GEO for SaaS & Tech Companies: Appear in ChatGPT

Example query: "best CRM for a 20-person SMB". Assistants usually answer with a short list of options and a reason for each.

If your product isn't on that list, the buyer may start their evaluation without it.

Software buyers often research online before talking to sales, and some now use assistants for part of that work: ChatGPT to build a first list, Perplexity to compare features, Gemini to check a decision. How common this is among your buyers is worth finding out, for example by asking new leads how they found you.

If your product is missing or described wrongly in those answers, you may be losing buyers early in their research without knowing it.

Why SaaS Should Pay Attention to AI Answers

Surveys suggest a growing share of B2B buyers use AI assistants in software research, although figures vary by survey, sample and definition. Check your own pipeline rather than rely on a single number.

The classic journey was: Google search → G2 or Capterra → demo → decision. For some buyers there is now an extra first step: ask an assistant → shortlist of 3-4 options → Google search to validate → G2 → demo. A product missing from that first list has to be discovered some other way.

Software is a category that models often know a lot about, because there is plenty of public writing on tools, use cases, integrations and comparisons. The question is whether they know enough about yours, and whether what they know is accurate and current.

Three types of software queries where AI answers can have real influence:

Category queries: "what's the best marketing automation tool for ecommerce?" The assistant builds a list. Without enough public information connecting your product to that category, you're unlikely to be on it.

Comparison queries: "compare HubSpot vs ActiveCampaign vs [your tool]." If there is little information about you, the answer may skip you or describe you incompletely.

Alternative queries: "alternatives to Salesforce for startups." These are especially valuable: the user is already qualified and looking to switch. Missing from these answers means missing a direct acquisition opportunity.

What Influences Which Software Gets Recommended

Providers don't publish how their models choose products to recommend, and it differs between answers from training data and answers that search the web. These sources are consistently relevant:

Presence on Software Directories

G2, Capterra, Product Hunt, GetApp and Software Advice host large volumes of public reviews and category pages. That content may be part of what models learned during training, and assistants that search the web can retrieve it directly. More recent, detailed reviews give answers more to draw on, but there is no published threshold for how many you need.

Comparative and Category Content

Comparison articles, "best tools for X" posts and content that places your product in a category are natural sources for these questions. If many independent articles mention your tool as an alternative to the market leaders, answers have more material to support mentioning you. If only your own website talks about you, there's much less.

Technical Documentation and Clear Use Cases

Assistants that search the web, such as Perplexity, can use documentation, knowledge bases and use-case pages. A well-structured page explaining which companies and problems your tool is designed for is more useful than a homepage full of marketing copy.

Mentions in Tech Media and Specialized Blogs

TechCrunch, Product Hunt, technology newsletters, marketing blogs — coverage like this adds independent descriptions of your product. How long it affects answers depends on whether a model learned it in training or finds it through search, so treat any single mention as one signal among many.

5 Steps to Improve Your SaaS AI Visibility

1. Optimize Your Presence on G2, Capterra and Product Hunt

Complete your profiles with a detailed use-case description, current screenshots and, above all, recent genuine reviews. Recent reviews reflect the current product, which matters to buyers and to answers that search the web. Never incentivize reviews in ways that break platform rules.

2. Create Category and Comparison Content on Your Own Blog

"Top X tools for [category]" posts where you mention your product alongside competitors — with honesty about when each is the best choice — answer the questions buyers ask assistants. Readers and search systems can see a page that only promotes you for what it is; balanced comparisons are more credible.

Examples for different SaaS types:

• CRM: "The 5 best CRM tools for marketing agencies"
• Marketing automation: "HubSpot vs ActiveCampaign vs [your tool]: which to choose based on your size"
• Project management: "Asana alternatives for remote teams"
• Invoicing: "Best invoicing software for freelancers and small agencies"

3. Build a Use Case Page per Segment

Not a generic "customers" page. Specific pages for each segment you target: "for marketing agencies," "for ecommerce," "for B2B startups." Each page should explain the specific problem your tool solves for that profile, with real data and customer quotes. Specific pages like these are good candidates for citation when someone asks a niche question.

4. Get Mentioned in External Comparisons

Third-party posts comparing you to category leaders are valuable because they're independent. An honest review on a marketing blog saying your tool is a good lower-cost alternative to HubSpot for a certain type of team gives answers a credible source to draw on. Earn those mentions with a good product and outreach; don't pay for undisclosed placements.

5. Implement SoftwareApplication Schema

SoftwareApplication schema can describe your application category, supported platforms, price and features in a structured way. Combined with Organization and, where you have a visible FAQ, FAQPage, it makes key facts easier to read. Keep it consistent with the visible page; schema describes content but doesn't guarantee inclusion in any answer.

A Common SaaS Mistake: Talking Only About Features

A lot of SaaS marketing content is about features: "200 integrations," "intuitive interface," "24/7 support." That rarely answers the questions buyers ask assistants.

Assistants answer specific questions. "What's the best project management tool for a 15-person agency working remotely?" calls for information about use cases, who the tool is ideal for and in which situations it beats the alternatives. Generic features don't help much.

The shift: from feature-centric content to content about problems and customer profiles. Every page, blog post and directory listing should help answer: "for what type of company and what specific problem is this tool a good option?"

How to Know If AI Recommends Your SaaS Today

Manual test: in ChatGPT, Perplexity and Gemini, run the queries an ideal customer would use — "best [category] for [segment]", "alternatives to [main competitor]", "[category] comparison for [customer type]" — three times each, and record whether and where you appear.

The problem with manual testing is that it's hard to repeat consistently and compare over time. Answers also vary between runs, so one test can be misleading.

Mentio analyzes your tool with prompts tailored to your category and segment. The report shows your visibility by model, your average position and your gaps against competitors. Model coverage depends on the plan: Free includes ChatGPT; Personal lets you choose one of the five models (ChatGPT, Claude, Gemini, Grok or Perplexity), Pro two of the five, and Enterprise all five.

Track whether appearing on those shortlists relates to demos and signups over time, rather than assuming it does.

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