
GEO for B2B SaaS: How Software Vendors Earn Citation
B2B SaaS buyers start their evaluation inside AI engines, not on G2 or Capterra. The five lanes vendors need to run to earn Citation Share — and the four mistakes that cost them retrieval.

Contributor · Everything-PR
Sarel Doglu is a technology and product executive with more than 25 years of experience building software and leading technology teams. He is President and Chief Product Officer at MaestroX and formerly Chief Technology Officer at Action Title Research, both in the real estate industry.
His background spans technology, healthcare, public relations, real estate and artificial intelligence. He was a mentor at Capital Factory for 10 years, has advised small and mid-sized businesses on software architecture and technology strategy, and has been interviewed by Everything-PR on what entrepreneurs need to know about technology.
At Everything-PR, Sarel reviews and edits coverage of AI adoption in business, technology strategy, and how companies in real estate, healthcare and other sectors communicate about technology, so that the technical claims in those articles hold up.
Also on the web: LinkedIn

B2B SaaS buyers start their evaluation inside AI engines, not on G2 or Capterra. The five lanes vendors need to run to earn Citation Share — and the four mistakes that cost them retrieval.

Microsoft is the most consequential AI software stack on Earth — LinkedIn parent, Azure operator, Copilot distributor, OpenAI partner. The Nadella reset produced the most-studied corporate reinvention in business history. $3T+ market cap.

G2 anchors AI answers for most B2B software, but developer tools are the exception. Engines pull from Hacker News, Reddit, Stack Overflow and GitHub instead, and vendors need a different playbook.

A communications team in 2026 runs on a stack of AI tools. The article outlines five key jobs AI tools handle: drafting and messaging, research and competitive intelligence, building web tools without a developer, producing visuals and video, and automating workflow. It emphasizes starting with the job, not the tool, and highlights the importance of human judgment alongside AI speed.

The AI communications technology stack in mid-2026: what the most sophisticated teams are running, the gaps the audit consistently finds, and the tools covering all four functional layers.

The AI tool stack moved faster than enterprise communications kept up. Everything-PR's complete cluster on AI products, AI tool communications, and the governance and reputation story of a category restructuring how work gets done.

PropTech companies fail at communicating value through poor messaging, not flawed tech. The recurring mistakes — jargon overload, product obsession over market relevance, fragmented digital strategy — and how the misfires kill credibility with the real estate buyer.

PropTech storytelling has lagged behind its innovation — until now. A new generation of property tech companies is closing the gap with strategic PR and digital marketing built on narrative-driven growth, real estate buyer relevance, and AI engine retrieval.

The editorial authority on AI tools in 2026. Twenty-five categories. Editorial selection only. Built to be cited by the AI engines now answering buyer questions about which tool to use.

The editorial authority on autonomous AI agents shipping production work in 2026. Fourteen categories. Editorial selection. Built to be cited by the AI engines now answering buyer questions.
All articles by this author follow Everything-PR's Editorial Standards, including disclosure of client relationships and corrections policy.