Most revenue teams have more prospects in their CRM than they can handle. The problem, frankly, is not building up contact lists—the problem is maximizing the pipeline to identify the best prospects and engage them effectively.

The sub-par prospects that clog your pipeline still consume resources but are more unlikely ever to close. If they do close, they’re less likely to renew or become your best customers.

Our research at Rev shows that up to 66% of the leads sourced through traditional prospecting practices sit dormant, due largely to the fact that many of them shouldn’t have entered your funnel to begin with. They should have never been considered a real prospect. Meanwhile, up to 65% of five-star opportunities get straight-up missed.

Those averages are outstanding in baseball, but horrendous in your revenue functions. The culprit? Most companies don’t actually know what their real ideal customer looks like. Their ICP is incomplete. And if they can’t identify their best prospects, they certainly won’t connect with them.

Developing a high-quality, high-efficiency pipeline starts with improving the fitness of your prospects—and your aim in targeting them. After all, your aim—the percent of accounts in your pipeline that match your ICP—matters, and it should be a key metric you track. When you spend more of your resources engaging with the right prospects, the ones most likely to close and become great customers, the entire journey downstream runs more smoothly. What company doesn’t need that, especially today?

If you’re wondering how to track your aim and how to improve it, you’re in luck. This article will guide you through everything you need to know to get started.

 

Step 1: Identify the characteristics of your best customers

When you think about your best customers, what traits come to mind? Too many revenue teams still rely on firmographics to understand the traits of their best customers. Broad categories like industry, location, size and revenue don’t actually reveal much about the inner workings of companies and how they execute their missions.

B2C companies have been riding this train for years now. They moved beyond demographics to psychographics to better predict what individual customers want to buy. In the B2B world, you need equivalent insights to really understand your best customers (and, in turn, your best prospects). 

Exegraphics provide those demand signals. They are, essentially, any piece of information you could want to know about a company, gleaned through AI-driven analyses in three ways.

1. Exegraphics focus on a company’s positioning in its industry and the value it brings to market.
2. Exegraphics also evaluate the functions of the people internal to an organization, including how those functions are prioritized.
3. Exegraphics then account for trends over time to better predict where a company is headed.

 

Exegraphic data digs beyond superficial indicators to evaluate broad organizational behaviors and patterns. You might have two companies that appear identical on the outside: same industry, comparable products, equivalent workforce. Yet they might operate entirely differently on the inside—and those inner workings effectively make them completely different customers.

Evaluating your existing best customers in these ways helps you understand what really makes them tick, and thus, what you really want to look for in a top prospect.

 

Step 2: Build a dynamic ICP

Exegraphics are precise data points. Any one of them, taken in isolation, may not mean much. But a collection of hundreds of exegraphics accomplishes what a traditional ICP hopes to: it builds a complete and thorough picture of how your actual best customers behave, and what they are most likely to need.

Even better? Exegraphics, by their very nature, enable revenue teams to create dynamic ICPs that continuously improve. (At Rev, we call these aiCPs—AI-driven ideal customer profiles.) These are ICPs that embody the current and ever-changing behaviors, strategies, attitudes and events (such as personnel and product changes) of your ideal customers.

Plus, each time you sign a new customer, or an existing customer expands its account, that customer’s exegraphic data feeds back into the model to better define what ideal means for you.

No more of the old-school, stuck-on-firmographics ICP on a PowerPoint slide that you update every few years. Equipped with a dynamic ICP, revenue teams know (essentially in real time) how their best customers behave—and what to look for in new prospects.

 

Step 3: See which accounts in your pipeline have the characteristics you care about most

Now that you know what your ideal customer really looks like, and have a living model in place that evolves over time, you’re ready to see how many of the accounts in your pipeline fit your ICP. In our experience working with some of the world’s top brands, it’s much less than you think.

When you evaluate the exegraphic markers of the accounts in your pipeline and compare them to your now-full-picture ICP, you’ll have an aha-moment. You’ll see why certain accounts got stuck in your pipeline with little to no progress. You’ll also see accounts that show more promise, that have leading characteristics of an account that will make its way to closed-won. Those are the accounts you’ll know to prioritize.

When you can see how closely accounts in your pipeline match your ICP, you’re able to take a data-driven approach to seal the deal. Accounts that are a clear match to your ICP could be routed to sales, while accounts with a lower match rate could be placed in a nurture track. The accounts that don’t have matching traits? Toss those. You don’t have time or budget to spend on them.

 

Step 4: Find new accounts that match your ICP

Now that you have fewer accounts in your pipeline, what do you do? And how do you fill it moving forward?

Volume still matters, yes. But it really needs to be more of the right stuff. More quality targets. You probably get where we’re going with this, and you’re likely saying to yourself, “Got it… but how do I find accounts that have the deep traits I care about most? If I knew how to spot them, they’d already be in my queue.”

Great point. You could try to do it manually: hire a dedicated team to determine the exegraphics behind your best customers, build a more robust ICP and evaluate the exegraphic data behind all the accounts in your pipeline. By the time they’re done running the analyses, though, the data has probably changed. Luckily, AI can tackle this workload almost immediately. It’s great for pattern matching across large data sets and language models—including all sorts of digital “breadcrumbs.”

AI can also tell you which companies match your ICP, and how closely. AIM, an AI-Match, improves aim. No more going after big, aspirational logos just to have them clog your pipeline. By using AI to find the accounts that resemble your best customers, you’ll always know which accounts to target, and when.

 

Step 5: Improving metrics through better aim

When companies improve their targeting efficiency through the use of exegraphics and aiCPs, they don’t just get better prospects in the funnel—they get improved results the entire way through it.

 

Engagement case study: Allytics

As a Central Marketing Organization (CMO) for its clients, managing everything from strategy to implementation with an eye on improving their marketing ROI, Allytics requires strong engagement on behalf of all of its customers: growing account lists, acquiring new leads, expanding pipelines for marketing and sales.

To those ends, Allytics have partnered with Rev for more than three years to support deeper lead qualification, target market expansion and nurture campaigns for their clients, with the aid of exclusively tailored Custom Lenses.

“We can come in with any angle and Rev builds a lens for us that helps our clients increase their pipeline growth by providing unique and specific targeted insights,” says Allytics President Dunya Riechelson. “This gives us clear direction and quality results.”

For Allytics, Rev’s Sales Development Platform expanded several clients’ account bases by more than 20% through lookalike targeting, providing access to a stronger pool of leads with higher levels of engagement.

VP of Marketing Services Robert Doi says: “Rev’s technology makes them a perfect partner to help our clients increase both the quality and velocity of new potential customers, closing more deals.”

 

Pipeline case study: Splunk

When Splunk acquired another company in the DevOps space, it set out to run a demand gen campaign to prospect for it. Splunk had developed an extensive ABM list and inherited a seed list of the acquisition’s best customers, but still struggled to gain traction and add quality prospects. 

Rev created an aiCP for Splunk, prioritized the list and ran a content syndication campaign.

Not only did the campaign result in sourcing the quality prospects Splunk desired, but it also revealed that the companies showing intent previously were not actually best-fit prospects. They were draining revenue resources with a lesser likelihood of actually closing.

Splunk’s new aiCP enabled them to prioritize the account list and focus marketing efforts. According to Joe Paone, Sr. Director of Worldwide Commercial Marketing, more than 15% of the pipeline can now be attributed to the aiCP, with increased pipeline revenue of more than $500 million.

 

Sales cycle length case study: Oracle

Oracle recognized it needed a more scientific way to maximize its sales cycle. The company struggled with low conversion rates, and thus an increased cost per conversion.

In addition to an aiCP, Rev built and managed an outreach campaign centered around Oracle’s in-house thought leadership content. Rev nurtured the companies that showed interest in this content, signaled strong early-stage buying intent and aligned with the aiCP.

The results from the initial pilot?

• Oracle experienced a 67% improvement on cost per new logo over the previous channel benchmark.
• Oracle also created opportunities 78% more efficiently, with $500k in pipeline value.
• The leads Rev provided moved 23% faster through the funnel, a significant improvement in sales cycle length.

The results aren’t isolated to Oracle either: Allytics saw a 50% decrease in time to find qualified leads, and Splunk saw the above results in less than three weeks.

 

Final thoughts: Keep on evaluating your pipeline

Once you achieve a stronger sense of your own ideal customers on an exegraphic basis, you can make a pretty immediate and drastic evaluation of your existing pipeline.

If you align with the averages, your revenue team isn’t even touching about 2/3 of the prospects in the pipeline. Imagine assessing the entire pipeline for the best-fit prospects—the ones most likely to close, and to become great customers—and being able to pluck those targets out of the crowd.

You can. And you can evaluate how you’re filling the pipeline based on what percentage of the prospects there match the characteristics that matter most to you. These are the metrics that can change the game for revenue leaders: early indicators of your revenue teams’ operational efficiency and ultimate success.

Doing so not once, but continuously, calibrates your teams’ efficiency and your pipeline’s quality. As Allytics’ Richelson says: “Quality is a focus from end-to-end through every touch point in the engagement. And, because the AI gets smarter over time, we can optimize as we go.”

As you need to pivot in an ever-changing market, exegraphics and aiCPs equip you to constantly refocus your aim and maximize your efforts. After all, your objectives aren’t static. Your approach doesn’t have to be, either.

These pipeline pain points are a universal experience, but they can be addressed head on by revamping how you think about your ICP and changing the way you identify and source top prospects. Refine your ICP. Contact us and get a free look at the exegraphics behind your best customers.

Straight up, the B2B world does not get measured and tracked the same as the B2C world. Years ago, consumer sales vendors used to track just demographics. Today, they know a ridiculous amount beyond your age, your gender or your location: the large data attractors (think Amazon or Google) can predict what you’ll want to buy, before you know it yourself.

There is no such thing in the B2B world. No giant data attractor for companies that want to know what other companies need. No way to predict who the most likely, or most ideal, customers for a product or service will be.

So at Rev we decided to construct that information ourselves. A deep picture about companies—what they produce, how they behave, how they work—helps our customers to identify other potential clients much like the way the e-commerce giants can target you as an individual consumer.

Anything you could want to know about a company, we call an exegraphic: a piece of information or a characteristic that conveys how a company executes its mission.

Let’s take a look at what exactly exegraphics are, and how they help companies like yours find more and better prospects, faster.

 

Exegraphics capture how a company projects itself to the world.

Exegraphics require us to look at companies in two major ways. The first is, what does a company say about itself? All companies make promises (both explicit and implicit) to their market about what their goods and services can accomplish, how they conduct themselves, and what stands them apart from their competition.

This external facet captures both functional language and messaging: both what a company says and how it says it. Essentially, our models take in however a business communicates its value to the public. We generally capture this information on company websites and social media platforms, as well as other similar sources.

The difference between collecting firmographics and collecting exegraphics is their depth. Just as B2C companies have moved from demographics to psychographics, B2B needs to shift from firmographics to exegraphics. 

No large or successful B2C company would be satisfied with making decisions based merely on demographics anymore. Psychographics simply tell a better story about where a consumer is positioned. Exegraphics do the same thing for B2B companies: they extend beyond firmographics not only to tell you the industry a company is in, but also to show you how it positions itself—and how they operate—within that industry.

 

Exegraphics puzzle out how a company functions on the inside.

The second major way exegraphics require us to look at a company is, how does it function on the inside? This one is less immediately apparent. Most companies don’t publish how large their legal team is, or how fast their software department is scaling. And these things are not always discernible from external projections.

Think of it like this: two companies can be in the same field, offering competing services. One does it with an army of people, and the other does it with five AI engineers and a bunch of robots. One of these companies might be your ideal candidate, and the other a worthless lead.

Exegraphics get to the difference by looking inside. Our model turns to professional networking sites and similar platforms to build a sense of who works at a company—what are their functions? their responsibilities? their skills? their professional backgrounds? It also looks at job postings to determine what the company is asking for in potential employees.

Whereas the first way exegraphics look at companies focuses on a company’s position in its industry and the value it offers to its market, this one focuses on the functions of people within the company, and how those functions are built, sized and prioritized.

 

Exegraphics figure out these things millions of times to place companies among their peers.

A human being with time and the internet could do that work for a single company. In a day, a team might be able to assemble information for a hundred. But to be of any significant use, you need to do it for the thousands upon thousands of companies in existence. Rev uses a mix of powerful AI technologies to undertake the sense-making by doing what a human would do, millions of times over: read websites, resumes, and job postings to create a clear picture of any characteristic of what a company does and how they do it—then compiling how individual prospects compare to their aggregated peers.

What industry a company is in is a firmographic. So is the fraction of people at that company who are in the legal function. Now, the model looks at the peers—same industry, same basic size—and evaluates if the legal team is about what you’d expect, way bigger or way smaller. And bam! You have an exegraphic that helps you understand that potential customer’s position.

Context matters for any exegraphic. You have to know what peer group you’re comparing to in order for exegraphics to matter. For example, you’d expect a large software team at a software company. But at a dog-walking service, one developer means that company is probably a software giant compared to its peers. Same for other considerations—slow growth in one industry might be massive growth in another. Or, one company scaling when others in its industry are contracting might offer you valuable insights into their behavior.

 

Exegraphics account for change over time.

Comparing peers tells you the relative bench strength of a company in distinct functional areas. Exegraphics can also account for how those strengths have changed and are changing.

Let’s say that you’re selling cloud-based accounting solutions. You’ve identified a bunch of growing prospects. Great—growth is one such exegraphic. Now you can identify the ones whose accounting departments are actually shrinking. These accountants might be overwhelmed; maybe they need new solutions, or maybe it’s hard to hire good accountants in their area and they need something to change.

Now you’ve identified clients who not only fit your audience, but who also have a reasonably demonstrable need for your services.

In this way, you can think of any exegraphic having a characteristic called speed or velocity. How quickly does it change, and in what direction? On an individual level, change is constantly happening. Companies hire and fire people all the time, and workers move between jobs. But looking at groups over time, exegraphics can identify trends within a single company and relate them to shifts across an industry.

Exegraphics can also identify sudden changes. We’ve developed new data sources around funding, for example. Companies that close a round of venture capital have loads more money in the bank overnight. But those kinds of changes don’t happen that often; sudden hiring changes do, however, especially in scaling companies. 

For instance, an emerging Acme Inc. is probably growing their marketing team right now. They’ll have a lot of new hires, and the average tenure will be pretty low. That would be good to know if you wanted to sell them your marketing solution—Acme finally has people who can use this stuff, and marketing is clearly a growing priority for them. And if it’s a priority, they might spend some money to do it right.

That’s the premise and the value of examining change through exegraphics.

 

Exegraphics stack multiple factors to identify top target accounts.

Each single exegraphic can feel pretty powerful to hold. You’ve just identified how many software engineers a whole bunch of companies have. You’ve even identified which ones are growing most rapidly. It’s like magic.

It’s also not a full solution. Individual exegraphics are really handy for getting your first grasp of the concept. But relying on isolated exegraphics will always have limitations. Instead, you want to stack several of them together to get a more multi-dimensional identification of top target accounts.

For starters: not only do you want a team with a need for your product—you want one with the funding to buy what you’re offering.

It turns out humans are really bad at considering multiple factors at once, combining them in a way that makes sense. Humans want to make rules. In or out. Yes or no. What our exegraphic models do instead is weigh the evidence and determine what is worth more points to your query, and what’s worth less, to deliver a more nuanced, inclusive understanding of how companies operate.

 

Exegraphics deliver you companies that look (and act) like your very best customers.

You’ve already got your best customers. The ones you wish every new customer could be like. But you may not know all the reasons why these are your best customers. What are their defining characteristics?

After you feed our Sales Development Platform the Seed List of your very best existing customers, it creates an aiCP (essentially, a lookalike model) to tap into, say, fifty or sixty exegraphic characteristics of those companies and figures out what traits they share. You don’t need to know what the data patterns are—the AI will identify them.

Then the model finds other companies whose combinations of distinctive exegraphics are comparable to your best customers. Essentially, it solves your give-me-more-like-these problem, a million times closer to instantaneously than a human team could manage, and in complex ways that humans simply can’t.

 

Exegraphics let you drive.

Rev’s AI doesn’t think like a human being. It creates and evaluates exegraphics with a points-based system. It also doesn’t make all the final decisions for you: rather, the model translates its points-based system into terms we humans can understand—industries, functions, growth rates, things like that. Once the model finds your lookalikes, you can define and apply lenses to whittle down the prospect list with your own considerations in mind.

To aid in that process, Rev’s exegraphic data and lookalike technology also lets you know which exegraphics are the most defining characteristics of your best-fit accounts. Once you have your list of more-like-these, you can use both exegraphics and traditional firmographics to sort or filter target lists to fit your sales and marketing goals and processes.

Just as an example—perhaps you want to focus on potential customers within a certain region. You can filter the results by geography. Or, you want to see which lookalikes are at a particular size. Easy.

The possibilities really are limitless. If you can dream up something you’d like to know about companies, our tool can take a credible shot at it for you. It’s a unique and valuable offering in the world of B2B commerce, where for too long we’ve been driving in the dark.

Want to see how exegraphics work? Schedule a demo, and we’ll show you our 500+ exegraphic lenses and show you how you can create your own.