In fire safety, it’s stop, drop, and roll. In retail, it’s no shirt, no shoes, no service. In Fight Club, it’s… well, we don’t talk about Fight Club. The point...
In fire safety, it’s stop, drop, and roll.
In retail, it’s no shirt, no shoes, no service.
In Fight Club, it’s… well, we don’t talk about Fight Club.
The point is, rules rule. And they’re especially important for establishing Account-Based Marketing within an organization. There’s always a degree of art and instinct that’s involved in providing consistently engaging experiences to prospects and customers, but make no mistake: if you want to succeed at ABM, there are proven rules to follow and operationalize.
Here are five must-use tips inspired by our recent ebook, ABM is [Still] Just Good Marketing, that can help you sidestep challenges, deliver account-based experiences at scale, and put you on track for predictable revenue growth.
If you’re trying to determine the best accounts to target for future business, try taking a closer look at your organization’s past and present.
Collect as much customer-related data as you have access to. Assess historical patterns of your best accounts including:
Once you’ve done that, identify current prospects with similar traits.
Harness this info to run more data and develop your Total Addressable In-Market (TAIM). This represents every company you could sell to that’s in the right stage of the buying process.
You can even narrow your TAIM down further into an In-Market Ideal Customer Profile (IICP) that helps illuminate the accounts you’re most likely to win.
Technology that uses AI and predictive analytics are your best friends here. They make consolidating and organizing all of this big data so much easier and more actionable.
Once you’ve selected your accounts, you’ll want to extract deeper, actionable insights to help move them along the buyer’s journey. Depending on your solution, you’ll want to learn such information as the accounts’:
Basically, you need to know what prospects care about at every stage of the game.
This and other data is often anonymized and out of reach, residing in what we call the Dark Funnel™. This is a historical blind spot for revenue teams. It includes invaluable intent data transmitted from B2B buyers who conduct research across thousands of websites and digital resources such as:
You can learn more about the Dark Funnel here, but know that it’s possible to leverage world-class revenue technology platforms to illuminate and collect this data. It provides the key to modeling out a buyer journey that leads to closed/won opportunities in a proven manner.
Armed with that critical Dark Funnel data, you can start brainstorming content and outreach. More urgently, you should cook up a way to accurately and resonantly personalize your engagement with prospects. ABM relies on understanding your buyer personas and ICP in order to deliver compelling, customized content over the right channel, at the right time, in the buyer’s journey.
Set things up strategically. Use predictive analytics as your base, making sense of the multitude of data points available to understand buying-related cues. Provide the right content that will provide a much appreciated “scratch” when they start to get the itch.
Automate this process whenever possible to be timely and to operate at scale. Without the right tools in play, you’ll revert to manual coordination, detailed project plans, and dedicated teams. That opens you up to more delays, more overhead, more miscommunication, and more errors.
As has been the theme, a level of data management is needed that’s simply beyond our finite human brains.
Now it’s time to work together across the revenue team. Marketing, sales, and customer success should all be running toward the same aims:
But that’s often easier said than done. Your organization may have thousands of accounts, each with multiple potential contacts on the buying team. This usually makes it hard to prioritize your resources.
Proactively address the issue by setting a positive tone of collaboration and determining who is responsible for accomplishing what, when, and how. Free your mind from old ways of working and let AI do its part to continuously calculate behavioral and fit scores for accounts, leads, and contacts in real time.
Perhaps most important, admire the approach together and ensure everyone’s concentrating resources on accounts with high buying propensity.
Data is the key to revenue success. It’s the antidote for debates and delays. And it’s at the heart of the best stories.
But as much as we might love data, it’s not all created equal. If you’re measuring the wrong business metrics, the resulting information won’t get you very far — and it certainly won’t give you any meaningful insights to help your efforts.
Many B2B marketers cling to lead-level metrics (MQLs, contacts reached, etc.) like security blankets even after they’ve evolved to an account-based structure. These systems are unscientific and aren’t helpful in predicting an individual buyer’s likelihood of making a complex B2B purchase. You may have lots of information, but little insight.
Your new KPIs should be more pure-play, such as:
Pattern-matching is useful here. Pair your historical account-based sales and marketing data with real-time intent and engagement data to see when a given account meets your IICP criteria. Note which accounts have just moved to the decision or purchase buying stage.
These kinds of insight opens a whole new prospecting pool that you didn’t know existed and enables you to predictably grow pipeline and revenue.
Nobody said rules were easy. These “commandments” demand investment, energy, teamwork, and a willingness to change — away from outdated tools and into the realm of unknown data, uncharted relationships, high-precision messaging, and metrics that make everyone gulp.
But rest assured, the payoff in predictability and amazing prospect experiences is well worth it.