SN Machinery sells B2B industrial equipment. We built its website, which launched in April 2026. From almost zero website purchase enquiries, the business now receives a steady flow representing $40K–$45K in monthly sales opportunity at its typical order value.
Our work combined a new website with AEO and GEO: helping the business become a useful source for AI-generated answers. We started with what buyers ask, studied the related searches ChatGPT makes, and created content to answer those questions.
What we did for AEO and GEO
Researched buyer queries and ChatGPT's fan-out searches
We worked to understand the queries behind equipment purchases and what ChatGPT searches when answering them. That included query fan-out: the related searches that help an AI system gather information for a broader answer.
This informed which questions the website needed to answer. The aim was to cover the supporting information behind a buying decision, as well as the initial question.
OpenAI describes how ChatGPT Search rewrites a request into targeted searches and may follow up with more specific queries. Our work used that research behaviour to guide content priorities.
From buyer queries to useful AI sources
Understand buyer queries
Research the questions behind an equipment purchase.
Study ChatGPT fan-out
Examine the related searches used to build an answer.
Publish the answers
Create comparisons, guides, and product information around those questions.
Track and improve
Review search visibility and AI citations to guide the next work.
Built content around the answers buyers needed
We used the query research to shape the site's supporting content and product information. The current website shows the kinds of buying questions that work addresses:
- Brand choice: a comparison of SPAC, Festo, Janatics, and Techno covers use cases, prices, range, and spares.
- Product selection: a cylinder-types guide explains the options and selection criteria.
- Technical fit: product specifications and the cylinder-force calculator help buyers understand dimensions and performance requirements.
The brand comparison is a concrete example. It gives a short recommendation by use case, compares the brands side by side, and then explains the trade-offs. That gives both buyers and search systems specific information to work with.
Supported discovery with the website foundations
We built the website and product pages with technical SEO, alongside the content and authority work. Category and brand browsing connect buyers with relevant ranges. The ESNC cylinder page brings model dimensions, indicative prices, application information, and answers to common questions together.
These pages give the supporting content somewhere relevant to lead: a product the buyer can investigate and ask about.
Strengthened the business presence beyond the website
We consistently worked on the website, Google Business Profile, and other business profiles alongside the content and authority work. The gains built gradually as that work continued.
Tracked visibility and used it to guide further work
After launch, we tracked Google Search performance and Microsoft AI citations alongside the client's reported purchase enquiries. The findings guided further page, content, and authority work. The original reports below show the visibility results across the supported Google and Microsoft experiences.
Turned discovery into a route to enquire
The website also needed to help visitors take the next step. Model tables let buyers filter by part number or size, compare the specifications, and request a quote beside the relevant item. Buyers who still need help choosing can use the cylinder-force calculator and explore related product ranges.
Two routes to a purchase enquiry
Know the model
Browse by category or brand
Compare the model
- Bore
- Stroke
- Indicative price
Filter by part number or size.
Need help choosing
Use the cylinder force calculator
Check the requirement
- Bore
- Rod diameter
- Pressure
See push and pull force, then explore product ranges.
Request a quote
Ask about the equipment through WhatsApp or a phone call.From launch to the current result
April 2026
Website launched
New website, starting from almost zero website purchase enquiries.
After launch
Track and improve
Search performance, AI citations, and client-reported enquiries guide further page, content, and authority work.
September 2026
Steady purchase demand
The client confirms that monthly demand is stable and growing.
Results and original reports
The commercial result is $40K–$45K in monthly sales opportunity, based on the client's verified purchase enquiries and typical order value. The platform reports show how often the website appeared and how many Google Search clicks it received.
Now appearing in 75% of tracked buying-query answers
SN Machinery now appears in 75% of the tracked AI answers for relevant buying queries. That presence grew gradually through consistent work on the website, Google Business Profile, and other profiles.
This is TCC-reported answer visibility within the monitored query set. The original Google and Microsoft reports below measure impressions and citations separately.
Microsoft: 10.8K citations in AI answers
The Bing Webmaster Tools report records 10.8K citations in its selected six-month window. These are references to the website across supported Microsoft Copilot, Bing AI summaries, and selected partner experiences. The report does not provide a separate ChatGPT total. Microsoft report documentation.
View the original Microsoft report
Google AI: 164K impressions
The Google report records 164K impressions over three months: appearances of website links in AI Overviews and AI Mode. This measures Google Search features, rather than the standalone Gemini app. Google report documentation.
View the original Google AI report
Google Search: 451K impressions and 3.61K clicks
The three-month Web report shows 451K impressions and 3.61K clicks. Google AI impressions are included in that Search total, so the two impression counts should not be added together.
View the original Google Search report
How the monthly sales opportunity is calculated
The client reports 80–90 verified purchase enquiries per month, with a typical order value of about $500. That gives $40K–$45K in potential monthly order value, valuing each enquiry as one potential order.
This is not a record of booked revenue. Enquiry volume and order value are client-reported; the search reports do not attribute individual enquiries to an AI platform.
What to apply to your own business
Start with a buying question your business should help answer. Then look at the related searches an AI system makes while researching it. Does your website answer the supporting questions about suitability, comparisons, specifications, and price?
Use those gaps to decide what to create or improve, and connect the answers to a relevant product or enquiry page. That is the link between AEO/GEO research and commercial delivery: understanding the questions, publishing useful answers, and giving interested buyers a next step.