Account-based marketing (ABM) is a personalized approach to GTM that has gained popularity due to its ability to target high-potential accounts effectively. Unlike traditional marketing, ABM focuses on tailored campaigns for specific segments rather than casting a wide net. A 2021 survey by Demandbase revealed ABM outperforms other marketing initiatives for 87% of B2B marketers, with an average 171% increase in deal size.
ABM can be right for companies of all sizes - large enterprises with complex sales cycles can cater to their highest-value accounts, mid-sized companies can easily test new markets, and small businesses can more efficiently allocate limited resources. Microsoft, IBM, Oracle, Salesforce, Adobe, and Hubspot are a number of companies that have successfully implemented ABM to win key accounts and drive higher conversion rates, revenue growth, and customer retention.
Implementing ABM for the first time requires a company-wide commitment to a customer-centric approach and a willingness to iterate based on feedback and results. The success of ABM hinges on the collaboration between Marketing and Sales teams through three crucial phases.
To effectively execute a new ABM strategy, revenue teams need to shift their organizational mindset, commit to data-driven decision-making, and be willing to invest in building longer-term relationships with key customers.
ABM can be categorized into three main types based on focus and personalization levels. We'll use Salesforce, the global leader in cloud-based CRM solutions as an example for each type.
The choice of which ABM strategy to use depends on a company's resources, target audience and objectives. Naturally, the highest level of personalization requires the most intensive resource commitments, but also generally leads to the highest ROI for key accounts.
While ABM can be a transformative strategy for companies, it also comes with significant challenges. Here are some of the most common pitfalls:
Thankfully, new AI-powered tools created over the last few years have brought transformative changes to ABM at every stage of campaign creation and execution.
Account-Based Marketing is a powerful strategy for engaging high-value prospects. The integration of AI-powered tools makes creating personalized content at scale more feasible, allowing businesses to implement ABM more effectively and drive exceptional results for their revenue teams.
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AI-powered tools are changing Account-Based Marketing (ABM) by enabling B2B companies to scale personalized content and expand their reach to a larger number of high-value accounts. As demonstrated by success stories of Vividly and Wunderkind, leveraging generative AI for ABM leads to enhanced engagement rates, higher conversion rates, and improved marketing effectiveness, pointing towards a future where AI will play a crucial role in transforming ABM strategies.
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A playbook for 1:1 marketing in the AI era
"I take a broad view of ABM: if you're targeting a specific set of accounts and tailoring engagement based on what you know about them, you're doing it. But most teams are stuck in the old loop: Sales hands Marketing a list, Marketing runs ads, and any response is treated as intent."
"ABM has always been just good marketing. It starts with clarity on your ICP and ends with driving revenue. But the way we get from A to B has changed dramatically."
"ABM either dies or thrives on Sales-Marketing alignment; there's no in-between. When Marketing runs plays on specific accounts or contacts and Sales isn't doing complementary outreach, the whole thing falls short."
"In our research at 6sense, few marketers view ABM as critical to hitting revenue goals this year. But that's not because ABM doesn't work; it's because most teams haven't implemented it well."
"To me, ABM isn't a campaign; it's a go-to-market operating model. It starts with cross-functional planning: mapping revenue targets, territories, and board priorities."
"With AI, we can personalize not just by account, but by segment, by buying group, and even by individual. That level of precision just wasn't possible a few years ago."
This comprehensive guide provides a blueprint for modern ABM execution:
8 interdependent stages that form a data-driven ABM engine: account selection, research, channel selection, content generation, orchestration, and optimization
6 ready-to-launch plays for every funnel stage, from competitive displacement to customer expansion
Modern metrics that matter now: engagement velocity, signal relevance, and sales activation rates
Real-world case studies from Snowflake, Unanet, LiveRamp, and more
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