Last updated: October 12, 2023
As we move further into 2023, it’s clear that AI is no longer just a buzzword, but a game-changer for marketing teams. With AI technology continuing to evolve, it’s important for marketers to stay up-to-date on how it’s affecting different roles in the industry. After speaking with hundreds of marketers, it's clear that right now there is an equal mix of excitement and also trepidation. This technology is new for marketing teams and will take some time for teams to trust new tools and allow AI to handle the heavy lifting of many of their day-to-day workflows. In this blog post, we'll explore how marketing teams should be thinking about AI in 2023 and how it is affecting different roles.
Head of Marketing: With AI technology becoming more widespread, the role of the Head of Marketing is evolving. In addition to managing a team of marketers, they are now responsible for overseeing the implementation of AI technology and its impact on marketing campaigns. They need to understand how AI is used to create hyper-personalized content, analyze data, make predictions and recommendations, and optimize marketing campaigns. This can help them make informed decisions, streamline processes, and improve the overall effectiveness of marketing efforts while relying less on expensive, external agencies and leveraging in-house resources.
Demand Gen: AI is revolutionizing demand generation by allowing marketers to identify and target specific audiences with personalized content. By leveraging AI technology, demand gen teams can analyze data and make predictions about potential customers’ behavior, interests, and needs. This helps them create targeted campaigns that increase engagement and conversion rates. Additionally, AI-powered chatbots can assist with lead qualification and even scheduling meetings, reducing the workload on the demand gen team.
Content Marketing: AI is also changing the way marketers approach content creation. Content marketing teams can use AI to analyze data on their target audience, identifying patterns and preferences that can inform the creation of more effective content. AI can also be used to generate personalized content from scratch, such as social media posts, blog posts, or product descriptions, saving time and resources. Leveraging AI can also allow content marketers to create one piece of content and then scale it to hundreds of variations based off of the persona, industry, or even account of the target. However, it's important to ensure that the content is still authentic and aligns with the company's messaging and brand voice.
Social Media Marketing: AI-powered social media tools can help marketers optimize their social media strategy by identifying trending topics and analyzing sentiment, allowing marketers to create content that resonates with their audiences on each respective channel. Additionally, AI can help with social media advertising, targeting the right audience and optimizing the ad placement to increase visibility and performance of social campaigns.
Paid Digital: When creating ad targeting and optimizing ad spend, AI platforms can provide huge value for growth marketers who focus on paid digital. AI can suggest the most effective ad placements and even adjust bids in real-time by analyzing customer data and behavior across channels and pairing that with data from non-paid marketing campaigns. Additionally, AI can help generate ad creative, including images and copy that are more likely to result in a conversion.
Design: AI can assist designers in creating more personalized, targeted, and eye-catching designs. New tools can suggest and create design elements that are more likely to resonate with the target audience. Additionally, AI can automate routine design tasks, freeing up time for designers to focus on more creative initiatives.
Exciting Opportunities:
There are many exciting opportunities for marketers with the use of AI. AI can help drive more personalized and targeted campaigns, resulting in higher engagement and conversions. Additionally, AI can automate routine tasks, freeing up time for marketers to focus on more strategic initiatives. Finally, AI can help identify trends and insights that may have been missed otherwise.
Possible Reasons for Concern:
However, there are also some reasons for concern with the use of AI. AI-powered tools may not always be completely accurate or ethical, and there is a risk of over-relying on AI and losing the human touch. Additionally, there is the potential for AI to replace jobs and displace workers in the marketing industry.
In conclusion, marketing teams should be thinking about how AI can be leveraged to drive results in 2023. While there are exciting opportunities with the use of AI, it's important to ensure that it is used ethically and in line with the company's values. Additionally, marketers should be aware of the potential risks and ensure that AI does not replace the human touch in marketing.
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
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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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