With the introduction of AI, the commercial landscape of the internet is changing fast. AI tools are taking an ever-growing role in how consumers search for products, and businesses across all industries should be accounting for this change to stay visible on a new avenue.
Engineering firms are among the many groups affected by this change. Users searching the web with AI tools now represent a strong share of potential clients, and a firm’s visibility strategy should be adjusted accordingly to capture this new audience. This guide will provide an overview of how engineering firms can adapt existing SEO strategies into a generative engine optimization (GEO) plan to maintain traffic on the changing web.
A Quick Intro to Engineering Generative Engine Optimization (GEO)
Many business owners and firm leaders are familiar with search engine optimization (SEO). This is the practice of optimizing web content to achieve a higher position on a search engine results page. GEO is a new subset of SEO that aims to optimize web content for appearances and citations in AI tool responses.
When prompted to find info on the web, an AI tool conducts a search that is effectively the same as a human user’s search, with a few key differences. Because the searches are similar, SEO practices still apply to GEO, as the desired content has to rank highly enough for the AI tool to trust it.
GEO applies to the content itself; AI tools prefer content with a clear question-and-answer structure, a legible backend, and links to more optimized content. Furthermore, AI searches are actually composed of multiple different queries; a large part of GEO is accounting for these additional questions to increase content coverage.
Building an Engineering GEO Strategy
Identify Priority Engineering Buyer Prompts
Where an SEO strategy begins with identifying important keywords, a GEO strategy starts with possible buyer prompts. Engineering firms should consider the questions that potential clients might be asking across multiple stages of the hiring process. Identifying these questions, as well as determining what the best brand-controlled answer is, provides the foundation for later GEO content.
Identify Engineering Query Fan-Outs
After compiling an additional list of questions, firms should consider the related questions that an AI model might pair with a main query. These sub-searches, called “query fan-outs,” represent additional chances for brand content to be used or cited in an AI response, making them just as important as the primary searches. Many AI models allow users to peek into their logic, which can often display query fan-outs for analysis.
Map Fan-Outs to Search Results
Once a list of main questions and fan-outs has been created, testing these questions in traditional search engines is a strong next step. This will show where a given firm’s content is ranking, as well as what pages are occupying the top spots and where competitors are appearing. This information helps guide content creation, as well as providing a valuable insight into the SEO performance of preexisting materials.
Create or Optimize the Right Engineering Pages
Having analyzed possible client prompts and their related fan-outs, firms can then begin to create relevant pages. The main principle of GEO content is to provide the answer to an AI’s search prompt in a clear, concise, and front-loaded manner, while retaining strong SEO visibility. Posting highly visible, quantitative, low-fluff statistics makes it easy for an AI to mine the information its user has requested, making it more likely for it to return a brand-controlled page in its response.
Depending on the list of queries and fan-outs generated in the preparation phase, relevant pages could include blog posts, case studies of past work, service and regulation compliance pages, or FAQs. To maximize AI readability, each of a firm’s services should be based on its own distinct page. Ensuring every new page provides a clear answer to a specific question and aligning new material to priority fan-outs are the best ways to retain traffic in an AI-focused search environment.
Build Authority and Improve Rankings
Once GEO pages have been posted, their SEO performance can then be enhanced. Focusing on traditional trust signals like internal links, external backlinks, clustered supporting content, thought leadership, and industry mentions will increase the authority of GEO content, placing it higher on search engine result pages.
While the practice of an AI search is very different from the user’s perspective, the material differences between a human search and an AI search are actually very few. AIs still route their queries through traditional search avenues and are more likely to investigate links with high rankings and rich trust signals. This is why GEO should be seen as a complement to SEO, rather than a replacement; SEO gets content placed in front of an AI tool, and GEO encourages it to forward that content to its user.
Measure Engineering GEO Performance
The work of GEO isn’t done once the relevant content has been published. Continuing to track the performance of this content in AI searches is a critical part of GEO that allows a firm to continuously improve its material and increase visibility. Using third-party tools or test prompts, firms can track how often AI tools locate their content and cite it in responses in order to determine how effectively their content is structured.
In addition to direct visibility tracking, it’s also useful to track the visibility of competing firms. Keeping an eye on what gets cited instead of brand content can provide a useful insight into what changes need to be made. Many web analytics services also allow clients to track how many visitors are referred from AI tools, which is a reliable indicator of how GEO content is performing.
Conclusion
As AI tools become more prevalent in web searches, engineering firms should adjust their web visibility strategy to account for this shift. To create a GEO strategy, firms should determine possible questions that clients might ask an AI, along with the related fan-out searches that the AI could make. Firms can then analyze what content ranks highly for those searches, as well as where their own pages fall in result rankings.
Using this information, relevant content can be created with a clear, concise, answer-focused structure. Finally, firms should continuously track the performance of GEO content, as well as competing material, and make adjustments to keep gaining traffic from AI models as search trends continue to shift.