Account-based marketing (ABM) focuses resources onto a limited number of highly-qualified target accounts, rather than spreading resources willy-nilly across all your leads. Identifying and engaging with those highly-qualified target accounts, the accounts most likely to buy from you, is enabled by quality data – the fuel propelling ABM’s revenue engine.
Data and ABM
An account-based marketer can use firmographic, technographic, and other types of data to better understand their target accounts, then move from insight to action to revenue generation, which is what ABM is all about. Data helps inform better engagement and personalized conversations around a target account’s particular needs. Intent data, for instance, allows both marketing and sales to reach out to accounts at the right time with specific information to help move the buyer’s journey forward.
On an operational level, quality data can help marketing and sales teams align and coordinate in building key tools for ABM effectiveness, including:
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the list of target accounts, based on your ICP (more on this later);
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mapping an account’s key influencers;
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building lead scoring models and account priorities;
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leveraging predictive analytics to anticipate account needs.
Having high-quality data and being able to leverage it is an ABM-enabling capability that is itself enabled by MOPS maturity. Without MOPS maturity - including data management maturity - the focused account engagement of ABM becomes impossible.
Data must be shared and operationalized with people, processes, and technology. Data flows through your CRM, your MAP, your CDP, and other parts of your tech stack in order to drive ABM’s revenue-generating engine.
Data and defining your ICP
ABM is about focus. Gaining that focus means leveraging quality data (internal and external) to develop your “ideal customer profile” or ICP, working alongside sales to do so. Your ICP reflects an account’s “fit” for your offerings, and gets built from the criteria you select.
Internal and external data can provide a snapshot of the type of account that’s most favorably inclined toward your offerings.
What’s the size of the companies who typically buy from you (small, mid-sized, enterprise)? Are they global or more localized? What other factors do they share that would likely bring them towards your solutions? What industries do they work in? All the factors that make a prospect a potentially good fit for your offerings represents your defined ICP.
You can also use data, internal and external, to identify “lookalike target accounts,” which are companies that share all the same attributes (perhaps gleaned from firmographic or technographic data) as the companies that have already purchased from you, but who you haven’t engaged with yet. Consider adding these “lookalikes” to your target account list for ABM.
Data and driving non-linear buying journeys
The B2B sales cycle can be long and winding. Despite the elegant visual representations of the sales cycle as a step-by-step linear journey from awareness to closing, the journey is anything but linear. It’s often one step forward and two steps back, then maybe a sidestep.
Depending on a target account’s needs and buying processes, a prospect can spend weeks or months defining their needs, drafting an RFP, setting up a buying committee, researching potential solutions, developing a shortlist of options, evaluating proposals, and (finally) choosing a vendor/partner. Today, most of this complexity happens online and long before a prospect account ever reaches out to you.
By the time a prospect visits your website, reads about your offerings, and (if you’re lucky) fills out a form to get more information, they’ve already been researching your competitors for weeks or months and have made up their mind already. In fact, Forrester estimates that prospects are anywhere from 66% to 90% done with their buying journey by the time they reach out to any vendor.
Because the B2B buying funnel can be so lengthy, non-linear, and complex, account-based marketers simply can’t afford to passively wait until a prospect has filled out a form. What’s the solution? Having relevant, quality data at the right time so you can target and engage prospect accounts at the right time with the right messaging. Your ABM program must have the capacity to (1) identify and (2) address account needs with customized and coordinated messaging and content that moves buyers forward in their journey.
Data and refining your target account list/ICP
Prospect accounts are moving targets, so you’ll need to continually refine your approach to ABM, including how you target and engage accounts. For example, you should be using data on an ongoing basis to “recalibrate” your ICP and account lists at least annually, and perhaps quarterly.
You’ll also need to leverage data dynamically to refine your account/lead scoring models and your predictive analytic capabilities.
Quality data offers you the ability to “sense and respond” to account needs as they arise. Maybe a target account is more likely to need your offering after they’ve bought product X,Y, or Z. Monitor relevant intent data and account “trigger events” and be ready to shift engagement priorities as prospects move through their journey.
Data as fuel for ABM: A final word
The better you know your target accounts and their behavior, the better you can engage them via ABM. When you use quality data to target the right accounts, the ones most likely to consider your offerings, you increase your ABM revenues/ROI. When you use data to engage those accounts in more personalized ways, having conversations that are driven by their needs as revealed by quality data, you have a successful, revenue-generating ABM program.
High-quality data is essential for finding your way to ABM success, at every step of the buying journey – data serves as your GPS, enabling you to read the signs and navigate your way to more revenues.
Want to learn more about how you can improve your data quality in order to drive ABM success? We’re experts. Reach out to us here.
