SEO by vertical · Manufacturing
SEO for Manufacturing that supports a long sales cycle.
Industrial buying does not close in a single visit. An engineer researches the spec sheet, a buyer compares suppliers, a quality manager checks certification, and only then does the committee decide. Our SEO consulting structures the site to show up in each of those searches, with an indexable technical catalog and structured data that carries the information the industrial buyer looks for.
We work in English, Portuguese and Spanish. Headquarters in Belo Horizonte, Brazil.
01Overview
SEO for manufacturing
Industrial search is rarely done by the person who signs the purchase order. It is done by whoever specifies: the engineer who needs a part with exact tolerance, the buyer comparing three suppliers on lead time, the technician looking for a material's safety data sheet. Each searches in different language, and each carries different weight in a decision that usually runs through a committee, not a single person.
Netlinks treats that as the starting point of the mapping: identifying who searches for what, at which stage of the purchase, and turning each search into a page with complete technical data, not a generic "contact us" landing page. You get the work finished and approve it in the Netlinks App, the same standard we apply on B2B operations like SP Labor, a laboratory equipment supplier.
Since the cycle is long, often months between the first search and the close, the site needs to show up again at every stage: initial research, technical comparison, and final validation before signing. That is why a well-indexed technical catalog and product structured data carry more weight here than in any other B2C sector.
- 200+
- companies served since 2017
- R$ 100 M+
- in sales generated for clients
- 24h
- of tracking in the App and on WhatsApp
02Sector
What is different about SEO for manufacturing
Search volume for an industrial technical term is usually low compared to a consumer sector, but the intent is far more qualified: someone searching "CNC machining dimensional tolerance" or "1/2 inch pneumatic valve spec sheet" already knows exactly what they need. Long-tail technical mapping usually returns more than fighting for a high-volume generic term.
Committee decisions mean the same site has to convince different profiles: whoever specifies technically, whoever compares commercially, and whoever approves the purchase. That reshapes the product page, which needs full spec sheet, certification, lead time and a commercial contact on the same screen, without forcing the visitor through three different pages.
Industrial technical catalogs often carry hundreds or thousands of items, frequently pulled from an ERP that was never built with SEO in mind. URL architecture, pagination and indexing for each product sheet take as much engineering work as content work, because a poorly indexed catalog leaves most of the inventory invisible to Google.
03Scope
What is included in the work
The scope covers the three layers that decide whether an industrial catalog shows up in search: mapping by purchase stage, indexing engineering, and product structured data.
Mapping by purchase stage
Terms split by who searches (engineering, procurement, quality) and by stage (specification, comparison, validation).
Complete product sheet
Spec sheet, certification, lead time and a commercial channel on the same page, with no extra navigation required.
Large-catalog indexing
URL architecture, pagination and a sitemap sized for catalogs of hundreds or thousands of items coming from an ERP.
Product structured data
Product markup with technical spec and availability, helping Google and AI models understand exactly what each item is.
Supporting technical content
Application guides, technical-standard comparisons, and material that supports the decision of the engineer who specifies.
Authority in industry outlets
Backlinks and press coverage in industry publications and trade shows, reinforcing trust across the supply chain.
04Technical edge
Structured data that matters in manufacturing
Marking up `Product` with technical spec, code, availability and purchase method lets Google and AI models understand the exact item, not just the surrounding text. In an industrial catalog, this usually carries more weight than any copy optimization, because the buyer specifies by technical data, not by adjectives.
`Organization` with certification (ISO, industry technical standards) and `FAQPage` on a product-line page round out the markup. The full semantic markup practice is in structured data, validated in a staging environment before launch.
- Product with technical spec, code and availability
- Organization with certification and industry technical standard
- FAQPage on product-line pages
- Sitemap sized for a large catalog, staying under the per-file limit
05GEO
Technical specification is an AI question too
Industrial engineers and buyers already use ChatGPT and Gemini for technical questions before opening a supplier's catalog: "what's the difference between a ball valve and a gate valve", "standard for industrial water piping". Precise technical content, backed by structured data, has a better chance of being cited in that answer.
This sits in the same consulting plan, alongside GEO: SEO for AI, with citation tracking in AI monitoring.
06Checklist
What to review in an industrial technical catalog
- Complete spec sheet on every item, without forcing a PDF download just to see basic data.
- Friendly, stable URL per product, even when it comes straight from an ERP with an internal code.
- Certification and technical standard visible, not just mentioned in loose text.
- Lead time and commercial contact on the same screen as the spec sheet.
- Segmented sitemap by category, staying under the recommended per-file limit.
- Supporting technical content (application guide, standard comparison) linking back to the product sheet.
07Comparison
Manufacturing against consumer e-commerce
An industrial catalog and a consumer online store look similar on the surface, but the search and decision logic is different.
| Industrial B2B | Consumer e-commerce | |
|---|---|---|
| Who decides the purchase | A committee: engineering, procurement, quality | One person, in most cases |
| Sales cycle | Weeks to months | Minutes to days |
| What the page needs to have | Spec sheet, certification, lead time, commercial contact | Price, photo, review, buy button |
| Search volume per term | Low, but highly qualified | High, with price competition |
08Measurement
What you track in the App
Rankings by product line, catalog indexing coverage, organic traffic by purchase stage, and AI citations all land in the live report, with no waiting for month end.
Since the cycle is long, the first qualified traffic movement usually shows up in 60 to 90 days, and the impact on closed sales follows the pace of the sales cycle itself. The consulting presents that estimate right in the diagnosis, along with the technical search volume gathered for the sector.
09The deliverable
What you receive
Finished work, approved by you in the App and shipped. Not a report that only describes the problem.
Mapping by purchase stage
Terms split by profile (engineering, procurement, quality) and by stage of the sales cycle.
Complete product sheet
Technical spec, certification, lead time and commercial channel on the same page.
Indexed catalog
URL architecture, pagination and sitemap sized for large catalogs coming from an ERP.
Product structured data
Product, Organization with certification and FAQPage marked up by product line.
Supporting technical content
Application guides and standard comparisons, linking back to the product sheet.
Live report in the App
Rankings, indexing coverage, traffic and AI citations, 24 hours a day.
10How it works
From the audit to the page going live
The same path on every project, with an owner and a date on each step.
- 01
Diagnostic conversation
One meeting to understand product lines, sales cycle and how the catalog is generated today. No commitment.
- 02
Audit and mapping
Catalog crawl, item-by-item indexing check and a search map by purchase stage.
- 03
Impact-ranked plan
Each product line gets a technical search volume and structuring effort estimate.
- 04
Tracked execution
Product sheets, structured data and technical content enter production with the consultant reviewing.
- 05
Approval in the App
You approve each deliverable before it goes live and see the full history of what was done.
- 06
Course correction
The plan is adjusted monthly against real data. Every quarter leadership gets the executive read.
11Who leads
Who leads your project
The three of them own the process and manage the team on every account. No senior who shows up at kickoff and disappears: they sign off on the plan, review the work and talk to your team.
Digo Garcia
Founder and CAIO
Over 20 years in digital. Built and scaled Letras.mus.br, then worked at Méliuz and in the joint venture with Globo.com. Owns AI, technical SEO and engineering inside every project.
Letras.mus.br · Méliuz · Globo.com
André Mousinho
Chief SEO Officer
Comes from Rock Content, Tray/Locaweb and LWSA. Designs the keyword mapping, the content architecture and the GEO strategy that turns a brand into the answer.
Rock Content · Tray/Locaweb · LWSA
Gabriel Raposo
Chief Authority Officer
Comes from Ambev and Agibank. Owns link building, digital PR and the authority that holds up both rankings and citations inside AI answers.
Ambev · Agibank
And the team behind them: Nathália Barcala (cofounder and COO, governance), Roberto Murta (CTO), Marcelo Ligere (senior advisor, 30+ years, formerly Grupo Globo) and Alfred, the artificial intelligence that runs the day to day: delivery queue, reporting and 24/7 support on WhatsApp.
12Who it is for
Where this work pays off the most
Manufacturer with a large, poorly indexed catalog
Hundreds of items in the ERP, but only a fraction show up on Google. Indexing engineering is usually the fastest win in this scenario.
Manufacturer with a long sales cycle
A purchasing committee researches for months before deciding. The site needs to show up at every stage of that research, not just the initial search.
Manufacturer exporting or selling through distributors
Needs technical content that speaks to engineering and procurement at the same time, often in more than one language.
13Case studies
Results with a name, a number and a date
Real projects, with what was done and what changed. No generic charts and no promises of a position.
FAQ
Frequently asked questions
Is industrial SEO worth it with such low search volume per term?
It is, because the intent is qualified. Someone searching an industrial technical term already knows what they need, and the low volume per term is offset by the number of technical variations and a higher conversion rate.
Our catalog comes from an old ERP, is that a problem for SEO?
It is the most common starting point. Indexing engineering organizes URL, pagination and sitemap so the whole catalog shows up on Google, even coming from a system that was never built for it.
How does SEO help when the decision is made by committee?
By structuring the same page to answer three different profiles: a spec sheet for whoever specifies, certification and lead time for whoever compares, and a commercial channel for whoever closes.
Does Product structured data make a real difference on a B2B site?
It does. It helps Google and AI models understand an item's spec, code and availability, which carries more weight in a technical decision than adjective-heavy copy.
How long before results show up in such a long sales cycle?
Qualified traffic usually shows up in 60 to 90 days. The impact on closed sales follows the pace of the sector's own sales cycle, calculated in the diagnosis.
Do you work with manufacturers that also sell outside Brazil?
We do, with the international SEO practice when the catalog needs a version in another language for engineering and procurement abroad.
Does the work cover technical content or just the product sheet?
Both. Application guides and standard comparisons support the specifier's decision, and link back to the product sheet that closes the sale.
Do AI models recommend an industrial supplier when someone asks about a spec?
Increasingly so. Precise technical content, backed by structured data, has a better chance of being cited in that answer, which falls under GEO work.
Keep reading
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