When was the last time you asked ChatGPT something instead of Googling it?
If you’re like most people in the software industry right now, it’s happening more and more. Maybe you asked it to compare two integration platforms. Maybe you wanted a quick breakdown of pricing models for a specific tool category. Maybe you just didn’t feel like wading through ten tabs to find a straight answer.
And that shift is very quickly reshaping how your prospects find (or don’t find) your software.
The game has changed, and many ISVs are still figuring out how to adapt
Google gives you 10 chances, more or less. AI gives you one.
The old way looked like this:
A potential buyer searches “best ERP solution for manufacturers.” Google serves up ten blue links. They click through three or four websites, compare features, read some reviews, maybe download a whitepaper, book a demo and eventually make a decision.
You had multiple opportunities to show up. Multiple chances to earn attention.
Now here’s the new way:
That same buyer asks ChatGPT or some other AI tool: “What’s the best ERP for a mid-market manufacturing company with complex inventory needs?”
The AI doesn’t give them ten options. It gives them one consolidated answer of the top solutions it could find. And if your solution isn’t in that answer, you don’t exist.
Not “you’re ranking lower.” Not “you need better keywords.” The buyer may never encounter your brand during that search.
This shift isn’t theoretical. Adoption is already happening.
Several recent studies point to how quickly AI is entering the research phase of the buying journey:
- ChatGPT hit 100 million users faster than any platform in history. Faster than TikTok. Faster than Instagram.
The implication for software vendors is simple: buyers are increasingly using AI tools to explore solutions, compare vendors, and narrow down their options before visiting a website. The question is whether AI is recommending you, or your competitor.
GEO: Generative Engine Optimization
You’ve probably spent years (and serious budget) on SEO. Keywords, backlinks, site structure, meta descriptions, the whole nine yards. The reassuring part is that SEO isn’t dead.
But there’s a new layer now, and it’s called GEO: Generative Engine Optimization.
Think of this as “teaching AI how to describe you.”
Here’s the difference:
SEO optimizes your content so Google’s algorithm ranks your website higher in search results.
GEO optimizes your content so AI systems cite you in their answers.
See the distinction? With SEO, you’re trying to win a spot on a list. With GEO, you’re trying to be the answer.
The tricky part is that while great SEO optimization forms a solid GEO basis, it doesn’t just look at your website.
Large Language Models (LLM) pull from how you’re mentioned across the entire web, in articles, forums, reviews, business publications, and even casual mentions in industry discussions. They’re building an understanding of your brand from everywhere, not just your homepage or backlinks.
What AI actually looks for
If you want AI to recommend your software, you need to understand what these systems are evaluating. It’s not just keywords anymore.
1. Authority signals
AI wants to know: Are you positioned as the expert in your space?
This means getting mentioned in high-authority public content like trade journals, industry resources, and media articles. It means having content that other sources reference. It means showing up in conversations that matter, like relevant review sites, not just on your own blog.
AI answers are consensus-driven, not keyword-driven. If many trusted places repeatedly say the same thing about you, AI believes it.
For software vendors, this is about owning your niche. Are you the solution for a specific use case or vertical? Or are you just another option in a crowded category?
Keep key content updated
AI systems favor information that appears current and well-maintained.
Updating high-value pages every 6–12 months with new data, examples, or industry developments helps maintain visibility.
Simple signals like a visible “Last updated” date can also reinforce credibility.
2. Structured content
Can AI easily understand:
Who you are?
What you do?
Who you serve?
What problems you solve?
This is where a lot of ISVs fall short. Your website might look great to humans, but if it’s not structured in a way that AI can parse, with clear schema markup, logical content hierarchy, and explicit service/pricing information, you’re making it hard for AI to recommend you.
You’ll have to be crystal-clear about your entity, which means you must consistently answer:
“[Brand] is a [what] that helps [who] solve [problem] using [approach].”
Repeat this verbatim everywhere online. Don’t constantly rebrand your value proposition with marketing language. Reuse the same clear language across websites, blogs, social media profiles, product docs, among others.
Think of it this way: AI needs to be able to confidently say “This company does X for Y type of customers.” If your messaging is vague or scattered, AI won’t take the risk of recommending you.
Start sections with a clear answer (“Answer Block” format)
AI systems often extract short passages that directly answer a question.
Instead of burying the key takeaway deep in a paragraph, begin sections with a concise explanation (around 30–80 words) that directly addresses the topic.
Think of it as the “executive summary” for both readers and AI systems. After the short answer, the rest of the section can provide deeper context, examples, and supporting detail.
Use clear heading hierarchies
AI systems use headings as signals to understand how information is organized.
A predictable hierarchy (H1 → H2 → H3) helps models interpret how ideas relate.
For example:
H1: How to Choose a CPQ Platform
H2: Key Evaluation Criteria
H3: Integration Capabilities
H3: Pricing Flexibility
Vague headings like “Overview” or “Best Practices” provide little context for either readers or AI systems.
Strengthen topic clusters with internal links
Internal linking helps AI systems understand how topics relate across your site.
Strong internal linking structures:
- Connect related pages within the same topic cluster
- Link supporting articles back to a main “pillar” page
- Use descriptive anchor text instead of generic phrases like “learn more”
This creates a clearer knowledge structure that AI systems can interpret.
Use formats that are easy to extract
AI systems frequently pull structured content into responses.
Lists, numbered steps, and comparison tables are easier to interpret than long paragraphs.
For example:
- evaluation checklists
- feature comparisons
- step-by-step guides
Schema recommendations
Useful schema types for software vendors include:
- Organization schema – defines your company entity
- Product schema – describes your software offering
- FAQ schema – helps AI extract direct answers
- Pricing schema – clarifies pricing tiers or ranges
- Article schema – adds author, date, and topic metadata
3. Semantic relationships
Does your content answer the questions buyers actually ask?
This as important in GEO as it is in SEO. AI doesn’t just match keywords, it tries to understand intent and context. If a prospect asks “What’s the best way to manage partner commissions for a SaaS product?”, AI is looking for content that directly addresses that scenario.
Generic feature pages won’t cut it. You need content that mirrors real buyer questions:
- Comparison frameworks
- Evaluation checklists
- Use-case breakdowns
- “How to choose” guides
- Direct Q&A
- Explainer pages
- FAQ sections
AI prefers clear answers over long marketing prose. Optimize for questions people ask AI. If you can answer a question in 3–6 sentences clearly, AI can reuse it.
Write sections that stand on their own (“write for snippets” concept)
AI systems frequently extract small portions of a page rather than the entire article. That means each section should make sense independently.
If a paragraph were quoted on its own in an AI answer, would the reader still understand it?
Define key concepts clearly
Explicit definitions make it easier for AI systems to understand and reuse your content.
For example:
“Partner revenue management software helps SaaS companies track commissions, partner performance, and channel attribution.”
The compounding advantage (and why waiting is expensive)
AI systems typically pull information from multiple sources across the web (articles, documentation, forums, reviews, and knowledge graphs). Brands that appear consistently across these sources are more likely to be included when AI tools synthesize answers.
In other words, the more clearly and consistently your company is referenced across the web, the easier it becomes for AI systems to understand who you are and what problem you solve.
It means that companies with stronger digital footprints are more likely to appear in the pool of sources AI systems draw from.
Over time, that visibility can compound as more content, citations, and references reinforce the same positioning.
GEO and SEO: partners, not competitors
Let’s be clear: this isn’t about abandoning your SEO strategy. SEO builds your authority and credibility across the web, which is exactly what AI uses to decide who to recommend.
Think of it like this:
- SEO builds the foundation. It gets you indexed, establishes your domain authority, and creates the content ecosystem AI draws from.
- GEO is the amplifier. It ensures that when AI synthesizes information, your brand is the one that surfaces.
Without SEO, you have nothing for AI to find. Without GEO, AI might find you but never recommend you.
Our recommendation? Run them in parallel. Audit your existing content for GEO readiness while continuing to build authority through traditional channels.
Try this right now
Before you close this tab, I want you to do something.
Go to ChatGPT (or Perplexity, or Google’s AI Overview) and ask:
“What’s the best [your software category] for [your target customer type]?”
For example:
- “What’s the best channel management platform for software vendors?”
- “What’s the best CPQ solution for B2B SaaS companies?”
- “What’s the best integration platform for ISVs with complex partner ecosystems?”
See if you come up.
If you do? Great, you’re ahead of most. Now figure out how to stay there.
If you don’t? That’s your wake-up call. Because your prospects are asking that exact question right now. And if AI isn’t recommending you, someone else is getting that business.
The shift from blue links to AI answers isn’t a trend to watch. It’s a transformation that’s already reshaping how software buyers discover solutions.
The ISVs who adapt now will own the AI recommendations in their niche. The ones who wait will wonder why their pipeline dried up.
