- NO.
- 016
- DATE
- Updated 2026-07-24
- READ
- ~2 min
- KIND
- Case study
- STATUS
- Reviewed
50+ Export Sites: a Top-10 Keyword Snapshot
A de-identified snapshot from an SEO delivery group's 50+ B2B export site portfolio, by industry code — and a plain statement of what it does not claim.
This cross-site snapshot comes from the project pool of an SEO delivery group supporting 50+ B2B export sites. Only de-identified numbers appear here — no client identities, company names, or real domains. The table comes from real phase review records (pulled 2026-05, de-identified). It is not a claim that I ran 50 sites myself: I was directly involved in planning-phase work on about 20 projects, plus existing-site checks and monthly reporting.
The snapshot (pulled 2026-05, industry codes)
| Code | Industry | Top-10 at start | Top-10 at pull |
|---|---|---|---|
| Site A | Flooring / building materials | 0 | ~1000 |
| Site B | General machinery / B2B | 0 | ~772 |
| Site C | Adjacent consumer products | 0 | ~648 |
| Site D | Machinery & equipment | 232 | ~578 |
| Site E | Energy equipment / B2B | 0 | ~469 |
| Site F | Electrical components / B2B | 0 | ~388 |
| Site G | Machinery & equipment | 0 | ~118 |
| Site H | General B2B | 0 | ~132 |
| Site I | Robotics / automation | 0 | ~66 |
On the spread: no inference yet
Explaining the gap between the high performers (A, B, C) and the low ones (G, H, I) means going back through page structure, content cadence, client responsiveness, and industry differences item by item. I do not yet have first-hand observations I could write down responsibly, so this section stays empty. Filling a "difference analysis" heading with inference would be easy; that is not how this blog works. When the observations are confirmed, they arrive here as a dated update.
Limits of this data
This is an end-value snapshot, not a control group with a shared starting point or time window. The numbers show the distribution of magnitudes; they cannot be compared for efficiency. Search demand differs enormously between industries, so absolute cross-industry comparison means little.
The data also cannot be used to attribute results to one person. Each site's outcome was moved simultaneously by content execution, technical fundamentals, client cooperation, industry demand, the algorithm, and outside events. This post treats the portfolio as an observation sample; it does not repackage a team's scope as individual ownership.
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