More Than Mentions: Why Your Strategy Needs More Than Just Visibility

Best practices

Feb 20, 2026

2/20/26

5 mins read

The shift from traditional search to AI-driven discovery requires more than just "showing up." It requires a holistic approach we call Generative Engine Marketing (GEM).

The shift from traditional search to AI-driven discovery requires more than just "showing up." It requires a holistic approach we call Generative Engine Marketing (GEM).

The shift from traditional search to AI-driven discovery requires more than just "showing up." It requires a holistic approach we call Generative Engine Marketing (GEM).

The shift from traditional search to AI-driven discovery requires more than just "showing up." It requires a holistic approach we call Generative Engine Marketing (GEM).

Most brands today are focused on Generative Engine Optimization (GEO)—the tactical "whack-a-mole" of trying to appear in a specific LLM response.

While visibility is important, it’s only one piece of the puzzle. At Share of Model, we’ve moved beyond pure-play GEO to pioneer Generative Engine Marketing (GEM), a framework funded in part by Google to integrate AI insights directly into paid, owned, and earned media.

Moving Beyond the "Whack-a-Mole" Strategy The GEM approach is built on four distinct modules that widen the aperture for marketers:

  • Brand Perception: Understanding the recurring semantic associations for your brand across models.

  • Search Visibility: Tracking real-time content visibility and how it overlaps with competitors.

  • Asset Evaluation: Testing and optimizing creative—including video—for multimodal agents.

  • Activation: Connecting these insights to platforms like Google Ads and TikTok to find new category entry points.

The GEM Advantage By treating AI insights as a "North Star" for strategy rather than just a search ranking, brands can use semantic associations to diversify their search themes. This allows for the creation of content that makes a brand unique rather than just "optimizing toward the average".

Similar Topic

Other Articles

Similar Topic

Other Articles