Personalization is one of the most powerful techniques that marketers use to connect with their audience. By providing personalized experiences, marketers can increase customer engagement and satisfaction, drive more conversions, and build stronger brand loyalty. However, creating personalized content and recommendations for each individual can be a daunting task. This is where AI comes in. In this blog post, we'll explore how marketers are using AI to do personalization.
Recommender systems are a popular way of providing personalized recommendations to customers. Generative AI algorithms can analyze customer behavior, preferences, and historical data to generate recommendations for products, content, and services. By tailoring recommendations to each individual, marketers can increase engagement and conversions.
Email marketing is another area where generative AI can be used for personalization. By analyzing customer data and behavior, AI algorithms can generate personalized subject lines, body copy, and calls-to-action. This not only improves open rates and click-through rates but also enhances customer satisfaction and loyalty.
Product customization is becoming increasingly popular among consumers. Generative AI can help marketers provide personalized products by analyzing customer preferences and generating customized designs, features, and options. This enables marketers to offer a unique and personalized experience that sets their products apart from competitors.
Personalized ads are more effective than generic ones. Generative AI can help create personalized ads by analyzing customer data and behavior, generating ad copy, and even creating custom images and videos. This enables marketers to provide a more relevant and engaging experience that resonates with the target audience.
Chatbots are becoming increasingly popular for customer support and lead generation. Generative AI can help create more human-like conversations by analyzing customer data and learning from past interactions. This enables chatbots to provide more personalized and effective responses that improve customer satisfaction and retention.
Landing pages are an important part of any marketing campaign. Generative AI can help create personalized landing pages by analyzing customer data and behavior, generating customized content, and even designing unique layouts. This enables marketers to provide a more relevant and engaging experience that drives conversions and builds brand loyalty.
Social media is another area where generative AI can be used for personalization. By analyzing customer behavior and preferences, AI algorithms can generate personalized social media posts, hashtags, and even captions. This enables marketers to create more engaging content that resonates with their target audience.
AI is transforming the way marketers approach personalization. By using this technology to analyze customer data, behavior, and preferences, marketers can provide more personalized experiences that improve engagement, conversions, and brand loyalty. As generative AI continues to evolve, we can expect to see even more innovative uses of this technology in the world of marketing.
Discover the top AI marketing tools for 1:1 ABM campaigns in 2025, and see why Tofu leads in personalization, multi-channel automation, and ROI.Introduction
Here is a breakdown of the best AI tools for multi-channel B2B marketing campaigns.
For B2B marketers, generative AI is no longer optional—it’s essential. ChatGPT offers broad capabilities at a low cost. Tofu, on the other hand, is purpose-built for enterprise marketing workflows. Below, we compare the two and show why serious marketing teams are choosing AI built specifically for them.
Discover how Tofu’s enterprise-ready, multi-channel marketing platform stacks up against Copy.ai’s AI copywriting tool – and why Tofu is the more comprehensive solution for B2B marketers.
Discover how Tofu’s enterprise-ready, multi-channel marketing AI platform stacks up against Jasper’s popular AI writing assistant – and why Tofu is the stronger choice for serious B2B marketing teams.
Tofu vs Mutiny: Which ABM platform comes out on top? Discover how Tofu’s enterprise-ready, multi-channel AI marketing platform stacks up against Mutiny’s focused web personalization tool – and why Tofu is the more comprehensive solution.
Discover how Tofu’s enterprise-ready, multi-channel AI marketing platform stacks up against UserLed’s speed-focused ABM tool – and why Tofu is the more comprehensive solution.
Just-in-time communication replaces outdated sequences by using real-time signals and AI to deliver timely, relevant, and personalized outreach across channels to improve engagement, reduce wasted effort, and focus on meaningful interactions over spam.
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
Sign up now to receive your copy the moment it's released and transform your ABM strategy with AI-powered personalization at scale.
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