The State of B2B Revenue in the Age of Intelligence

2023 Annual Report: Unlocking The Revenue Potential of AI for B2B

Revenue teams can access more information than ever before. So why haven’t their jobs gotten any easier? Find out now.

June 5, 2023 —

The 6sense Team

Chapter 1

Introduction

Chapter 2

The State of B2B Revenue Production

Chapter 3

Challenge #1: Buyers Prefer to Remain Anonymous

Chapter 4

Challenge #2: The Buying Process is More Complex

Chapter 5

Challenge #3: Revenue Teams Need to Be Increasingly Aligned & Efficient

Chapter 6

No Longer A Novelty, AI is A Necessity

Chapter 7

Where to Start: Practical AI Applications Across the Revenue Team

Chapter 1

Introduction

For the past two decades, businesses have amassed exabytes of data — that’s several billions of gigabytes — that could revolutionize every aspect of how we work.

Yet sellers and marketers are struggling to work effectively. Despite working harder and being armed with new tools and limitless information, they’re still missing pipeline and revenue targets. Why?

We’ve reached a data tipping point. B2B revenue teams now have so much data, they can’t make sense of it all. What should have been a path to clarity has instead become a convoluted journey of noise and guesswork.

The outcomes for B2B revenue teams are dire: low-quality pipeline, lackluster conversion rates, and a shocking amount of go-to-market (GTM) waste — a combined $2T per year, according to Boston Consulting Group.

We’ve now realized that information is easy to collect — but without the ability to convert it into usable intelligence, it doesn’t do much good. And distilling massive amounts of data is more than human brains, spreadsheets, and a disparate collection of apps can accomplish.

Intelligence is what you get when you turn data into insights that drive revenue growth. It’s what empowers marketers and sellers to take meaningful actions, like:

Creating hyper-targeted, personalized interactions with buyers who prefer to conduct research anonymously
Uncovering prospective customers (aka “accounts”) that are in-market and interested in what you’re selling
When contacts self-identify through form-filles, acquiring clues about their engagement

Gleaning intelligence from this epic volume of data can’t be accomplished by tweaking systems and processes that have worked in the past. It requires sophisticated technology built to handle massive amounts of data. Namely, it requires the help of artificial intelligence (AI).

Without AI, it’s nearly impossible to predictably grow revenue in today’s modern buying environment, which by the day is growing more anonymous, complex, and prone to waste and misalignment.

Armed with AI, revenue teams have an unprecedented opportunity to make sense of the virtually unlimited depth and breadth of information at their disposal. It extracts invaluable signal from all that noise.

To understand the true impacts of AI on revenue production, we analyzed the performance of 420 6sense customers who have used big data and AI to power their revenue teams for four quarters — enough time to fully implement the tools and accurately measure their effects. These customers ranged from early-stage startups to Fortune 100 companies.

This report will demonstrate what we found based on real customer data. It will offer suggestions for how revenue teams can use AI to:

Create high-quality pipeline
Convert that pipeline to revenue, and
Reduce waste across the GTM process

Let’s take a closer look.

Chapter 2

The State of B2B Revenue Production

After a decade-plus of growth at all costs, B2B revenue teams now face a new era of belt-tightening. Economic uncertainty brought on by the pandemic, global instability, and widespread inflation ushered in a demand for intelligent, predictable, and profitable growth — often with reduced or flat budgets.

Meanwhile, during that decade-plus of growth, buying behavior changed in key ways that led to a phenomenon we call “revenue team inflation” — the ballooning of sales and marketing resources required to garner the same results. Much like buying the same items at the grocery store now costs more than it did a few years ago, achieving the same revenue results we’ve long enjoyed now takes considerably more time, effort, and expense. (At 6sense, for example, it now takes us twice as many touches as it once did to progress an account to a stage 2 opportunity.)

Another challenge has also arisen: Marketers and sellers must be in more places at once to effectively engage with prospects. McKinsey reports that B2B buyers are using more channels when researching potential vendors — up to 10 channels in 2021, compared to five in 2016. And yet, of 18 potential buying signals that reveal buyer activity in these channels, 88% of marketers report using fewer than half.

These days, we must also market and sell to more individuals for each deal. Buying groups, which were about 6 to 10 people a few years ago, now include 14 to 23 people, according to Gartner.

The phenomenon of 'revenue team inflation' means it now takes considerably more effort to achieve the same results than it did a few years ago.

This has made life harder for all members of the revenue team. Take BDRs (Business Development Representatives), who work under intense pressure to generate new business opportunities and meet targets within a fast-paced, highly competitive environment.

These professionals say their jobs have only gotten harder. In fact, only 30% of them achieved 90% or more of their quota goal in the past year, compared to 34% the previous year — a clear indication that BDR productivity and effectiveness are slipping.

The three main reasons B2B revenue teams are facing these challenges are:

Let’s delve further into these challenges and explore how AI can help with each.

Chapter 3

Challenge #1: Buyers Prefer to Remain Anonymous

In the past two decades, as the buying process has increasingly morphed into a digital one, sellers and marketers adjusted to reach their buyers. One way was by “gating” educational content and requiring visitors to fill out a website form with contact information before they could access the material.

Buyers got wise to this lead generation tactic — especially after they were bombarded by unsolicited emails and unwanted phone calls. Suddenly, buying teams weren’t big fans of marketers and sellers. Today, less than 3% of B2B buyers today identify themselves to vendors by filling out a form.

That means that 97% of the buyers that revenue teams work so hard to drive to their websites are going unnoticed, even as they’re actively showing that they’re in market and primed to buy.

With dramatic behavior changes like these, revenue teams can’t rely on old marketing tactics like form fills, blast emails, and cold calls. In order to even know who’s in market to buy what they’re selling, they need visibility into what we call the “Dark Funnel™” — all the many thousands of websites, social networks, and channels across the digital universe where buyers conduct their research anonymously.

The Dark Funnel is a trove of buyer intent information that revenue teams historically haven’t been able to access. This invisible data is essential for modern selling and marketing — the kind that rapidly moves accounts through the sales funnel.

One main source of Dark Funnel data is a company’s own website. Accessing that data requires de-anonymizing web traffic in order to attach buying signals to the accounts that are sending them. And yet, recent 6sense research found that only 26% of B2B organizations de-anonymize their web traffic.

Yet another truth about how B2B organizations buy is that they conduct only a small percentage of their buying journey on vendor websites. According to Gartner, the percentage of time spent on vendor websites is only 17% of the buyer’s journey itself. Because buyers evaluate multiple vendors, any given B2B provider is likely to see only a fraction of that 17%.

Other places buyers conduct their research anonymously — and leave behind important signals of intent to buy — include:

Industry publications
Blogs
Social networks

Influence outlets
Product review sites like G2 and TrustRadius
And more…

The intent signals buyers leave behind in these channels brim with incredibly useful and actionable intent data. The game changes when you can combine these disparate intent signals into a cohesive picture that informs the entire revenue team.

So in addition to de-anonymizing traffic on their own sites, revenue teams need intent data from third-party sources to paint a complete picture of which accounts are in market for what they’re selling. And also importantly, they can determine who isn’t ready to buy.

No more than 10% of the accounts in a company’s Ideal Customer Profile are in market to buy at any time. AI reveals these highly valuable (if fewer) accounts that deserve meaningful engagement.

Of course, knowing that an account is in market only gets you so far. You also need to be able to act on that information. Doing so requires having up-to-date buyer contact data ready at just the right time. But our research shows that revenue teams don’t even have contact information for 78% of companies that are in-market for their solutions. It’s no wonder so many teams struggle to create high-quality pipeline.

How AI helps: Identify hidden buyer activity, automatically enrich CRM

All that data is an essential first step in seeing who’s in market for what you’re selling … but it’s only part of the equation.

It’s not easy to combine data from these hundreds — and sometimes thousands — of sources. For starters, intent data providers package and deliver their signals in different formats, using different methods for deriving meaning from those signals. For instance, some provide raw feeds of the interactions that they deem is “intent.” Others deliver a simple score. Still others use sophisticated methods for identifying rises and dips in activity related to a topic.

These differences can make the data very difficult to combine, interpret, and act upon.

With AI, revenue teams have an unprecedented ability to develop high-def images of their buyers and use that image to sell and market effectively.

What’s more, interpreting anonymous traffic on a company’s own site isn’t always straightforward. For instance, companies that offer multiple solutions must figure out which solution visitors are interested in before they can market or sell effectively.

So, yes, the data is essential. But without a way to intelligently combine, integrate, and use all these sources of data to generate insights, it’s just information. And we’ve already mentioned that this informational noise drowns out the all-important, relevant “signal” that revenue teams actually need to sell effectively and survive.

This is where AI comes in. Making sense of this volume of data requires the advanced pattern-matching capabilities that only AI can provide. AI can digest and analyze those troves of Dark Funnel data, as well a company’s own historical sales data, to recognize patterns that signal when a prospect is ready for engagement. In doing so, AI predicts the right time for sellers to begin direct outreach to prospects based on their behavior and engagement patterns.

This is obviously a win-win for sellers and buyers. Sellers are more efficient and effective. Buyers receive helpful, meaningful engagement only when they’re ready — and not before.

AI also dynamically enriches and acquires contact records at exactly the time the revenue team needs it for the most effective outreach. This means there’s no need for team members to spend time manually enriching every account currently in the CRM, and there’s also no need to enrich accounts that aren’t being contacted anytime soon.

Instead, revenue teams can automatically target their acquisition budgets toward enriching and refreshing data on the right accounts at the right time. (This “right time” can be defined by a certain thresholds of predictive scores, fit matches, or other criteria.) Costs are controlled. Engagement efforts are optimized.

Case Study: How Bynder Increased Outbound Pipeline 250% with AI

Bynder is an industry-leading, cloud-based solution for organizations that want to easily manage their digital content. Customers include Five Guys, Groupon, and Zendesk.

The Challenge

Bynder wanted to diversify its pipeline by upping the marketing team’s outbound efforts. While the company understood its total addressable market (TAM), its BDRs needed a better understanding of their prospects’ behavior and buying propensity.

The Solution

Bynder used an AI-based revenue platform to uncover and analyze buying signals from many sources to accurately predict which accounts to engage at the right time. BDRs then narrowed their focus on the accounts that were likely to result in revenue, empowering them to hit and exceed quota, quarter after quarter.

The Results

2.5x increase in outbound pipeline
ROI within four months
Increased BDR productivity and quota attainment
Improved alignment across revenue team and between EMEA and North America

“By Q4 in 2021, we already paid back the cost of the tool for the upcoming two years,” said Marko Ivanov, Demand Generation Manager, Bynder.

Chapter 4

Challenge #2: The Buying Process is More Complex

Unlike in B2C selling (which targets individuals), B2B revenue teams conduct business with a group of individuals on a buying team who work together to evaluate and acquire solutions for their organization. As noted earlier, those teams have grown in size to up to 23 known individuals.

More people means more everything.

But beyond the known individuals on a buying team — the usual suspects who are copied on emails and who attend meetings — many other people engage in the buying process by conducting research and contributing perspectives behind the scenes.

A 2023 study from PathFactory found that small and midsize organizations involve 30 to 35 distinct individuals in the buying process. The same study found that for large companies, those numbers swelled to well over 100 individuals. These continually growing and changing buying teams mean marketers and sellers must address the personal concerns of a growing number of stakeholders and personas.

More people means more everything — emails, content, number of personas to address, activities to track, touches, etc. — which makes it exponentially harder to focus on and reach the people who matter the most.

How AI can help: Navigate buying complexity

Buying journeys are far more complex than back in the days when journey maps were handwritten and tacked to an office wall. With multiple buyer personas continuously entering and leaving the conversation at different stages of the sales process, navigating today’s buying journey requires orchestration that operates across function, tactic, and lifecycle.

AI can plot these journeys and translate them into easy-to-follow plays, which marketers and sellers can use to their advantage.

We know that multi-threaded accounts — those in which multiple contacts are engaged simultaneously throughout the marketing and sales process — are more likely to close than those that aren’t worked with this approach. 6sense’s own data shows that:

Won deals in our strategic segment have an average of 9 engaged contacts, versus 6 for Lost deals
In our enterprise segment, Won deals have an average of 7 engaged contacts, compared to 4 for Lost deals

AI-driven insights empower revenue teams to multi-thread accounts much earlier (and more easily) in the buying journey. By identifying influential buying team members based on their roles, content consumption, and engagement, AI provides revenue teams a deep understanding of the buying team. It elucidates which personas are:

Most likely to be involved in a deal cycle
Who else on the account should be looped in, and
Whether marketing is engaging with leads in ways that create sales opportunities

This assist from AI means that by the time marketing passes an account to sales, all the right stakeholders have the information they need at that stage in their buying journey — which accelerates the sales process and yields more successful, higher-value deals.

In addition, AI digests every account’s firmographic, technographic, and psychographic details, as well as insights from prospect keyword research, web page visits, and campaign activity. These millions of datapoints — which are far beyond a human’s ability to process — are distilled into insights that enable revenue teams to make every conversation relevant and effective.

AI can plot buying journeys and translate them into easy-to-follow plays, which marketers and sellers can use to their advantage.

For the conversations themselves, AI (specifically generative AI) dramatically enhances revenue teams’ ability to multi-thread efficiently. Rather than expecting sellers to stay on top of the activities and progress of the dozens of individuals involved in a buying team and engage them with relevant outreach at just the right time, AI can do the heavy lifting.

Here’s a prime example of how AI can move the needle for a B2B revenue team. We know that AI tracks each individual persona’s progress on the buying journey in order to understand and anticipate their needs. Layering on a tool like AI-powered conversational email, which uses intelligence to engage in limitless email conversations with prospects, dramatically increases the team’s efficiency. These back-and-forth email conversations provide relevant context, respond to questions, and loop in humans when necessary and appropriate.

With conversational email, revenue teams can use AI to move prospects efficiently through the buying process, without overwhelming BDRs and sales teams. Companies using AI see nearly double the deal velocity, according to our research.

“It started as a solution to just generate emails. But now, conversational email AI assistants are fully executing campaigns and following up with leads that our SDRs didn’t have the bandwidth to go after," said Rich Fong, Senior Manager of Sales Development, Vendavo

Case Study: How Custom Truck One Source Saves 738 Hours of Work with AI

Custom Truck One Source is the first true single-source provider of specialized truck and heavy equipment solutions, offering a vast rental fleet, new and used equipment sales, and much more.