How to Improve Your GEO: Get AI to Recommend Your SaaS

What Is GEO and Why Should You Care?

Generative Engine Optimization (GEO) is the practice of positioning your product so that AI tools — ChatGPT, Claude, Perplexity, Gemini — recommend it when users ask for solutions in your category. Where traditional SEO targets Google's crawlers, GEO targets the training data and retrieval signals that shape what large language models say.

The shift is already happening. A growing percentage of software-buying decisions now start with a prompt, not a search query. Someone types "what's the best tool for X?" into an AI assistant and acts on whatever comes back. If your SaaS isn't in that answer, you're invisible to an entire acquisition channel — one that's growing faster than any other.

The good news: GEO is still early enough that systematic effort pays off. Here's how to build it, step by step.

Step 1: Identify Where Your ICP Actually Asks Questions

Before you can influence AI recommendations, you need to understand where your ideal customer profile (ICP) goes when they have a problem your product solves. The most important channels are:

• Reddit — subreddits organized around pain points, tools, and industries
• Quora — long-form Q&A that gets scraped heavily by AI training pipelines
• Hacker News — technical founders and early adopters asking nuanced product questions
• Niche forums and communities — Slack groups, Discord servers, product-specific communities
• Twitter/X threads — real-time discussion that surfaces in AI retrieval augmentation

Map out 10 to 20 specific questions your ICP asks before they find a solution like yours. These questions are your GEO keywords — the phrases that, when someone types them into an AI assistant, should surface your product.

Step 2: Why Reddit Dominates LLM Training Data

Reddit deserves its own section because it's categorically different from other channels in how heavily it influences AI outputs.

When researchers and companies build large language models, they need massive datasets of human text. Reddit has been one of the richest sources available. The Pushshift dataset — a historical archive of Reddit posts and comments — was used extensively in early LLM training. Common Crawl, another major training corpus, has crawled Reddit billions of times. When OpenAI, Google, and Anthropic trained their foundation models on the open web, Reddit conversations were a disproportionately large slice of that data.

The practical consequence: when someone asks ChatGPT "what's the best project management tool for a 5-person startup?", the answer reflects the aggregate sentiment of thousands of Reddit threads discussing that exact question. Products mentioned repeatedly in helpful, upvoted Reddit comments are more likely to surface in AI answers. Products that never appear in authentic Reddit conversations are invisible.

This isn't a loophole — it's a signal. Reddit threads represent genuine human opinion at scale. When your product genuinely helps people, Reddit is where that help gets documented.

Step 3: Find Relevant Conversations and Participate Authentically

The operative word is authentically. Reddit communities have sophisticated spam detection — both algorithmic and human. Moderators ban promotional accounts within minutes. The only approach that works long-term is genuine participation: answering questions helpfully, sharing real experience, and mentioning your product only when it's genuinely the right fit for what someone is asking.

Practically, this means:

• Search subreddits for posts asking about your problem space, not just your product
• Build account history in the community before posting anything promotional
• Lead with the answer, not the plug — mention your product at the end if relevant
• Disclose your affiliation when recommending your own product
• Engage with threads even when your product isn't the answer

This is exactly the problem Reddily was built to solve. It scans Reddit for threads where your SaaS would genuinely help, so you can participate in conversations rather than interrupt them. Instead of manually browsing subreddits for hours, you get a curated list of the most relevant posts where adding your product recommendation makes sense. That changes Reddit from a time-consuming guessing game into a focused, high-signal channel.

Step 4: Create Content That Gets Cited by AI

Not all Reddit comments are equal from a GEO perspective. The posts and comments that LLMs are most likely to reference share a few characteristics:

• Specificity — vague answers don't get cited; concrete comparisons and detailed explanations do
• High upvote counts — community validation is a proxy for quality that influences training data weighting
• Length and structure — well-organized, thorough answers are preferred over brief ones
• Named comparisons — "compared to Tool X, we found Tool Y does Z better" is the kind of structured claim LLMs extract
• Real use cases — "we used this at our company for [specific scenario]" carries more weight than generic praise

Apply this framework beyond Reddit too. Detailed Quora answers, thorough GitHub issue discussions, and in-depth Hacker News comments all contribute to the broader web corpus that shapes AI responses.

Step 5: Track Which AI Tools Are Recommending Your Product

GEO without measurement is guesswork. You need a systematic way to know whether your efforts are moving the needle. Start with manual spot checks — query ChatGPT, Claude, and Perplexity with your target phrases and record what they recommend. Do this weekly and track changes over time.

More advanced approaches include:

• Setting up a spreadsheet with 20 to 30 target queries and running them monthly across multiple AI tools
• Monitoring brand mentions in AI-generated content using search operators
• Watching for traffic spikes that correlate with no corresponding SEO or paid activity — this often indicates AI referrals
• Asking customers "how did you hear about us?" — "AI recommended it" is becoming a real answer

GEO is a compounding strategy. Reddit threads you participate in today may influence AI training data for years. The founders who invest in it now — when the channel is undervalued — will have a meaningful head start by the time it becomes mainstream.

Putting It Together: A GEO Action Plan

Start small and build consistently. Week one: identify your 10 most important "what tool should I use for X?" queries. Week two: find the Reddit threads where those questions are being asked right now. Week three: write one genuinely helpful response per day, mentioning your product where appropriate. Week four: measure — check your target queries in AI tools and look for any movement.

GEO rewards persistence over perfection. A single brilliant comment can generate AI recommendations for years. A pattern of helpful participation across dozens of threads builds an authoritative signal that LLMs learn from. The question isn't whether to invest in GEO — it's how quickly you can build the habit.