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. 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.”

And that’s not all. Allytics also saw a 50% decrease in time to find qualified leads.

 

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.

 Did we mention they saw these results in less than 3 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.

Ideal customer profiles are a staple of B2B sales strategy. And they make sense: if you can identify the traits that make your best customers your best customers, you can target the same traits in your best prospects.

The problem with ICPs is that they are generally a shallow way to characterize companies. A sales team can put an entire ICP in bullet points on a single slide. That ICP is often a static document, too, not accounting for changes in your best customers or your best prospects.

In essence, a traditional ICP is a stereotype. Sales teams target prospects on five or so traits. The B2C world has moved away from targeting prospects based on how they look, so why do so many B2B companies still target their best-fit customers that way?

The simple answer is that deeper information about companies is harder to take into account. Really, revenue teams need to identify prospects based on the decisions and behaviors of companies—but that data is hard to understand, let alone formulate. So, ICPs remain assumption-based, superficial and limited.

That’s why we at Rev set out to create a new approach to identifying best-fit prospects. Using our AI-based modeling techniques, we developed the aiCP: a dynamic, customizable and in-depth way to profile prospects across market segments.

Let’s look at the power of aiCPs and how they help revenue leaders target the right prospects.

 

aiCPs target look- and act-alikes.

 Traditional ICPs are so brief (and so shallow) because they essentially identify lookalike firmographics: industry, headcount, revenue, recent funding, specific job titles and so on. However, these are not insightful ways to understand how a company actually operates, and therefore how they compare to your best customers.

aiCPs, on the other hand, rely not on firmographics but on exegraphics. 

Exegraphics are pieces of information or characteristics that convey how a company executes its mission—and they are the crux of aiCPs. Just like the B2C world realized psychographics are far more powerful than demographics, Rev’s exegraphics offer the same caliber of insight beyond old-school firmographics for the B2B world.

Our modeling technique looks at everything from company messaging to hiring boards and employee resumes to understand how a company functions, how it changes over time and how it compares to its peers—and it examines millions of data points to build a clear picture of what actually makes your best customers your best. 

(For a more in-depth exploration of exegraphics, read What are exegraphics?)

Then, we build an aiCP from that picture. You get to really know how your best existing customers function, and what they share in common, regardless of topical characteristics. You know how your target market behaves on the inside—not just how it looks, but also how it acts—now that you’ve put more rigor into defining your ideal customers. Therefore, you can get much more precise in how you target new accounts, cutting through the fluff of firmographic lookalikes alone.

 

aiCPs evolve.

Too often, traditional ICPs remain static within a target market. A sales team identifies traits to look for, and then it sticks with them. However, industries and individual companies are constantly changing, and it makes little sense why a sales strategy shouldn’t evolve too.

That’s why we build aiCPs as living sales strategies: they are meant to iterate continuously, and respond both to the market and to your own human input.

 

Dynamic aiCPs

Once you enhance your customer profiles with aiCPs, incorporating change over time is inevitable. After all, your products change, your customers change, the economy changes. Nothing in a sales environment stays the same forever. The dynamic nature of aiCPs takes those changes into account.

• aiCPs change with each successful sale. The customers you’re selling to today might look different than the ones six months or a year ago. You can push every sale you close back into the aiCP model so that it incorporates the new data points associated with that customer. Refining the aiCP each time a new customer comes on board keeps your seed list relevant and your targeting in sync with your market.

• aiCPs grow alongside your best customers. Say your organization started off selling strictly to early-stage tech startup companies. You’re still closing those sales today, but your existing customers have stuck with you through their Series B funding and are increasingly becoming successful enterprise companies. By continuously reassessing your aiCP over time, your target profile grows to include other established companies that behave like your best oldest customers in addition to your best new customers.

• Companies take actions that readjust themselves. Think of those important moments that dictate the course of a company. A new executive hire. A new product launch. Those fundamentally alter the way a company operates, which means they will either become a better or a worse target for your sales team. The dynamic nature of aiCPs capture those changes to reprioritize them for your revenue team.

• New exegraphics improve the modeling. Exegraphics are not a static tool either. We at Rev are continuously developing new ways of understanding companies. That means each new analysis of your seed list will adjust the Rev Score of each target account and reprioritize them based on the best understanding available—in conjunction with the most recent assessment of thousands of active peer companies.

 

Customizable aiCPs

For all the characteristics of companies that exegraphics capture, they don’t catch your own human understanding of your revenue team, your company and your customers. That’s why aiCPs are customizable, allowing you to weight certain traits and prioritize accordingly.

Rev’s AI model is not a black box: it’s a powerful tool to give you, as a revenue leader, the target list you need. Pairing that utility with your institutional knowledge enables you to create massively effective customer profiles, prioritized according to your understanding of what matters.

Our customers are able to drive their aiCPs. We’ll help you define custom exegraphic lenses. We’ll help you prioritize what’s meaningful or feasible for your revenue team. That can look like just about anything you can imagine—because while we’re passionate about getting you connected with top-quality prospects, you also need to feel passionate about the results.

 

aiCPs open up unexpected market segments, save resources and help you move faster.

Cutting-edge aiCPs offer plenty of advantages over traditional ICPs for revenue teams looking to reach new customers. Yet one of the great strengths of the aiCP model is its ability to identify entirely new market segments for growth-minded organizations.

You can dig deeper into how aiCPs open up new market segments in New ways to identify new market segments. Here, though, are some key insights into how an aiCP drives growth for companies who need to break into new markets.

• aiCPs do away with assumptions. The exegraphics behind aiCPs are less concerned with what industry a company is in, and more concerned with the interior functions of that company. So when the AI model identifies act-alike companies for your best customers, those often reside in entirely different and unexpected market segments from your typical clients.

 

Without this knowledge, revenue teams looking to breach new segments tend to presume that adjacent markets make for strong prospects. It makes some sense to reason that similar markets will have similar needs, and that this transition will be an easy one. Yet adjacent markets, despite appearing similar, are not always the best prospects. Let’s say your current best customers are auto insurance companies. You might decide to start targeting health insurance companies, while your hypothetical aiCP shows that the financial sector is your strongest addressable market—a pivot you would never make without deep insights into those prospects.

• aiCPs allow you to breach new markets more affordably. It’s expensive to craft a marketing plan for a new market segment. (One of the appeals of adjacent markets is that the marketing team isn’t building from the ground up.) But with the high-fidelity prioritization offered by aiCPs, you aren’t targeting the TAM from the start. You are taking a strike-team approach: sending in a small handful of sales reps, with basic early-messaging collateral, to make first contact with prospects most likely to bite.

• aiCPs get you to market faster. That surgical approach to the first prospects gets your team talking to prospects instead of building strategies without on-the-ground knowledge. What kind of engagement is happening? Can your reps close a deal? What needs to shift?

 

The customers you land (and the ones you don’t) can inform both the ever-evolving aiCP and your team’s sales strategy. You’re not stuck waiting for the marketing machine to start turning out materials before you can get started. The precision and high resolution of your aiCP accelerates the info-gathering period and helps you assess, quickly and definitively, whether a new market segment is viable. With this approach, you can manage that in 3-6 months, rather than the more usual 12-18 months to develop a go-to-market program.

The aiCP, in short, keeps your revenue team at the top of their game. Your decisions are driven by data more than generalization. Your targeting is more focused, your likelihood of landing new customers increases. You can accomplish more sales in less time, using less of your resources. And your strategy evolves as you do, keeping your team continuously sharp.

To see how your ICP compares to your aiCP—and get a view of the behavioral characteristics of your best customers—contact us to schedule your free aiCP audit.

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.