Founded in 2015, Gong realized revenue operations could be more efficient. The problem was companies didn't have the data they needed to make this happen. Sellers were using CRMs but weren't exactly consistent in their data entry and keeping it up to date.
Gong's thesis, according to Chief Product Officer Eilon Reshef, was that if a company had enough data, it could leverage AI to automate some of the sellers' work and provide them with guidance. And where is much of this data? It's in customer conversations. So, Gong started recording calls and emails (video, phone, email) and other digital interactions. Then, it applied revenue AI to that data.
What kind of guidance does Gong provide sellers? Things such as:
Gong was ahead of the curve in building a revenue intelligence platform with AI at its foundation. Of course, it was machine learning at the time, but now, it's leaning into generative AI and provide the support sellers need.
Mason Johnson, Senior Product Marketing Manager, cites stats that show why the new product capabilities they introduced are important. According to this data, only 33% of reps met their quota last year. But, if they use their company's methodology and get consistent coaching from their manager, they can attain quota 73% of the time. That's what these new capabilities are intended to help with.
Johnson points to three ways to extract insights from customer interactions: playback review, keyword and filter search, and concept tracking (or what Gong calls Smart Trackers). The first two are time-consuming, and the second one -- keyword review -- is prone to errors because you have to match the exact keyword. The keyword might be used in a different way that doesn't match the search, or a completely different keyword or phrase may be used that won't get picked up.
The pitch here is that Smart Trackers resolve all of these challenges. In Gong, customers can create their own models by narrowing down and honing in on what they want to know. They are training the Gong AI to recognize patterns so that the AI can more accurately detect themes within conversations. The AI will continually self-test itself using the examples it's given. Johnson says:
Once you run it over the 1000s and 1000s of calls or emails, it's going to be 85% accurate. The first-time business users get not only something that works but actually self-tests itself and can tell you what you should expect. And that means you might execute differently because if you're at 50% accuracy, your marketing might work, but you can't tell salespeople to do about it, because it's going to be half garbage. But if you're at 90% accuracy, then you can actually trigger a workflow that says, if this thing happens, why don't you call that customer, etc, etc."
Traditionally, seller playbooks that follow sales methodologies such as MEDDICC, Challenger, and others are followed manually. The seller might have a checklist to mark off what they have done. Reshef argues that this can get tedious, and you can't always be sure the rep is following the rules.
Now, with Gong, the AI will scan emails and calls and apply the playbook for the rep, identifying the things the playbook expects the rep to do. The AI surfaces the information, and the rep can accept or adjust it. This new approach takes an organization from 30-40% compliance to 90%. Reshef says this helps veterans focus and helps new reps adopt the methodology faster:
So now, if the rep is being asked, 'Have you found the decision maker?', rather than them having to remember that they did it three weeks ago and who the decision maker is, the AI comes back and says, 'Hey, here's the decision, whatever process that we all talked about. This is my AI suggestion', and now the seller can accept or reject it, or edit it or tweak it, but it takes all of the thought process and the work and the heavy lifting from this.
Johnson says that Smart Trackers works out of the box with a number of methodologies (playbooks), and customers can define Smart Trackers as their homegrown methodologies. Also, they can dive into the areas where the AI is finding its answers with the click of a button.
Sellers need consistent feedback to improve. Gong uses AI to help managers evaluate and provide feedback to sellers. Reshef said every company has its own methodology for what it expects in the sales conversation. So the manager defines a list of questions, and the Gong AI will review the seller's work and pre-fill the answers with snippets of a conversation for the manager to review.
Again, according to Reshef, AI is about 80-90% accurate, not 100%. Most customers prefer always to give the right feedback, not the right feedback, 80% of the time. He said someone needs to be accountable versus letting AI "rule the world." Instead, AI can guide humans through a process. Reshef concludes:
So again, the way we've taken this to market, from a product perspective, we're not ranking the individuals. That's a product decision. We don't like AI overly monitoring people, just from a culture perspective. But what it does is basically gives the managers like, 'Here's the canned answer, here's what the seller said'. If the question is, for example, 'Did they pitch the right product?', the AI is going to say, 'They pitched this product. They said this, they said that'. And now all the manager or the coach has to do is click a button that says yes, accept or tweak it, and it kind of takes away more than 80% of the work but still holds them accountable.
According to Gong Labs research, sellers that use AI to guide their deals increase win rates by 35%. This makes sense because there is so much customer data to sort through and understand that doing it manually takes too much time and effort, and things fall through the cracks.
If AI can analyze the data and look for things that are important and companies can train the AI on what to look for, it will help drive conversations forward, increase sales, and help sellers get better at their jobs.
Gong wants to be the main system that revenue professionals use daily. But it also offers solutions for marketing and customer success. Reshef said Gong can help marketers eliminate guesswork when developing messaging and campaigns. They can learn the challenges customers face and surface insights to help them develop content that addresses customers' needs. Marketers can also determine if salespeople use their messaging and how customers react.
So, it's a platform for sellers but also a vital tool for marketers who want to better understand their customers and prospective customers. These product updates demonstrate the value generative AI brings to sales - and to marketing.
