Elevate AI-generated marketing ideas by including a document of behavioral psychology principles (e.g., loss aversion, reciprocity) as part of your initial inputs. This prompts the AI to connect your brand's narrative not just to customer needs but also to fundamental human biases, resulting in more persuasive creative.
Related Insights
Instead of starting with academic studies, analyze what top brands are already doing successfully. Deconstruct their tactics to uncover the underlying behavioral science principles, which you can then apply with confidence to your own business.
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.
Buyers are motivated either by moving toward a desired outcome (possibility) or away from a problem (pain). Marketers often unconsciously favor one style based on their own personality. Crafting copy that addresses both motivations allows you to resonate with a broader, more diverse audience.
Marketers should use AI-driven insights at the beginning of the creative process to inform campaign strategy, rather than solely at the end for performance analysis. This approach combines human creativity with data to create more resonant campaigns and avoid generic AI-generated content.
Before asking an AI for creative ideas, feed it a document defining your "category entry points"—the specific moments or triggers when a customer should think of your brand (e.g., "annual planning"). This strategic input ensures the AI's output is tied to specific buying moments, not generic concepts.
To replace a technical expert in a sales process, an AI's value isn't just its data. It should be prompted to explain concepts through storytelling, visualizations, and 'future scaping.' This shifts the AI from a mere information-dispenser to a persuasive communicator that resonates with a buyer's emotions.
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.
Simply using one-sentence AI queries is insufficient. The marketers who will excel are those who master 'prompt engineering'—the ability to provide AI tools with detailed context, examples, and specific instructions to generate high-quality, nuanced output.
Instead of brainstorming in a vacuum, upload raw transcripts from recent sales calls into a pre-loaded AI project. This provides the AI with the exact language, frustrations, and goals of your target customers, enabling it to generate highly relevant and authentic ad campaign ideas.