Gong IO: Cutting Through the Noise

Gong IO: Using AI to train and optimize sales professionals


Up until recently, the development of sales professionals was severely constrained. Often considered more of an art than a science, a great salesperson was usually chalked up to innate talent, rather than a rigorous training plan. Gong.io (Gong) sought to change that. Leveraging AI on recordings of sales professionals, it looks to give feedback to those same professionals on ways that they can improve, increasing sales, decreasing average customer acquisition costs, and simplifying evaluation and compensation.

How Gong Works

2022 Super Bowl Commercial

Gong is a software as a service (SaaS) platform focused on the training of sales professionals. It all starts with a simple software extension for whatever video or calling platform your salespeople use. When added to a call, it records the conversation. It also will utilize data from other sources, emails, voicemail, and internal Customer Relations Management (CRM) software. Compiling all these together, a trained AI parses the data and provides feedback to the individual, the manager, and -if desired- the greater organization. Gong has a massive amount of data on the sales process across industries and companies, and leverages this to provide its users with the best path forward. Think like a computer with a chess library giving you guidance as you play a game with a friend. Gong will tell you if you’re talking too much in a call, if your not asking the right questions, beyond that it will see who at the organization your engaging with, if you should reach out more, over what medium you should communicate. Gong wants you to be the best salesperson possible, and it also wants you to be a datapoint to help it learn and grow.

How Gong Works

How it adds value

The insights gleaned from the above are hugely valuable. Keep in mind, before Gong, sales organizations were running in the dark, and Gong -maybe somewhat proudly- likes to proclaim they invented the field of “Revenue intelligence”. While that may be overstating their role, they’re not overstating the benefits. Firms using Gong have lower customer acquisition costs, increased sales, and a more sustainable sales pipeline. Hiring and firing in sales is a constant practice, and metricing professionals can be difficult. Did they not hit quota because they were not a great salesperson? Or did a pivotal deal just fall through due to factors beyond their control. Shining insights that can help answer that allow organizations to retain the best, train the middle, and move on the worst.

A rather unique feature Gong uses to create value is also their role in the greater SaaS ecosystem. Good sales performance is critical for SaaS businesses, and one or two seasoned sales professionals can make the difference required to have revenue for raising either a next round, or being fully cash flow positive. Gong knows this, and makes it’s product incredibly easy for these firms to use, both from an operational side and from a pricing side. They make it easy for a nascent company to use their product, and are sure to capture the monetary upside as those organizations succeed and grow.

Gong’s Results Across Firms

Current Challenges

Currently, Gong faces two main challenges as it looks to grow beyond its current size. The first concern is market competition. SaaS is a notoriously high-margin business with a winner-takes-all mindset, so competition is never far away. Smaller players are rising up with more focused and specialized products and nipping at Gong’s heels.  Firms like Clari are looking to better integrate beyond just the sales organization to create a full-service organizational tracking tool. Avisio is doing very much the same thing as Gong, raising the scary prospect of a price war. At the same time larger players have seen Gong’s success, want it for themselves, and have plenty of resources -both in capital and data- to throw at their products in an effort to unseat them. Microsoft and salesforce are trying to replicate Gong’s success within their own incumbent platforms, which could prove to be an extremely hard moat to bridge by Gong’s team. Microsoft, for example, could integrate Sharepoint and Github functionality for a true-cross disciplinary suite. Salesforce, who’s main customers are large sales organizations, also benefits from a huge incumbent position in most firms, and could likely reach customers faster than Gong.

The second concern is around privacy of data. A constant concern across tech companies, this is exacerbated by Gong’s usage of AI. As part of the value creation process, Gong takes conversations, analyses them, and gives feedback. Not only does this feedback go to individuals, but across teams, and even organizations, in an effort to share “best in class” learnings. However, an AI has to be particularly savvy if it wants to distinguish what it should share -based on quality of learning- from what it CAN share -from a security, privacy, and confidentiality standpoint. A lot of sales processes are highly confidential, and in some industries both sellers and buyers are dealing in confidential information. A lot of customer discovery involves understanding pain points, which requires vulnerability from potential customers. Vulnerability which may not be easy to find if they know an AI might be blasting out parts of their conversation to a wider audience.


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Student comments on Gong IO: Cutting Through the Noise

  1. Very cool post! This is the first time I’m hearing of this company. I can certainly see why a tool like this would be helpful. I once did sales and there were certainly moments where I could have used some coaching or feedback but no one was around. That said, I do wonder about the privacy and also how bias will be handled. Each industry, culture, etc varies so drastically and trying to give “feedback” or “ratings” can certainly be a challenge.

  2. This is super interesting, thanks for sharing Sutton. I would be curious to learn more about the technical challenges they faced when building this solution. For example, were they able to apply this technology across all industries or sales-motions (e.g., technology, consumer, B2B, B2C)? Or did they target one specific kind of salesperson first as they built out the technology? Sounds like a fascinating tool that is already paying off its clients.

  3. Thank you for your post Sutton. This is so promising but I agree with you on the challenges related to the privacy of data. I wonder if Gong and its competitors have made different decisions to address these challenges. Also, do you believe this can be a critical element for differentiation and success in this market?

  4. Really neat to learn how this company approaches this tough problem. I’d be interested to hear more from users on whether they feel like the feedback from the algorithm is effective for them — human interactions are very complex and it’s not obvious to me at all that an algorithm would be able to assess whether someone should talk more or less in a sales call, as it seems very context dependent.

  5. Thanks for the post Sutton – this is a very interesting space! Gong IO’s work reminds me of the recent controversy over Zoom mulling whether or not to implement Intel’s AI to detect bored students (https://www.protocol.com/enterprise/emotion-ai-school-intel-edutech) and also harkens a little to Affectiva’s work.

    I think a lot of the criticisms of AI/facial recognition apply here as well. We keep on thinking that adding more data to the equation will help, but it remains to be seen!

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