01Who the Client Is
A machinery parts manufacturer focused on OEM and custom components. It has exported for years, has complete brochures and spec sheets, and its website is several years old. Its buyers are equipment manufacturers and purchasers in Europe and North America — the classic 'strong product, weak online presence' manufacturer.
02What the Client Was Struggling With
- The site has existed for years, yet organic Google traffic stayed persistently low;
- Product count: over 500, product page content was heavily duplicated and nothing but spec lists;
- core product terms never ranked, so buyers could not find it;
- inquiries depended mainly on Google Ads, andthe moment ads stopped, inquiries fell to almost nothing.
03What We Found
- Chaotic keyword structure: product terms, industry terms and scenario terms were jumbled on the same level, with no split by buying stage;
- Thin product page content: nothing but model numbers and specs, with no answer to what buyers actually care about (application, material differences, MOQ, certifications);
- Search intent left uncovered: buyers searching decision terms like 'custom', 'OEM' or 'factory direct' had no page to land on;
- Ineffective internal linking: authority was scattered across hundreds of isolated product pages instead of flowing to core category pages.
04What We Did
- Rebuild product pages: turned spec lists into a 'demand coverage' structure — applications, material and process comparisons, MOQ and lead times, certification lists, FAQs;
- Build keyword clusters: rebuilt the keyword map around the three buying stages (awareness / consideration / decision), prioritising decision-stage long-tails;
- Improve internal links: built a 'category page → product page' pyramid so authority concentrates on core category pages;
- Create industry content: wrote in-depth content around real purchasing questions (selection guides, material comparisons, industry standard explainers);
- Build an overseas search-demand matrix: separated content by target market to reflect how English and Spanish demand differ.
05How the Numbers Moved
Data sources: Google Search Console and Google Analytics. Company names and part of the commercial data are anonymised to protect client privacy.
| Metric | Project start | Month 6 | Month 12 |
|---|---|---|---|
| Organic Traffic (monthly) | XX | XX | XX |
| Top 10 Keywords | XX | XX | XX |
| Qualified Leads (monthly) | XX | XX | XX |
| Ad dependency | High | Medium | Medium–low |
06Client Feedback
“We used to get fewer than 10 organic Google inquiries a month and were mostly propped up by ads. After the product page rebuild and keyword clustering, organic inquiries stabilised and we were able to cut the ad budget.
At the client's request, the company name and personal names are anonymised; ask during our conversation and we will explain what can be verified.
07Key Takeaways From This Case
- A product page is not a spec sheet — it isLanding pages matching search intent— this point matters especially for export websites;
- Keywords need to beby buying stage tiered — decision-stage long-tails are what actually drive inquiries;
- Internal linking decides whether authority reaches the pages that actually generate inquiries.