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Instead of accepting a single AI output, generate multiple versions of your landing page copy. Then, have the AI create and embody different "judge" personas (e.g., a skeptical CFO, a distracted founder) to score each version, merging the best elements into a final winner.
The true power of AI in marketing is not generating more content, but improving its quality and effectiveness. Marketers should focus on using AI—trained on their own historical performance data—to create content that better persuades consumers and builds the brand, rather than simply adding to the noise.
Develop superior AI-generated copy by first using an AI agent to research and deconstruct the frameworks of top marketers. Then, feed the AI examples of your own writing to distill a unique brand voice. Combining these into a custom 'skill' produces consistent, high-converting copy that feels authentic.
The traditional "test and learn" mantra is flawed because teams often start with a weak set of creative variants. By using predictive AI to generate a diverse but pre-vetted, high-performance set of options, marketers can ensure their tests are more meaningful and aren't just optimizing a bad strategy.
Instead of using AI to write final copy, leverage it as a brainstorming partner. Dave Gerhardt uses ChatGPT to generate 15 variations of a subject line. This process allows him to cherry-pick words and phrases, combining them into a superior, human-crafted final version.
Instead of asking AI for a final answer, use it as a sophisticated focus group. Prompt it to embody different customer personas (e.g., "a left-leaning feminist," "a conservative male") and provide feedback on your messaging from those perspectives. This helps refine copy before market testing.
To make AI-assisted writing more effective, first create detailed personas of your target readers. Then, have these AI personas review your drafts, providing specific feedback on clarity, impact, and what would make them disengage. This allows for unlimited, targeted feedback cycles.
Instead of guessing at marketing copy, build an AI model of your ideal customer. By feeding it internal data like call transcripts and external data like forum posts, this "digital twin" can review and rewrite your marketing materials using the customer's exact language.
Instead of asking an AI tool for creative ideas, instruct it to predict how 100,000 people would respond to your copy. This shifts the AI from a creative to a statistical mode, leveraging deeper analysis and resulting in marketing assets (like subject lines and CTAs) that perform significantly better in A/B tests.
Instead of general analysis, feed your AI a defined customer persona (e.g., "Growth Gabby") and ask it to evaluate a competitor's website copy from that specific perspective. This uncovers messaging weaknesses that directly relate to your target audience's concerns, like complexity or pricing.
AI's strength in copywriting is not generating final text, which often lacks a human touch. Instead, use it as a research assistant to find unique concepts, analogies, or data (like the 'Michelangelo effect') that can serve as the core, attention-grabbing idea for your campaign.