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How to use data to power target account selection
According to SiriusDecisions, a full 91% of B2B teams that are doing account-based marketing (ABM) see larger deal sizes from their target accounts than from non-target accounts. If that isn’t a ringing endorsement for the efficacy of ABM, then I don’t know what is. In theory, ABM is straightforward: Focus the bulk of your energy […]
According to SiriusDecisions, a full 91% of B2B teams that are doing account-based marketing (ABM) see larger deal sizes from their target accounts than from non-target accounts.
If that isn’t a ringing endorsement for the efficacy of ABM, then I don’t know what is.
In theory, ABM is straightforward: Focus the bulk of your energy and resources on best-fit accounts that have the highest revenue potential for your business. But in practice, it’s not always that simple.
Despite the impressive results organizations are generating with target account strategies, ABM is still in its infancy. When it comes to account-based, many marketing and sales teams are still struggling with execution and efficiency.
One of the biggest barriers to an effective ABM program is target account selection and prioritization. In fact, a 2018 survey from Ascend2 found that 37% of teams consider account targeting to be a top challenge.
The challenges with identifying target accounts
What are the barriers to building and segmenting an effective target account list? Most commonly, marketers struggle with the following challenges.
- Lack of a clearly defined ideal customer profile (ICP).
- Limited visibility into accounts’ online behavior.
- Inability to predict when an account is in an active buying process.
- No way to aggregate disparate account-level data, including data from both known contacts and anonymous members of the buying committee.
- Uncertainty about how to segment account lists.
Fortunately, with the right data and strategy, you can overcome these challenges and galvanize your team to focus on your best-fit accounts.
Build a master pool of ideal customer accounts
The first step to data-driven account targeting is to create a master pool of all accounts that fit your ideal customer profile (ICP). An ideal customer profile is a description of accounts that are a perfect fit for your solution.
If you don’t have a great handle on your ICP, your marketing and sales teams should work together to define it. Your ideal customer profile should focus on relevant characteristics of your best-fit accounts, such as industry, technographics, annual revenue and customer base.
There are many effective methods for solidifying your ICP. You can dig into your CRM to uncover the commonalities among your most lucrative customers. You can analyze all the accounts in your database that have ever had an open opportunity and determine which segments have the highest close rates. Alternately, you may see an opportunity to move into a new market with an ICP different from your existing customer base. But regardless of the approach you take, it’s imperative to use clean data.
With this profile nailed down, you can build a master pool of accounts that can be used to create segmented target account lists moving forward. To build this master pool, you’ll need high-quality data about each account’s firmographics, technographics, online behavior, and propensity to buy a solution like yours. Then, you can use your CRM in combination with an AI-assisted audience identification platform to create a list of all the accounts that fit your ideal customer profile.
Tier and segment target accounts using data
This is where a lot of organizations that are new to scaling ABM miss the mark. With a list of best-fit accounts, it can be tempting to go after all of them at once.
In fact, we fell victim to this mentality ourselves when we first launched our account-based marketing program. Perhaps unsurprisingly, focusing on a long list of target accounts didn’t result in higher conversions and more pipeline. Our sales reps were still operating with a high-volume mindset, and our marketing budget was spread too thin among all our accounts.
Data-driven account tiering and list segmentation were our saving grace. The purpose of account tiering is to help your marketing and sales teams prioritize specific account segments, tailor your messaging to those segments and run more targeted campaigns.
When we scaled back our ABM strategy and focused our efforts on the accounts that were most likely to make a purchase at any given period in time, our results drastically improved. Within 90 days, we were seeing incredible results.
- The win rate from first demos went up 125%.
- Demo-to-interest conversion rate increased by 58%.
- Average deal size increased 35%.
- Sales cycle length decreased by 20 days.
This came from using account insights to get more strategic about which companies we were going after and how we engaged with them.
Unify fit, intent, and engagement data in one place
For the most robust and accurate targeting, aggregate all your important account data in one central location accessible to both marketing and sales. Then, use this data to help you prioritize target accounts and tailor your outreach. There are three key types of insights marketers can use to segment and prioritize their target account list.
All accounts in your master pool are “best-fit,” but you can dive deeper into firmographics and technographics to further segment your audience — for example, by company size, tech stack, or industry. Your target account strategy should be highly personalized, and one way to streamline this personalization is by grouping accounts with similar attributes.
A predictive platform can tell you if an account is in-market for a solution like yours. With intent insights, you can pick up on signals that they’re researching you or your competitors, allowing you to prioritize accounts in an active buying cycle. If you have multiple products or services, intent data can also help you segment your audience based on the topics/solutions for which they’re showing intent.
Understanding account-level engagement is critical to strategic ABM. Use engagement data to mainline your most engaged accounts, identify who needs more outreach from your team and get a full picture of how all the stakeholders at an account — whether or not they’re in your database — are interacting with your brand. Engagement insights also allow you to segment your target account list by topics of interest and levels of engagement.
Operationalize engagement insights from known and anonymous buyers
Fit and intent data are relatively straightforward, but engagement is where the real magic happens. Traditionally, marketers have only been able to track known contacts’ online activity. There’s no question that this data is important, but it doesn’t help you when buyers from your target accounts haven’t yet identified themselves by filling out a form.
We all know that a large portion of the decision-making process happens before a prospect ever reaches out to your company. This is especially true for upper-level stakeholders who may never fill out a form on your website, despite having significant influence over the purchase decision. This is where anonymous website visitor data comes in.
Being able to aggregate web engagement data from known and unknown visitors — and roll that data up to their respective accounts — can help you segment your account list in more meaningful ways.
So, what does it take for an account to be classified as Tier 1, and therefore receive the most valuable engagement from your team, like direct mail and exec-to-exec outreach? That’s largely dependent on what matters to your organization.
For example: You may decide that in order to be classified as Tier 1, an account must have a potential lifetime value of at least $1M, and at least five people from the account must have engaged with your brand — whether online, at a field event, or on the phone. If you don’t have a way to see anonymous account activity, then your Tier 1 account list will be lacking accounts whose buying committee haven’t yet identified themselves despite being in an active research process.
Meanwhile, you may decide that your Tier 2 accounts must have the same revenue potential but be less engaged with your brand. They’re absolutely still worth working, but your team should focus more efforts on the Tier 1 accounts that are more likely to close. Keep in mind that a Tier 2 account can progress to a Tier 1 account when they hit that agreed-upon engagement threshold.
This is why engagement insights are crucial to a data-driven target account strategy.
Account-based marketing to win
Account-based marketing is not one-size-fits-all. You’ll need to tailor your approach based on your business’ goals, needs, and audience.
Make sure you select marketing technology that allows you to aggregate all your account data to easily build, manage, and report on target account lists.
By working together as one revenue team to prioritize your most valuable accounts, you can increase win rates, decrease time to close and build lasting relationships with the right accounts, not shallow relationships with the most accounts.
Opinions expressed in this article are those of the guest author and not necessarily MarTech. Staff authors are listed here.