How Parts Town Scaled GEO and Achieved 31% Growth in Clicks

Parts Town is the global leader in mission-critical OEM parts distribution in the foodservice, residential and HVAC industries. Known for innovation, Parts Town was the first to market with e-commerce and mobile apps in the foodservice industry. To scale for their next phase of growth, they needed to evolve their digital platform away from a monolithic architecture to a more agile front end-led experience. At the same time, the team needed to be able to better manage AI traffic, scale GEO strategically and increase the volume of high-impact optimizations quickly.

As the Parts Town site has a massive product catalog, its modern, JavaScript-forward approach created an opportunity to better align with how search engines and AI crawlers discover and interpret critical content. Site speed was inconsistent, and performance and crawl efficiency varied across the site; crawl activity wasn’t focused on the most valuable product and category pages, making it harder to surface the highest-priority content.

With tens of thousands of parts, efficient crawling and clear internal linking were essential. However, key connections between high-value PLPs and PDPs were hidden behind RequireJS, and important PDP elements, such as product specifications and related links, were also rendered via JavaScript. While JavaScript creates a great experience for human users, AI Bots that are attempting to crawl key revenue-driving pages are unable to render JavaScript. Meaning this important content was completely invisible to the AI Search platforms that users rely on to understand and surface content to shoppers. As AI bots have increased their crawl activity (Botify’s analysis found that their activity grew 5.4x across 2025), the additional load further slowed the site, potentially creating friction for shoppers and risking conversion performance - especially considering that JavaScript content is invisible for AI bots.

To accelerate their growth, the Parts Town team needed a partner to help them improve crawl efficiency, enable faster optimizations without relying heavily on engineering resources, and build a foundation that could keep pace with the AI-driven future while keeping the focus on customers and their experience.

The Parts Town team partnered with Botify to access both a leading AI-first platform and an embedded team of search and AI experts, bringing strategy, execution, and measurement into one workflow. Together, the teams did a comprehensive audit, analyzing crawl behavior and cross-referencing Google Search Console keyword data. Consolidating these in a single place (rather than stitching insights together from multiple sources) made it easier to diagnose issues quickly, prioritize opportunities with confidence, and evaluate performance at both high and granular levels.

To improve discoverability at scale, Parts Town implemented Botify’s SpeedWorkers to pre-render key content coded in JavaScript, ensuring PLP and PDP pages could be fully accessed and understood by search and AI crawlers. This was especially important given their millions of SKUs: extensive crawling could strain performance while still leaving important parts of the product catalog underexplored. With Botify, the Parts Town team gained tighter control over crawl pathways and prioritization, helping search and AI engines focus on the pages that matter most, while protecting a fast experience for shoppers arriving from different marketing channels.

Finally, the team used Botify’s PageWorkers to rapidly test and deploy optimizations at scale, accelerating iteration cycles and reducing dependency on engineering resources. Some examples of these optimizations included removing facet links across 125k+ URLs, improving Schema on the Homepage and Contact Us pages, and optimizing pagination.  The result was a higher velocity of experimentation and a repeatable process for rolling out GEO improvements across the site.

The Parts Town team partnered with Botify to access both a leading AI-first platform and an embedded team of search and AI experts, bringing strategy, execution, and measurement into one workflow. Together, the teams did a comprehensive audit, analyzing crawl behavior and cross-referencing Google Search Console keyword data. Consolidating these in a single place (rather than stitching insights together from multiple sources) made it easier to diagnose issues quickly, prioritize opportunities with confidence, and evaluate performance at both high and granular levels.

To improve discoverability at scale, Parts Town implemented Botify’s SpeedWorkers to pre-render key content coded in JavaScript, ensuring PLP and PDP pages could be fully accessed and understood by search and AI crawlers. This was especially important given their millions of SKUs: extensive crawling could strain performance while still leaving important parts of the product catalog underexplored. With Botify, the Parts Town team gained tighter control over crawl pathways and prioritization, helping search and AI engines focus on the pages that matter most, while protecting a fast experience for shoppers arriving from different marketing channels.

Finally, the team used Botify’s PageWorkers to rapidly test and deploy optimizations at scale, accelerating iteration cycles and reducing dependency on engineering resources. Some examples of these optimizations included removing facet links across 125k+ URLs, improving Schema on the Homepage and Contact Us pages, and optimizing pagination.  The result was a higher velocity of experimentation and a repeatable process for rolling out GEO improvements across the site.