Improving the Sales Process Using Revenue Intelligence
Since just under half our readers hail from around the globe, they may not be familiar with the high-pressure sales tactics used at auto dealerships here in ‘Murica. As soon as you drive up, the salesperson’s goal is to get your car keys so they can “value your trade in.” If that happens, you are not leaving that dealership. They will use every tactic possible to make you stay there until you finally capitulate and sign those papers. You’ll never get your keys back, and if by some miracle you do, don’t be surprised if they physically block the exits to keep you from leaving. Fortunately, there are better ways to close more deals.
We’ve talked before about how natural language processing (NLP) allows computers to understand what we’re saying. Think about how valuable it would be to understand every word exchanged between your sales team and your customers. That value is why Gong.io just became a $2.2 billion company. They’re providing something called revenue intelligence.
We first came across Gong.io a few years back in a piece we wrote on 13 Startups Transcribing Voice to Text Using AI. Since the piece, Gong has raised a lot more money with total disclosed funding at $333 million. Just yesterday, Gong raised a $200 million Series D round valuing the firm at $2.2 billion and making it the 46th AI startup to make the prestigious CB Insights Global Unicorn Club. All this money is being used to fund the latest buzzword term in enterprise sales – revenue intelligence.
What is Revenue Intelligence?
It’s a given that the customer relationship management (CRM) system is a core part of any sales team. It’s how that system gets used – or doesn’t get used – that creates problems. A regional enterprise sales manager would probably experience some of these pain points:
- Opportunities not being up to date based on latest information from client relationship
- Salespeople not entering call notes into Salesforce
- Salespeople not entering meeting notes in Salesforce
- Being blindsided by unexpected cancellations
- Not having some actionable information about why customers are canceling
Revenue intelligence involves examining various customer touch-points – web conferences, phone calls, emails, texts, etc. – and then providing an accurate, automated method of analyzing these interactions for insights and recommended next steps. And it’s all made possible by a form of machine learning called NLP.
Understanding written and spoken words, and then recording this data accurately, is just the start. Being able to understand what’s being said is where the machine learning algorithms can add value. For example, every sales manager has some rock star big swinging dick (BSD) in the office who is often an arrogant prick that everyone secretly dislikes, but who can sell ice cubes to Eskimos. Wouldn’t it be useful to find out what this person gets up to without daring to waste their valuable time with stupid questions? Things you might want to know include:
- How are they structuring their calls?
- What kind of questions were they asking?
- What were they talking about? What weren’t they?
- How do they respond to competitors?
- How do they handle objections?
Gong starts with a simple calendar integration that takes three clicks to set up. Once connected, Gong “scans” each sales reps’ calendar looking for upcoming sales meetings, calls, or demos to record. The “Gong bot” will then join each scheduled sales call as a virtual meeting attendee to record the session. Both audio and video (such as screen shares, presentations, and demos) are recorded. Gong then uses conversation analytics technology to analyze sales calls at the individual and aggregate level.
Gong works 24-7 because those are the hours your global sales team works. Charges are based on the number of BSDs you have that you want to record. And it works great for managing remote sales teams which means it’s getting a boost from “the rona.” An article by VentureBeat on the latest funding round states Gong supports 64,000 sales reps from 1,300 customers.
Gong may be the most visible revenue intelligence company, but they’re hardly the only player in this space.
Update 06/03/2021: Gong has raised $250 million at a $7.25 billion valuation. This brings the company’s total funding to $583 million to date.
Other Revenue Intelligence Startups
This is not an exhaustive list, just a few names we came across that we haven’t written about before. If your sacred cow isn’t listed below, don’t panic. You can avail yourself of our (puts sales hat on) content marketing service where our underpaid MBAs will tell your amazing story to the masses for the price of an average night out in Lan Kwai Fong. Click here for more information. (Takes sales hat off.)
Founded in 2016, San Francisco startup People.ai has raised $100 million in disclosed funding so far from a whole slew of names that include Y Combinator and Andreessen Horowitz. Their revenue intelligence system seems to have similar functionality to Gong.ai. This big ass graphic that’s supposed to explain what they do doesn’t really tell you anything useful, but some poor marketing person likely spent weeks on it, so let’s give them some self-actualization:
The company claims to offer “the industry’s first Revenue Intelligence System,” and they talk about “triple-digit revenue growth” without providing any sort of baseline (absolutely useless information). They make it a point to talk a lot about patents – 39 granted, 84 applications filed – so they’re definitely drawing a line in the sand.
Founded in 2012, Los Angeles startup ringDNA has taken in just over $35 million in disclosed funding with Golden Slacks leading their last round of $30 million which closed in November 2018. Offering similar functionality as Gong, ringDNA has some cool features – like the Intelligent Dialer – which helps sales reps spend more time on the phone with leads. Did you know that dialing leads from a number with a local area code has been shown to boost connection rates by up to 400%? ringDNA will sort all that out for you with a simple app install – and your credit card number.
Conversational Intelligence and Conversational AI
Note that there are loads of startups that capture spoken and written conversations using NLP and then analyze them for insights. What they do may fall under the scope of revenue intelligence, but they just call it something different. Some of these firms label their offering as “conversational intelligence,” something that could also be used to describe “revenue intelligence.” Such technologies can also be applied to other functional departments.
For example, Berlin startup i2x applies NLP to call center operations, something we talked about in our piece on Optimizing Call Center Conversations Using AI. Another company in that genre is Afiniti, one of the most memorable AI startups we met with. What they do is match callers to customer service (CS) reps in milliseconds, making sure the most appropriate CS rep is speaking to the customer. Sounds like a small thing, but the efficiencies they’re creating are huge. Back when we spoke with them about three years ago, they were simply taking a cut of the money they were saving organizations which – they said at the time – far exceeded whatever software-as-a–service (SaaS) pricing model they might have considered using. That’s a perfect example of how a true AI product or service doesn’t just add incremental value, it adds exponential value.
The breadth of nomenclature used by NLP startups is exhausting. Another term you’ll hear thrown around is “conversational AI,” something you can read more about in our piece on Conversational AI for Enterprise Applications. You have Dialpad offering “voice intelligence,” SalesLoft offering a “sales engagement platform,” and Conversica offering “AI sales assistants.” What all these companies have in common is that they’re using NLP to improve the sales process – hyperautomation for sales if you will.
Every software-as-a-service business model focuses on increasing run rate. Revenue increases happen through cross-selling, new customers, price increases, and contract renewals. Revenue decreases occur when customers cancel. Being able to understand what factors contributed to a customer cancel used to be a Salesforce dropdown where half the time, sales reps just chose “Other.” Today, sales managers turn to revenue intelligence to truly understand their customers.
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