Nowspeed Boosts Early AI Authority for a High-Performance Plastics Manufacturer

Before the GEO Work Began

Every manufacturer has product lines that perform exceptionally well but receive less attention online. For this high-performance plastics producer, a strategically important material category had become a blind spot—not for customers, but for generative AI engines.

When buyers and technical decision-makers asked AI for comparisons, properties, or application guidance, the company’s expertise rarely appeared in the answers. Their products weren’t part of the conversation early in the research process, where supplier perception often begins.

Nowspeed helped identify why AI systems overlooked the category and began reshaping how the information was presented, structured, and interconnected across the site. Now, just four months into the engagement, early authority signals show that generative engines are starting to surface the company’s material expertise where it previously went unseen.

The Challenge: Limited Visibility

A major high-performance material category wasn’t showing up in generative AI answers, leaving the company absent from early-stage inquiry moments that influence supplier discovery. For a manufacturer with decades of experience and proven products, this lack of representation created a visibility gap that could affect how future buyers compared materials or evaluated vendors.

Several factors contributed to the challenge:

• Minimal structured content around foundational material questions
• Limited contextual linking that helped AI engines understand related products
• Sparse representation of the material category across AI search surfaces
• Few signals pointing generative engines toward the company’s authority

AI engines struggled to interpret the material category in a way that reflected the company’s expertise, which limited how often the brand appeared in early research.

The GEO Strategy: Building from the Ground Up

The initial phase of the GEO program focused on creating a stronger foundation for AI visibility by clarifying the material category’s role and ensuring AI systems could reliably interpret, categorize, and surface the company’s answers.

1. A New Pillar Page to Anchor the Material Category

Nowspeed developed a comprehensive pillar page built around the category with the least AI visibility. The page provided:

• clear, buyer-friendly explanations
• structured sections optimized for generative engines
• contextual descriptions of properties and use cases
• content crafted to support question-driven AI answers

It served as a new anchor point for how AI systems interpret the category.

2. FAQ Content Targeting Early-Stage Buyer Questions

Additional FAQs answered the most common queries generative engines see about material selection, performance characteristics, durability considerations, and application needs—giving AI systems the concise, structured context they tend to favor.

3. Strengthened Interlinking With Related Materials and Applications

By connecting this category to adjacent products and relevant use cases, Nowspeed helped AI engines understand the relationships within the company’s broader offering—a critical step toward establishing visibility.

4. Monitoring AI Citations and Early Signals of Traction

A tracking framework captured citations, mentions, and LLM-driven traffic, allowing the company to see early progress as generative engines began indexing and citing the updated content.

The Results: Early Signals of Authority

Only four months into the engagement, the company is seeing clear movement across multiple AI platforms—evidence that the foundational restructuring of the material category is beginning to register with generative engines.

Success scores, which measure how often AI systems cite or reference the company when answering relevant questions, improved across all tracked surfaces:

• AI Overviews increased from 15% to 24%
• ChatGPT increased from 8% to 9%
• Perplexity increased from 9% to 25%

These gains were reinforced by steady traction in absolute citations and engagement:

• 66 citations in AI Overviews
• 176 citations in Perplexity
• 54 mentions in ChatGPT
• 1,000+ monthly LLM sessions
• 5.8% conversion rate on AI-driven sessions

Together, these indicators show that generative engines are beginning to recognize and surface the company’s material expertise more consistently—reintroducing the brand into early-stage research moments where it had been largely absent.

The Impact So Far: Trending Strong

The early gains show how foundational GEO work can influence AI-driven discoverability. By restructuring content around a previously underrepresented material category, strengthening relationships across product lines, and answering the questions AI engines encounter most often, the company is establishing its presence in a channel that will only grow in influence.

With only a few months of work behind them, the signs point toward increasingly stronger visibility, deeper engagement, and a clearer connection to the technical buyers who rely on generative AI for material research.

Want to Strengthen Your Visibility in Generative AI?

A GEO audit is the fastest way to see how generative engines assess your expertise. Let Nowspeed evaluate your AI visibility and outline the steps to improve it. Schedule your free GEO audit today.

Read More
How to Create FAQs that LLMs Will Actually Use
How AI Is Reshaping Paid Search: What Marketers Need to Know
Evaluating GEO Agencies: Questions to Ask Before You Hire