SEO by vertical · Technology
SEO for Technology that shows up in search and in AI answers.
A technology company sells to an audience that already asks ChatGPT, Gemini or Perplexity for the right tool before opening a website. GEO was built exactly for that shift, and it is in the technology sector that it pays off first.
We work in English, Portuguese and Spanish. Headquarters in Belo Horizonte, Brazil.
01Overview
SEO for Technology
Technology buyers search differently: a specific technical term, a direct comparison between tools, integration with a system the company already uses. That calls for content more precise and more current than the sector average, because this audience spots shallow information fast.
It is also the sector where AI-driven search is already established behavior: developers, product managers and technical buyers ask ChatGPT and Claude before deciding which tool to try. Showing up in those answers demands the same discipline in structured data and direct content that supports traditional SEO.
The work follows the Response Marketing Method with a focus on documented technical content, product structured data and constant monitoring of where the brand is already cited by AI.
- 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 technology
Technical terms usually carry lower search volume than generic ones, but much higher buying intent. One well-written page about a specific use case converts better than ten generic "what is" pages about the product category.
Documentation and changelogs, when indexable and well structured, work as a long-term SEO asset: they answer real technical questions, and that is exactly the type of content language models cite when someone asks how a tool works.
Competitor comparisons are the most searched content format in the sector, by humans and by AI alike. Writing that comparison honestly, without inflating your own tool, raises the chance of being cited as a trustworthy source instead of dismissed as marketing.
03Scope
What is in scope
The workstreams below connect around the same goal: closing the gap between the buyer's real technical question and the answer the company should already be giving, whether on Google or inside an AI conversation.
Citable technical content
Articles and use-case pages written with technical precision, answering the buyer's question directly.
Product structured data
SoftwareApplication, FAQPage and Article markup, reinforcing rich results and AI citation.
Honest comparisons
Comparison pages between tools, written to earn trust, not just clicks.
AI monitoring
Tracking which models and which questions already surface the brand as a citation.
04Technical edge
Structured data that matters in technology
`SoftwareApplication` with category, price and supported operating system helps Google present the tool correctly in search results. `Article` with a visible update date matters more in technology than in less dynamic sectors, because outdated content loses relevance fast.
- SoftwareApplication with category and compatibility
- FAQPage on product and documentation pages
- Article with visible publish and update dates
- Schema review at every relevant version release
05GEO
The sector most exposed to AI search
Of every sector Netlinks serves, technology feels the effect of GEO the most: technical buyers already ask an AI to compare tools rather than using traditional search, more often than not. This sits in the same plan, alongside GEO: SEO for AI and AI monitoring.
06Comparison
Technology against other B2B sectors
Technology and general business share a B2B audience, but the content format that converts differs.
| Technology | Business (general B2B) | |
|---|---|---|
| Format that converts most | Documentation and technical comparisons | Top and mid-funnel content |
| Where AI is used most | Tool comparison | Vendor research and referrals |
| Core schema | SoftwareApplication, Article | Organization, Service |
07Measurement
What you track in the App
Rankings by technical term, organic traffic tied to documentation and comparisons, and citations across dozens of AI models land in the real-time report, with no waiting for month-end.
Monitoring shows which model and which question already cite the brand, and which competitor shows up alongside it, the kind of information that guides the next piece of content to produce.
08The deliverable
What you receive
Finished work, approved by you in the App and shipped. Not a report that only describes the problem.
Citable technical content
Use-case articles with technical precision.
Product structured data
SoftwareApplication and FAQPage marked up per page.
Honest comparisons
Comparison pages between tools, written to build trust.
Live reporting in the App
Rankings, traffic and AI citations, 24 hours a day.
09Who 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.
10Who it is for
Where this work pays off the most
A software house or B2B SaaS
A well-built technical product that is invisible to people researching the category. Well-structured documentation and comparisons are usually the fastest lever.
A company that is strong on product but absent in GEO
Shows up well on Google, but has never been cited in a ChatGPT or Claude answer about its own category. AI monitoring reveals that gap first.
A small technical marketing team
Few people covering product, content and demand at once. The advisory takes on what needs dedicated research and structure time.
11Case 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
Why do technology companies need GEO more than other sectors?
Because technical buyers already ask AI models like ChatGPT and Claude to compare tools, often before using traditional search.
Does technical documentation count as SEO content?
It does, and it is one of the strongest formats when indexable and well structured, because it answers real questions and is exactly the kind of content language models cite.
Do you write comparison pages against a direct competitor?
Yes, honestly, without inflating the client's tool. It is the most searched format in the sector, and honesty is what builds trust with both the reader and the AI.
Which structured data matters most for a software company?
SoftwareApplication, with category, price and compatibility, plus Article with a visible update date.
How long before we show up in an AI answer?
It varies by model and by term competitiveness, but well-structured technical content tends to get cited faster than generic content.
Does Netlinks serve technology companies outside Brazil?
Yes, in English, Portuguese and Spanish, with the same method and the same delivery standard in all three languages.
Does English-language documentation count more than Portuguese for GEO?
It counts more when the target audience searches in English. The content's language needs to match the language the buyer actually uses when asking an AI.
Keep reading
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Next step
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