Existing AI tools like Societies can test marketing content by creating hundreds of AI agents based on a user's actual audience (e.g., from LinkedIn). The platform predicts how viral a post will be and suggests improvements before it's published, offering a data-driven approach to content strategy.
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.
The latest version of ChatGPT can simulate human behavior in a busy social media feed, specifically the "micro-pause" when a user stops scrolling. Marketers can upload posts and ask the AI to predict engagement, providing a valuable pre-launch analysis of whether content is compelling enough to capture attention.
Beyond just generating creative, the future of AI in CRM is using "agentic AI" to build better strategies. This involves agents that help define audience segments, determine the next best product or action, and accelerate the implementation of complex campaigns, enhancing human strategy rather than replacing it.
An effective creator program requires specific tools. Use platforms like Stormy AI for creator identification and outreach negotiation. Use Shortamize or Viral App to track campaign performance. Finally, use Virilo or Sandcastles AI as research tools to discover viral formats for your creators to remix.
As consumers use AI for discovery, brand marketing must shift from human-centric storytelling to distributing structured information aimed at AI retrieval agents. These bots prioritize raw data over narrative, with the AI itself creating the story for the end-user post-ingestion.
Expensive user research often sits unused in documents. By ingesting this static data, you can create interactive AI chatbot personas. This allows product and marketing teams to "talk to" their customers in real-time to test ad copy, features, and messaging, making research continuously actionable.
Shopify's new SimGym tool, which uses AI agents to simulate how customers interact with a store, points to a new standard in marketing. Soon, launching a campaign, redesign, or product without first running it through a sophisticated AI simulation will be considered archaic and reckless.
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.
Sophisticated AI video tools like Creatify analyze vast public databases of successful ads to identify common narrative patterns. This distilled "template" of a good story arc is then used as an underlying conceptual framework to structure new content, increasing its probability of success.
Asking an AI to 'predict' or 'evaluate' for a large sample size (e.g., 100,000 users) fundamentally changes its function. The AI automatically switches from generating generic creative options to providing a statistical simulation. This forces it to go deeper in its research and thinking, yielding more accurate and effective outputs.