Optimizing for “share of prompt” sounds like a pretentious, jargony, buzzword bingo-ish admonition designed to prey on the fears of self-doubting marketers. How is optimizing for share of prompt any different from SEO or, if you’re a brand marketer, optimizing for share of mind? To be fair, the challenges are similar. The goal is to grow your business by ensuring that your goods or services are at the top of the consideration set. But that’s where the similarity ends.
Instead of buying or earning your way to the top of a SERP, you are now going to do everything you can to help a reasoning engine respond to a prompt with a glowing endorsement of your product and, in a perfect world, a link or a path to a direct transaction. How will you get an “intelligence decoupled from consciousness” to favor your brand? Let’s explore.
The Fundamental Difference
When someone Googles “best electric SUV,” they’re expressing intent to research. Google translates the currency of intention into wealth for its clients and shareholders. When a prospective customer asks ChatGPT “What car should I buy?” they’re expressing intent to be advised. The AI not only surfaces information, it makes judgments, weighs trade-offs, and advocates for specific choices. We’re no longer optimizing for findability; we’re optimizing for advocacy.
The New Competitive Landscape
A potential customer asks Claude, “What’s the best project management software for a 50-person marketing team?” The AI doesn’t return a list of options ranked by SEO metrics. It analyzes the requirements, considers team size and function, weighs pricing against features, and recommends Brand X with specific reasons why it beats Brand Y for this use case.
That recommendation just bypassed your $X million brand awareness campaign, your SEO-optimized content, your retargeting pixels, and your sales team. The AI made a contextual judgment based on data patterns, structured information, and algorithmic preference signals that have nothing to do with your traditional marketing metrics.
You’re now competing for the favor of reasoning engines that don’t experience emotional appeals, don’t respond to repetition-based awareness building, and don’t care about your brand’s heritage or personality. Not the way humans do.
What Machines Want
AI systems favor clarity over creativity, specificity over sentiment, and structured data over beautiful storytelling. Almost every external-facing data infrastructure was built for human consumption, not machine reasoning. Your websites optimize for emotional conversion. Your product documentation assumes human interpretation. Your customer success data sits in silos that AI systems can’t access.
AI-savvy competitors will be feeding AI systems structured data about performance benchmarks, detailed use case scenarios, integration capabilities, and real-time availability. When an AI needs to make a recommendation, which company do you think it will favor?
The New Metrics
This creates an entirely new category of marketing metrics:
Algorithmic Preference Score: How often does your product get recommended when AI systems have multiple viable options? Whatever we ultimately call it, how often you show up in a context window is the new new metric.
Prompt Share: The percentage of relevant AI queries that result in your brand being mentioned or recommended. This is the idea of “share of prompt” replacing “share of mind,” which ultimately impacts “share of wallet.”
Conversion via AI Mediation: The percentage of sales that originate from AI-driven recommendations rather than traditional marketing channels.
What To Do Right Now
Audit your data for AI accessibility. If a reasoning engine wanted to recommend your product, could it easily find accurate, comprehensive information about features, pricing, use cases, and performance metrics? Most brands fail this test.
Create AI-friendly content formats. You need structured FAQs, detailed specification sheets, clear use case documentation, and honest limitation discussions. The goal is to provide reasoning engines with the information they need to make appropriate recommendations.
Monitor AI recommendation patterns. Start tracking how your brand performs in AI-generated responses. Which competitors get recommended instead of you? This requires new monitoring tools and probably new vendor relationships.
Build algorithmic feedback loops. Traditional marketing campaigns optimize based on human response data. AI-era marketing requires optimizing based on how reasoning engines interpret and utilize your content.
The New New Thing
Optimizing for share of prompt requires capabilities most marketing organizations don’t yet have. This is an evolving hybrid discipline that combines marketing strategy, data science, and systems thinking. We have to do our best to retrain and upskill our marketing teams. My guess is we’ve got about 18-months before this is absolutely mandatory. On a corporate timescale, that might as well be tomorrow.
AI-mediated recommendations are trending to become the fastest-growing marketing channel. Your new job is to achieve algorithmic favor before your competitors lock you out of the answer engine economy. The shift from share of mind to share of prompt isn’t coming soon, it’s happening right now.
Author’s note: This is not a sponsored post. I am the author of this article and it expresses my own opinions. I am not, nor is my company, receiving compensation for it. This work was created with the assistance of various generative AI models.
About Shelly Palmer
Shelly Palmer is the Professor of Advanced Media in Residence at Syracuse University’s S.I. Newhouse School of Public Communications and CEO of The Palmer Group, a consulting practice that helps Fortune 500 companies with technology, media and marketing. Named LinkedIn’s “Top Voice in Technology,” he covers tech and business for Good Day New York, is a regular commentator on CNN and writes a popular daily business blog. He's a bestselling author, and the creator of the popular, free online course, Generative AI for Execs. Follow @shellypalmer or visit shellypalmer.com.
