Gong, the new AI-driven Gong Forecast analyzes approximately 300 distinct “buying signals” gathered from conversations its revenue/sales team customers have with their prospective clients and leads.

These include sentiment analysis beyond just keyword flagging. So, for example, if the topic of pricing comes up in a conversation between a sales representative and a prospective client, Gong’s AI analysis software that is recording and analyzing the call in realtime doesn’t just detect that word alone, but the context surrounding it.

“Just because pricing is mentioned doesn’t mean that’s a good sign,” Wu explained to VentureBeat. “What context is it mentioned in? Is it mentioned in the context of ‘this price is too high for us,’ or is it mentioned in the context of, ‘we have plenty of budget to pay for this and we actually think this price point is fair’? Gong is able to understand the nuance of that context, and then translate that into whether or not that is a positive or negative signal that affects a deals likelihood to close.”

Wu sought to emphasize that while many revenue team members and sales reps still rely on manual data entry into their CRMs or even spreadsheets of customer calls and buying signals, Gong Forecast and the larger Gong Revenue Intelligence Platform could eliminate and automate much of this by simply listening to, automatically transcribing, and analyzing calls and emails.

“The process of creating forecasts is incredibly manual,” Wu said. “It takes a ton of time to cobble together all that information across various data sources…if you’re basing your forecasts on a pretty static system of record, and you’re relying on salespeople to manually input their best guess of reality into that system, those forecasts are kind of like created secondhand. They can be subject to seller bias, they can be inaccurate, they can be out of date.”

Using Gong Forecast, revenue teams can remove bias and eliminate the need for revenue team members/sales reps to be only half listening on their calls while they struggle to take notes and later enter information into their CRMs. Gong Forecast allows them to be more present and use their human “soft skills” to focus entirely on the prospective client and their needs.

Going beyond prior data with intelligent insights about deals still in the pipeline

In addition, Gong Forecast goes beyond other tools that look primarily at historic deal closing ratios and data to project future deal outcomes.

“We’re able to assign a deal likelihood score to the deals in the open pipeline,” Wu said. “These scores are much more accurate because they’re based on the actual substance of customer interactions. Once we have an accurate understanding of the likelihood [a given deal will close’, we’ll use that to weight the pipeline for a sales leader to know how much revenue are they expected to bring in.”

By using Gong Forecast across sales reps, sales teams can then get a more accurate picture of which deals each rep is expected to close, and from that, the actual revenue the entire team is expected to bring in during a given timeframe, say a quarter.

Wu said that the Gong Forecast kicks in as soon as a customer ports over their audio and CRM data to its platform, and that the forecasting only improves as Gong’s ML algorithms continue to observe and analyze conversations the reps have in realtime. And importantly, though Gong Forecast is based on aggregated data from “thousands of customers” of the firm, it is unique for each sales rep and team.

“We’ll layer on a customer specific model that will learn [each customer’s] business over time and continue to fine tune and tweak those predictions to become even more accurate,” Wu said.

Privacy and security remain paramount

Getting more accurate revenue predictions is one thing — maybe among the most important things — to sales teams and their leadership, and the larger organizations in which they work.

But in order to use Gong Forecast, Call Spotlight, and the larger Gong suite of revenue intelligence tools, the customer does have to turn over lots of proprietary data on their leads and customers to Gong. So how does the company assure its customers and prospective clients that it is taking good care of their data?

“We’ve got enterprise-grade security, we take data and privacy very seriously,” explained Wu. “We ensure the highest level of data protection and governance, and we build everything in house. Everything is kept within Gong.”

I.e., Gong does not share customer data with third-parties. All customer data is siloed and Gong’s ML models train on each silo to derive their overarching predictions across customers.

Wu said that in the modern environment, Gong had received few objections from revenue and sales team to having their conversational data recorded and analyzed.

“Most folks are really open to having Gong enabled because of what it’s able to deliver on the back end,” she told VentureBeat.

Already, the company says more than 250 of its customers are using Gong Forecast worldwide, including digital adoption company WalkMe, which provided an endorsement of the new feature in a press release.

“We use Gong to give our team the data and tools they need to truly understand what is driving their forecast and deal outcomes,” said Sunil Panda, VP Global Revenue and Sales Operations at WalkMe. “With the more complete insights delivered by Gong Forecast, we are able to provide this data and raise the bar for our revenue organization.”

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Author: Carl Franzen
Source: Venturebeat
Reviewed By: Editorial Team

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