Sales enablement platform deploys AI to help organizations close orders

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While trying to close a deal, salespeople need to do many different things. Sometimes it’s the things they don’t do or don’t do right that make the difference between selling and not meeting quotas.

The use of artificial intelligence (AI)-powered technologies and services to help salespeople gain an edge is nothing new. Customer relationship management (CRM) giant Salesforce uses AI to provide optimization. Sales automation platform like Revenue net and Business Department use AI to help automate workflows. Startups like Regie Use it to help with content sales and marketing.

Well-funded sales support platform gong has been building its technology using a variety of techniques, including natural language processing (NLP), to help organizations understand sales conversations. In June, the company announced economic pulse help sales staff better understand the status of transactions. While those capabilities are valuable, being able to take actions that actually affect the outcome of the sales process is just as valuable.

Today, gong is taking its AI-powered platform to the next level with the release of a new Public Assistance feature. Gong Assist will help guide organizations to take the best possible steps to close deals.

“Assist really looks at your transactions and sees what the customer said or what they didn’t say, makes recommendations and actually automates those actions for you,” said Amit Bendov, Director. CEO of Gong, told VentureBeat.

The difference between CRM and revenue support is AI

For decades, CRM platforms have been the main repository and tool for sales professionals, helping to keep records of contacts and leads.

In Bendov’s view, the challenge for traditional CRM systems is that they have to rely on the user actually entering the right information to become valuable. That includes not only the prospect’s contact information, but the details of the sales call or email exchange.

“If you think about it, in an average conversation you would exchange 6,000 words and what ends up in your CRM from that conversation is about 30 words, and that is a problem,” said Bendov. speak. “The second issue is that what’s in the CRM is highly subjective and based on the thoughts of the sales reps they’ve heard or their opinions, and that’s subjective and imprecise. “

Deploying NLP to understand what’s being said in voice calls, video meetings, and emails, Gong is using AI to feed more information into the sales process than humans can. Bendov explained that Gong’s data science team performed machine learning (ML) training on sales interactions to build AI models that could accurately summarize content, and infer and recommend recommendations. next step.

Changing the future to sell

To date, Gong’s system has provided capabilities to help an organization understand the trajectory of a transaction and the likelihood that it could close. With Assist, Gong is giving users new tools to influence the future.

“What’s more interesting than predicting the future is actually changing the future,” says Bendov.

Based on the ML training Gong conducted on its client base, its AI model was able to infer best practices for closing deals. For example, the Gong Assist system might recommend that users send a follow-up email to a prospect at a certain time of day. Going a step further, Gong’s AI can also draft the body of the next email.

ML training is based on aggregated anonymized data on the basis of Gong users, as well as ML training on data in the account of a specific Gong customer. Bendov said that the majority of the Gong system uses a self-monitoring ML model that does not require users to manually train or label the data.

Bendov says that the new Gong Assist feature is intended to help organizations manage deals with existing customers, reduce churn, and increase win rates. Going forward, he said that in 2023, Gong will expand Support to help organizations find new leads.

“We are creating a system that can search with greater accuracy and generate specific messages for specific people at the right time, based on [an] Bendov said.

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