
Keeping content libraries fresh and engaging in B2B marketing is a necessity. The challenge, however, lies in the constant demand for new material and the limited resources at most marketing teams' disposal. That's why more and more teams are starting to turn to generative AI tools as a solution that not only breathes new life into existing assets but also revolutionizes the content repurposing process at scale.
One of the primary reasons generative AI is so well suited to help marketing teams combat content stagnation, is its ability to transform old, pre-existing content. A prime example of its impact can be seen with Avanan, a cybersecurity firm that struggled with the consistent generation of relevant content. By recently integrating generative AI tools into their content strategy, Avanan managed to leverage its extensive repository of past content to create fresh, new assets. The result has been a dramatic increase in email open rates, from a modest 17.3% to an impressive 54.8%.
The positive effects of content repurposing and its resulting relevant content are clear. Here are some ways you can keep your own content fresh and engaging:
1. Audit Existing Assets: Start by taking stock of your current content assets. Even those that might seem outdated can be transformed into fresh, relevant pieces.
2. Leverage AI for Efficiency: Certain generative ai tools can ingest existing materials and repurpose them into a variety of formats, tailored for different channels and campaigns, significantly cutting down on content generation time.
3. Personalize at Scale: Use AI to create personalized experiences. From emails to landing pages, customizing content for specific audiences increases engagement and conversion rates.
4. Foster Continuous Innovation: Lastly, stay open to the evolving landscape of generative AI and its applications in marketing. Staying on top of technological advances ensures that your content strategy remains on the cutting edge.
With the strategic application of generative AI technologies, B2B marketers can not only refresh their existing content libraries but also scale their content creation efforts efficiently. Embracing these tools is a strategic imperative for staying relevant and engaged with your audience and preventing against content stagnation.


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Discover how to implement a successful generative marketing strategy that will help you create personalized content, engage with customers in real-time, and optimize your campaigns for conversion.

In 2023, personalization is more important than ever before, and marketers can use AI to provide personalized experiences that increase customer engagement, drive conversions, build brand loyalty, and improve customer satisfaction.

Marketers are using AI to personalize content and recommendations for their audience through recommendation engines, email marketing, product customization, ad personalization, chatbots, personalized landing pages, and social media.

Account Based Marketing (ABM) is a go-to-market strategy that enables companies to personalize campaigns to their most valuable accounts. It’s historically been difficult to implement due to the significant upfront investment required, but the advent of new generative AI tools now allows teams to enhance conversions with greater ease.
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."
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"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."
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"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."
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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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