As a B2B marketer, you understand that creating engaging and informative content is essential for attracting and retaining customers. Unlike consumer marketing, where a quick photo or ad might suffice, B2B audiences often require deeper industry knowledge and product specifications to make informed decisions. This is where long-form content, such as eBooks, white papers, and case studies, comes into play. However, creating such content can be time-consuming and resource-intensive. Fortunately, generative AI is revolutionizing the way B2B marketers approach content creation.
Chris Spellman, Director of Marketing & Communications at Rex, recently highlighted the extensive time and resources that "Lead gen" gated eBooks and content syndication consume, only to yield minimal engagement and conversions. This observation underscores a pressing challenge for B2B companies: creating quality content that genuinely drives revenue without being ensnared in the traditional, cumbersome process of gating content.
Gated content, which requires users to provide their contact information to access it, has long been a staple in B2B marketing. However, as Spellman points out, the ROI on such content is often lacking. eBooks that "take months to create" may only "deliver 'leads' that convert to revenue at maybe 1 per 1000." This inefficiency highlights the need for a new approach to long-form content creation.
Enter generative AI, a technology that is transforming the way B2B marketers create content. By leveraging advanced algorithms and natural language processing, generative AI can quickly and easily repurpose old content or create entirely new pieces, allowing marketers to produce high-quality, long-form content at scale.
Generative AI tools are at the forefront of this innovation, offering platforms where long-form content creation is no longer a bottleneck but a streamlined, efficient process. With generative AI, marketers can input key information, such as product specifications, industry trends, and target audience insights, and the AI will generate a comprehensive, well-structured piece of content in a matter of minutes.
As the B2B marketing landscape continues to evolve, it's clear that generative AI will play an increasingly important role in content creation. By harnessing the power of this technology, B2B marketers can create the high-quality, long-form content that their audience craves, without the time and resource constraints of traditional content creation methods.
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Key takeaways to help CMOs integrate AI into their team's workflows
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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:
6 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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