Helping B2B SaaS scale revenue with SEO/GEO
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Articles by Perry Steward
How to Fix Wrong AI Answers About Your Brand
To fix wrong AI answers about your brand, you change the sources the model reads: correct your own pages, fix the third-party listings it trusts, add clear structured facts, and update entity records like Wikidata. You cannot edit the model directly, but you can make the right answer the easy one to give. Key takeaways AI states wrong facts because it blends dated training data, stale third-party pages and a narrow set of retrieved sources, then phrases it with full confidence.
How to Run an AI Reputation Audit for Your B2B SaaS
An AI reputation audit is a repeatable check of how AI assistants present your brand: whether they mention you, how they frame you, whether the facts are right, and how often they recommend you against rivals. You run a fixed set of buyer prompts across the main engines, score the answers, and turn the gaps into a plan. Key takeaways An AI reputation audit measures four things across many prompts: presence, sentiment, accuracy and recommendation share. It is not a technical GEO audit.
Why AI Recommends Your Competitors (and How to Change It)
AI recommends your competitors because the sources it trusts mention them more often, more consistently, and in the right context for the buyer's question. It is not picking the best product. It is repeating the strongest pattern of independent signals, and the good news for a challenger is that you can change that pattern with focused work. Key takeaways AI recommends whoever the trusted sources mention most, most consistently, and in the most relevant context, not whoever is objectively best.
AI Reputation Management for B2B SaaS
AI reputation management is the practice of shaping what large language models like ChatGPT, Perplexity and Google AI say about your brand: whether they mention you, how they describe you, whether the facts are right, and whether they recommend you over rivals. For B2B SaaS, it is fast becoming the work that decides the shortlist. Key takeaways AI reputation is not the same as AI visibility. Visibility asks whether you appear.
AI Brand Monitoring for B2B SaaS
AI brand monitoring is the ongoing practice of tracking what AI assistants like ChatGPT, Perplexity and Google AI say about your brand: whether they mention you, how they frame you, whether the facts are right, and how often they recommend you against rivals. It is a reputation watch, not a rank check. Key takeaways AI brand monitoring tracks what AI says about you, which is different from tracking a keyword rank or a citation link.
AI Brand Sentiment for B2B SaaS
AI brand sentiment is how large language models characterize your brand when they answer a buyer: the adjectives, the caveats, and the audience they say you suit. For B2B SaaS it decides whether a mention helps or quietly kills the deal, because buyers act on the framing, not just the name. Key takeaways Sentiment is the framing, not the presence. Being named as the expensive, hard-to-set-up option is a loss even when you appear.
Agentic Marketing: How B2B SaaS Gets Chosen When AI Agents Do the Buying
Key takeaways Agentic marketing is marketing for a world where the buyer is often an AI agent acting for a human, not the human alone. Gartner projects that by 2028, 90% of B2B buying will be AI agent intermediated, moving over $15 trillion through agent exchanges. Semrush found 92% of B2B professionals say AI has already shaped their vendor shortlist, and only 7% notice a vendor because they recognise the brand name.
Agentic Search Explained: How AI Agents Find and Evaluate Software
Key takeaways Agentic search is when an AI agent runs a multi-step search for you: it plans, browses, uses tools, compares and returns a shortlist. It is different from a single AI answer. The agent acts across several sources instead of replying once. What an agent can parse on your site decides what it can repeat about you to a buyer. Clean text, explicit pricing and structured data get read. Facts buried in images, forms or heavy JavaScript get skipped.
Agentic AI vs Generative AI: What the Shift Means for B2B Marketers
Key takeaways Generative AI creates content in response to a prompt. Agentic AI plans, uses tools and acts across several steps to finish a goal. Salesforce frames it simply: generative AI is reactive, agentic AI is proactive. The shift matters for marketers because agents, not just people, now research and shortlist software. Gartner projects 90% of B2B buying will be AI agent intermediated by 2028, moving over $15 trillion through agent exchanges.
Agentic SEO: How to Get Your SaaS Found and Recommended by AI Agents
Key takeaways Agentic SEO has two meanings. One is using AI agents to automate SEO work. The other is optimising so AI agents discover and recommend you. This guide is about the second, because that is what decides whether a B2B SaaS brand gets picked when agents do the research. Agents reward use-case fit, machine-readable facts, third-party evidence and a consistent entity, not keyword density.
AI Agents and B2B Software Buying: How the Shortlist Gets Made Now
Key takeaways AI agents are moving into B2B software buying, from early research all the way to the shortlist and the final call. Gartner projects 90% of B2B buying will be AI agent intermediated by 2028, moving over $15 trillion through agent exchanges. Semrush found 92% of B2B professionals say AI has already shaped their vendor shortlist. Agents filter on fit and evidence. Generic positioning, hidden pricing and thin third-party proof get you cut early.
Google Preferred Sources in AI Overviews and AI Mode: What Changed (and What Didn't)
Key takeaways Google's Preferred Sources lets a user pick the sites they want to see more of. In May 2026 it came to AI Overviews and AI Mode, not just Top Stories. When someone adds you, your links can carry a “Preferred” label in their AI answers and you show up more for them. It is user-scoped. Google's own docs say the badge appears “for users who have selected your site,” so it does nothing for people who have not added you.
AI Agents for Marketing: A Practical Guide for B2B SaaS Teams
Key takeaways AI agents for marketing split into two jobs: using agents to do the work, and preparing your brand to be found by buyers' agents. On the doing side, agents are strong at research, audits, finding decaying content and spotting AI mention gaps. They are weaker at anything high-stakes or client-facing, and they still need a human in the loop. The job most teams miss is the second one: being discovered and recommended when a buyer's agent researches your category. Do both.
How Hola Prime Grew Organic Traffic 481% to 38k/mo in 11 Months
Key takeaways Organic MQLs grew 16x, from 416 to 6,892 a month (Jul 2025 to Jun 2026, GA4). Google Search clicks rose 481%, from 6,700 to 38,899 a month, as average position improved from 47.6 to 6.8 (Jul 2025 to Jun 2026, Google Search Console). Organic search drove 34,851 MQLs and 51,121 completed registrations between July 2025 and August 2026 (GA4). Ahrefs data: estimated organic traffic grew 114x, from 80 to 9,127 (Jul 2025 to Sep 2026). This is an Ahrefs model estimate, not measured visits.
LLM SEO Tools for B2B SaaS
Key takeaways LLM SEO tools help you get found and stay found inside AI answers. They fall into four jobs: monitoring, content optimisation, technical readiness, and competitive benchmarking. No single tool does all four well yet, so most B2B SaaS teams assemble a small stack rather than buying one platform. Monitoring tools (Profound, Peec AI, Otterly, Semrush, Ahrefs Brand Radar) tell you where AI cites you. Content tools help you earn those citations. Match spend to team size.
AI Rank Trackers for AI Search
Key takeaways An AI rank tracker measures whether AI answer engines mention your brand, but "rank" is the wrong word: there is no stable position to hold in a generated answer. SparkToro found roughly a 1-in-1,000 chance ChatGPT returns the same brand list in the same order twice, so a single rank number is noise. A useful tracker reports four things: appearance frequency, position within the answer, whether you were cited or just mentioned, and your share against named rivals. Start manual.
Measuring AI Search ROI
Key takeaways AI search ROI is real but hard to see, because AI referral traffic is small, high-intent, and badly under-counted in analytics. Roughly 70% of AI traffic lands in analytics as Direct, so most teams undercount the pipeline AI search actually drives. The upside is conversion. Multiple 2026 studies put AI referral conversion at 4 to 5 times organic search, and higher still for B2B SaaS.
How to Run a GEO Audit
Key takeaways A GEO audit checks whether AI engines can reach, understand, trust and cite your site. It runs across four layers: technical crawlability, content structure, citation footprint and measurement. Crawlability is the gate. If GPTBot or PerplexityBot cannot fetch a page, no amount of good content earns a citation. A GEO audit is not an SEO audit. SEO asks whether you can rank; a GEO audit asks whether an engine can extract, attribute and cite you.
AI Search Analytics for B2B SaaS
Key takeaways AI search analytics is the downstream half of AI visibility: once buyers arrive from an AI answer, you measure who they are and what they do. Most AI traffic is mislabelled. Around 70% lands as Direct in GA4, so it goes uncounted unless you set up detection. GA4 added an AI Assistant channel in 2026, but it misses sources like Perplexity, so you still need custom channel groups and regex.
How to Get Your SaaS Featured in AI's Best Software Lists
Key takeaways Third-party "best software" lists are the most-cited buyer surface in AI answers, and you cannot buy your way into a good one. Shortlist the lists first: target roundups that already rank, name your competitors, and have a gap your product fills. Pitch the person who can actually edit the article, and lead with reader value plus verifiable proof, not a link request. Unlinked mentions are the fastest win. Ask the author to add a link where you are already named. Keep placements fresh.
Digital PR for AI Search: Earning the Mentions LLMs Cite
Key takeaways News and editorial media are among the most-cited sources in AI answers, so digital PR is now a citation channel, not just a link channel. The same content earns far more AI visibility when a third-party outlet publishes it than when it sits on your own domain. Data-led stories, expert commentary and reactive comment are the PR plays LLMs quote most. Measure PR by share of citation, not coverage volume or domain rating.
How G2, Capterra and Review Sites Shape AI Recommendations
Key takeaways AI engines lean on review platforms to answer "best software". In one study, every tool ChatGPT named had Capterra reviews and 99% had G2 reviews. Being in the top 20 of your G2 or Capterra category is linked to being cited far more often in AI answers. Buyers trust these citations. 45% say a review-site citation is the most confidence-inspiring signal in an AI response.
How to Get Your B2B SaaS Recommended by AI
Key takeaways B2B buyers now build their shortlist inside AI assistants. 51% start software research with a chatbot more often than Google, up from 29% in early 2025. Recommendations beat rankings at the bottom of the funnel. 69% of buyers picked a different vendor than planned after an assistant weighed in, and 33% bought from a vendor they had never heard of.
AI Share of Voice: Measuring Buyer-Intent AI Visibility
Key takeaways AI share of voice is how often AI answers name your brand for a set of prompts, measured against competitors. Aggregate visibility scores flatter brands. A high overall number can hide the fact that you never appear for buyer prompts. Build a prompt set from the best, alternatives and vs questions your buyers actually ask, then score against those. Track by engine, not just blended, since a brand can look strong overall and be invisible in two of three engines.
Alternatives and Comparison Pages: The AI Search Playbook
Key takeaways "X alternatives" and "X vs Y" are the highest-intent prompts a B2B buyer types, and comparing vendors is the number one reason they open a chatbot. Both your own comparison pages and third-party roundups feed the AI answer, so you need to shape both. Honest, specific comparisons get cited. Pages that claim you win on everything get skipped. Structure matters: clear criteria, tables, and schema make a page easy for a model to lift.
Programmatic SEO in the AI Search Era: Does It Still Work?
Key takeaways Programmatic SEO is not dead in 2026, but the thin, low-value version is. Google's March 2026 enforcement of scaled content abuse stripped 50 to 80 percent of traffic from low-value programmatic sites. AI Overviews cut the top result's clicks by 58 percent when they appear, hitting definition-style pages hardest. Pages with real data or utility keep ranking, and the best of them earn AI citations, not just clicks.
How to Do Programmatic SEO: A Step-by-Step Guide for SaaS
Key takeaways Programmatic SEO runs in seven steps: find the pattern, build the data, design the template, generate, QA, internal-link, and prune. The pattern is a head term with a repeatable modifier, like "[x] for [y]", with enough real variations to justify the build. Your data set is the moat. First-party or verified data is what keeps pages off Google's scaled content radar. A no-code stack of Airtable, Webflow, and a sync tool can run a full programmatic set for a few hundred dollars a month.
Programmatic SEO Examples: 6 B2B SaaS Teardowns
Key takeaways The best programmatic SEO examples share one trait: every page is backed by data or a tool a summary cannot replace. Zapier built its traffic on "[app] integrations" pages, which drive about 16 percent of its organic traffic. Wise turned live exchange rates into currency pages that reportedly pull tens of millions of visits a month. Canva's roughly 21,000 template pages draw over 13 million organic visits a month on their own.
Programmatic SEO Tools: The B2B SaaS Stack for 2026
Key takeaways Programmatic SEO tools do four jobs: source data, generate pages, check quality, and monitor what indexes. Airtable is the data layer, a CMS like Webflow holds the template, and a sync tool such as Whalesync connects them. All-in-one tools like SEOmatic bundle the workflow, while a modular stack gives more control. QA is the step teams skip and the reason most sets fail, so budget a human review layer, not just software.
Keyword Research for Programmatic SEO: Finding the Dataset
Key takeaways Keyword research for programmatic SEO finds a repeatable pattern, not a list of individual keywords. The workhorse shape is a head term plus a modifier, like "[x] for [y]" or "[x] vs [y]". Your modifiers usually come from a data set you already own, such as integrations, industries, or competitors. Size the opportunity before you build, because most patterns have real demand for a few terms and little after.
Topic Clusters: The Architecture Behind Search and AI Visibility
Key takeaways A topic cluster is one pillar page plus a set of focused articles, all interlinked, that together resolve a topic completely. AI assistants split prompts into sub-queries, so a cluster gives you many chances to be retrieved where a single page gives you one. Plan clusters from aggregated themes, not individual long-tail queries, and lock one distinct primary keyword per node before writing.
Pillar Pages: What They Are and How to Build One That Gets Cited
Key takeaways A pillar page is the broad, comprehensive page that anchors a topic cluster and links down to every focused article in it. AI systems read pages in small chunks, so a pillar's sections must each stand alone: direct answers first, one idea per section, comparisons in tables. Aim for 2,500 to 3,500 words that resolve the topic, not a 6,000-word wall. Coverage decides the length, never the other way round.
Knowledge Graph Optimization: Getting Your Brand Into Google's (and AI's) Memory
Key takeaways The Knowledge Graph is Google's database of entities and their relationships, and it's a memory layer AI systems lean on when describing brands. Brands earn a place through an unambiguous entity home, aligned Organization schema, and corroboration from sources like Wikidata, Crunchbase and the press. Most B2B SaaS brands won't get a Wikipedia page, and the honest playbook doesn't need one: consistency plus trusted third-party records does the work.
Semantic SEO: Optimising for Meaning, Not Keywords
Key takeaways Semantic SEO optimises for meaning: covering intents, naming entities and structuring passages, instead of repeating keyword strings. Engines now compare content as embeddings at the passage level, so every section of a page is scored on how well it means what the query means. The practical shift: cover the questions inside a topic, define terms explicitly, use comparison tables, and stop writing synonym-stuffed filler. Site focus matters.
Entity SEO: Making Your Brand Unambiguous to Google and LLMs
Key takeaways Entity SEO is the work of making your brand, products and people unambiguous to the systems that map the web as things, not strings. Google and LLMs resolve who you are by cross-checking your site, your schema and your third-party profiles, and inconsistency caps everything else. Most B2B SaaS entity problems are self-inflicted: renames, repositioning and profile drift that leave five different descriptions of one company.
Structured Data and Schema for AI Answers
Key takeaways Schema markup does not directly buy you AI citations. A controlled Ahrefs test of 1,885 pages found no meaningful lift on ChatGPT, Google AI Mode or AI Overviews. The "cited pages have schema" stat is correlation. Sites that add structured data also do the technical SEO, content and links that actually earn the citation. When AI systems fetch a page in real time, they read visible HTML. Testing found ChatGPT, Claude, Perplexity, Gemini and Google AI Mode all ignored hidden JSON-LD.
AI Visibility for B2B SaaS
Key takeaways AI visibility is how often, and how favourably, AI answers name your brand on the questions your buyers ask. It's fast becoming the leading indicator of pipeline for B2B SaaS. The traffic looks small (AI referrals are around 1% of visits today) but it punches far above its weight, converting several times higher than organic and deciding who makes the shortlist. Track presence, recommendation rate, share of voice against competitors, citations and sentiment.
AEO vs GEO vs SEO: What's the Difference for B2B SaaS?
Key takeaways SEO gets a page ranked. AEO and GEO get your brand named inside an AI answer. That is the whole difference, and it changes what you build and what you measure. AEO and GEO are the same job with two labels. Andreessen Horowitz popularised "GEO" in May 2025; practitioners like Profound argue "AEO" is the clearer term. Pick one and move on. AEO is not just SEO renamed. What gets cited by an LLM diverges from what ranks on Google, so the tactics and the scoreboard are different.
How to Structure Content for Answer Engines
Key takeaways Answer engines often retrieve at the passage level, not the page level. They break your content into chunks, embed them, and pull the few that match a question. That means each section has to stand on its own. A 3,000-word article can be mined for ten different answers, but only if each section makes sense without the rest of the page. Google says you don't need to manually "chunk" content for its AI systems.
The B2B SaaS AEO Audit Checklist
Key takeaways Run AEO as a sequenced audit, not a tips list. The order is baseline, foundation, structure, off-site placement, then measure and repeat. Start by building a set of 20 to 50 buyer prompts and recording who gets named today. Without that baseline you can't tell if anything you do works. Fix the foundation first (crawlable, indexable, consistent facts), then restructure your buyer pages into answer-first sections a model can lift.
AI Visibility Tools: How B2B SaaS Brands Track Their Presence in AI Search
Key takeaways AI visibility tools run a fixed set of buyer prompts through ChatGPT, Gemini, Perplexity, Copilot and Google's AI answers, then report whether your brand shows up, how it's described, and who gets recommended instead of you. Track two different things: a citation links to you as a source, a mention names or recommends your brand inside the answer. For B2B SaaS, the mention usually matters more, because a recommendation on a buyer query does the selling with no click.
Query Fan-Out for B2B SaaS
Key takeaways Query fan-out is how AI search answers you: it splits one prompt into many hidden sub-queries, searches them in parallel, then blends the results into a single answer. Google says AI Mode issues "a multitude of queries simultaneously". Independent testing found an average of 10.7 sub-queries per prompt on Gemini 3, up 78% from Gemini 2.5. Ranking first for one keyword is no longer enough. Pages that rank across several fan-out queries are 161% more likely to be cited by AI.
How KEY ESG Went From Near Zero to #1 for ESG Reporting Software
Key takeaways Organic traffic grew from 65 monthly visits in January 2023 to a peak of 5,464 in February 2026, an 84x increase (Ahrefs Site Explorer). KEY ESG now ranks #1 in Google for its core category terms, including "esg reporting software" (1,300/mo), "esg software" and "esg compliance". Top-3 Google rankings grew from 0 in early 2023 to a peak of 310, with more than 500 page-one keywords (Ahrefs).
Reddit SEO for B2B SaaS: How to Rank in Google and Get Cited in AI Search
Key takeaways Reddit is now the single most-cited source inside Google AI Overviews and Perplexity, so "Reddit SEO" has quietly become an AI search strategy, not just a traffic tactic. There are two prizes on Reddit: ranking a thread in Google, and being named or linked inside an AI answer. For B2B SaaS, the second one usually matters more. Google pays Reddit about 60 million dollars a year for its data, and OpenAI has its own Reddit deal. That is why Reddit shows up everywhere buyers now research.
Nosto | MADX Digital
Key takeaways Nosto went from a near-zero presence in AI answers to a 51% share of voice in ChatGPT, third in its category behind Bloomreach and Algolia. Keywords ranking in Google positions 1 to 3 grew from 54 to 199 in twelve months, up 268%. More than a dozen earned buyer-guide placements, a full technical SEO rebuild, and over ten new content guides did the work. Honest comparative buyer guides now hold position 1 for terms like best ecommerce search and site search best practices.
How to Get Mentioned in ChatGPT
Key takeaways Getting mentioned in ChatGPT is mostly an off-page job. Across the B2B SaaS accounts we run, the pages that shape an AI answer usually sit on other people's domains, not yours. A citation is a link back to you as a source. A mention is the AI naming or recommending your brand in the answer. For B2B SaaS, the mention on a buyer query is the one that sells.
llms.txt Explained: What It Is and Whether B2B SaaS Should Bother
Key takeaways llms.txt is a markdown file at your site root that hands an LLM a curated map of your best content. It controls nothing and blocks nothing. No major AI search platform reads it. Google has said outright that it doesn't use llms.txt, and server logs back that up. Ahrefs checked 137,000 sites in June 2026 and found 97% of published llms.txt files got zero requests in a month. AI retrieval bots were 1.1% of the traffic they did get. The one real audience is AI coding agents.
AI Crawlers: How ChatGPT, Claude and Perplexity Read Your Site
Key takeaways AI crawlers split into three jobs: training, search indexing, and real-time user fetches. Only two of them decide whether you show up in an answer. Blocking training crawlers costs you very little. Blocking search crawlers like OAI-SearchBot or Claude-SearchBot removes you from the answer entirely. None of the major AI crawlers execute JavaScript, so anything rendered client-side is invisible to them.
GEO vs SEO: What B2B SaaS Should Actually Invest In (2026)
GEO (generative engine optimization) and SEO are not rival strategies. SEO earns rankings and clicks in traditional search. GEO earns mentions and citations inside AI answers from ChatGPT, Perplexity, and Google AI Overviews. For B2B SaaS in 2026 you need both, because buyers now research across both surfaces before they ever fill in a form. Key takeaways SEO optimizes for rankings and clicks in traditional search. GEO optimizes for being named and cited inside AI answers.
Google AI Mode SEO: How B2B SaaS Brands Get Cited
Key takeaways Google AI Mode is the Gemini-powered, conversational version of Search. It passed 1 billion monthly users at Google I/O 2026, and query volume is more than doubling every quarter. AI Mode runs on query fan-out. It splits one question into many sub-queries, then builds an answer from the pages that best match each sub-query, or facet. Ranking for one keyword is no longer the game. You get cited by covering every facet of a buyer topic with clear, self-contained answers.
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