The Quiet Power of Specialised LLM Visibility Tools: A Sector-by-Sector Breakdown

The Quiet Power of Specialised LLM Visibility Tools: A Sector-by-Sector Breakdown

Here’s the uncomfortable truth most businesses haven’t grasped yet: AI isn’t recommending your brand nearly as much as you think it is. And it’s not even consistent across platforms. A brand visible on ChatGPT might be a ghost on Google AI Overview. If you’re not tracking this, you’re flying blind.

My theory? The rise of specialised tools is the only way forward. General visibility tools aren’t cutting it anymore because no two industries are tackling the same AI challenges. Healthcare isn’t e-commerce. Finance isn’t manufacturing. Yet, many businesses are treating AI optimisation like it’s a one-size-fits-all game. Spoiler: it’s not.

Across our dataset of 2361 AI prompts run for 29 businesses, the visibility disparities are glaring. Some brands hit 100% mention rates on certain providers (Viking Pumps, for example, are visible everywhere), while others barely scrape into double digits. Contxt itself is at 13%. That stings. But it’s also a reminder of why tailored visibility strategies matter.

When industries lean into specialised LLM visibility tools made for their unique challenges, the results speak for themselves. Let’s break this down sector by sector.

Healthcare: Navigating Regulation and Precision

Healthcare is probably the toughest nut to crack when it comes to AI visibility. Why? It’s not just about appearing in answers; it’s about appearing with the right information. Misleading recommendations here can’t just hurt a brand; they can harm patients.

One client we’ve worked with in the healthcare sector struggled with this exact issue. Their visibility score across our testing network was less than 40%. Across ChatGPT, Perplexity, and Google AI Overview, their brand was recommended in some scenarios but totally absent in others. Related reading: this piece about the llm consolidated testing framework: 36 signals, 37,00.... Related reading: The 3 Types of Prompt That Decide Whether AI Recommends Y.... Worse, even when their name appeared, the AI responses weren’t citing their most up-to-date clinical data.

Here’s what we did: we targeted “knowledge-cutoff” prompts to verify how AI systems respond to outdated queries in healthcare. Out of 12 businesses tested for buying intent, healthcare brands had the widest variance in mention rates based on query type. We built specific visibility experiments designed to ensure clinical authority was prioritised. The outcome? A 67% increase in AI-recommended instances where their latest studies were cited. This wasn’t just visibility optimisation; it was trust optimisation.

If you’re in healthcare, the takeaway is simple. You need tools that focus on data precision and regulatory compliance. Anything less is a risk your competitors won’t hesitate to exploit.