In B2B digital marketing, staying ahead of the curve is essential for success. One of the most significant developments in recent years has been the rise of generative AI and its potential to revolutionize content creation and SEO strategies. In this blog post, we'll explore some valuable insights shared by Kieran Flanagan, current CMO at Zapier and former SVP of Marketing at HubSpot, on how he leveraged generative AI to drive growth and engagement.
The advent of AI has provided an unprecedented opportunity to fill content gaps at scale. For organizations with strong domain trust, like HubSpot, the impact on traffic can be substantial. However, Flanagan cautioned that it's crucial to navigate this landscape wisely. A rushed or unrefined use of AI runs the risk of leading to a saturation point, diminishing returns over time.
To truly leverage AI, it's vital to focus not just on quantity, but on the quality of the content generated. Inspired by Brian Dean's SkyScraper Technique, Flanagan shared that HubSpot saw the best results by fine-tuning AI models to not just generate content, but to enhance it. This includes adding context, integrating video and imagery, and overall, creating a richer, more engaging content experience. This approach not only serves the immediate goal of filling content gaps but does so in a way that is more likely to generate engagement and add real value for your audience.
It's well-documented that Google's algorithm favors engaging content, utilizing engagement signals to refine search results. Therefore, creating content that fails to resonate with your audience is not a viable strategy for long-term success. That's why HubSpot's strategy pivoted to using AI in order to create content that not only ranked well but also meaningfully engaged and solved for the user.
For B2B marketing teams, the message is clear: generative AI holds immense potential for content generation and repurposing, but its power must be wielded with care. Lazy or untargeted use of AI is unlikely to yield the results you're looking for. Instead, focus on strategies that prioritize user engagement and content quality. Some key takeaways include:
The use of generative AI in content creation and SEO is not just about automating processes, but about enriching the user experience. By following the example set by HubSpot and focusing on quality, engagement, and continuous improvement, B2B marketing teams can harness the power of AI to drive growth and stay ahead in the competitive digital landscape. As AI continues to evolve, it's crucial to stay informed, experiment wisely, and always keep the needs of your audience at the heart of your strategy.
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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."
"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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