Keyword research for an AI tools company requires understanding three distinct intent categories: informational (how does X work), commercial investigation (best X tool), and navigational (X tool login). Each category requires a different content approach and has different conversion potential. Informational keywords drive traffic and build authority but convert slowly. Commercial investigation keywords are where your direct buyers are researching. Navigational keywords indicate existing brand awareness. The most common mistake AI companies make in keyword research is pursuing high-volume informational keywords while ignoring the lower-volume commercial investigation keywords where actual purchase decisions are made.
I have been doing keyword research for Pristren's blog for two years. Here is the framework and the tools.
Understanding Search Intent for AI Tools
Before choosing keywords, you need to understand what the person searching is trying to accomplish.
Informational intent: The searcher wants to understand something. "How do large language models work," "what is RAG," "how does vector search work." These searchers are learning, not buying. Content targeting informational keywords builds topical authority and brand recognition but converts to paid signups at low rates (0.5-2%).
Commercial investigation intent: The searcher is evaluating options before making a decision. "Best LLM for coding tasks," "ChatGPT vs Claude comparison," "OpenAI API pricing." These searchers are much closer to a purchase decision. Content targeting commercial investigation keywords converts at 3-8% in my experience.
Navigational intent: The searcher already knows where they want to go. "Zlyqor login," "OpenAI API dashboard," "Hugging Face models." These keywords indicate existing brand awareness. You mostly want to own your own brand keywords and not build content strategy around someone else's navigational terms.
Transactional intent: The searcher is ready to act. "Sign up for Perplexity Pro," "buy Claude API credits." Lower search volume but highest conversion rate.
For an AI tools company, the highest-ROI keyword strategy focuses on commercial investigation intent.
The Tools
Ahrefs ($99-$399/month). The most comprehensive SEO tool available. Keyword Explorer shows search volume, keyword difficulty, clicks, and SERP analysis. Site Explorer shows what keywords competitors rank for, which is often the most efficient way to find keyword opportunities. The $99/month plan is sufficient for most early-stage companies.
Semrush ($119-$449/month). Broadly comparable to Ahrefs. Semrush has slightly better data for US keywords, Ahrefs is generally considered better for international. For AI tools with a global developer audience, either works.
Google Search Console (free). If you have any existing content ranking, Search Console shows exactly which queries are generating impressions and clicks. For finding content refresh opportunities and discovering low-hanging keyword wins, Search Console is often more valuable than paid tools.
Google Keyword Planner (free, requires Google Ads account). Primarily a PPC tool but useful for finding search volume ranges. The volume data is less granular than Ahrefs or Semrush but the tool is free.
AnswerThePublic / AlsoAsked ($9-$49/month). Specialized tools for finding question-format keywords ("how to," "what is," "why does"). Useful for finding informational content topics.
For a bootstrapped company, the workflow that works: free tier of Google Keyword Planner for volume estimates, Google Search Console for existing traffic analysis, and one month of Ahrefs or Semrush when you need deep competitor analysis.
Finding High-Value, Low-Competition Keywords in AI Tools
The AI tools category is extremely competitive for broad terms. "Best AI tool" and "ChatGPT alternative" are dominated by major publications with thousands of backlinks. The opportunity for a smaller site is in the long tail.
Long-tail keyword patterns that work:
"[AI tool] vs [AI tool]" comparisons. "Llama 3 vs Mistral for code generation," "Claude Haiku vs GPT-4o Mini cost comparison." These rank because specific comparisons have lower competition than generic "best AI" terms, and searchers using them are in high-intent evaluation mode.
"How to [specific task] with [AI tool]." "How to fine-tune Llama 3 on a single GPU," "how to run Mistral 7B locally with Ollama." These are tutorial keywords with clear informational intent. They rank faster than commercial keywords because the content is more specific and competition is lower.
"[AI tool] for [specific use case]." "Best LLM for SQL generation," "open source LLM for customer support automation." Use-case specific keywords have high commercial intent and lower competition than generic tool comparisons.
"[AI tool] pricing" and "[AI tool] cost." High commercial intent. Developers search these before making API provider decisions. If you have a pricing comparison post, these are among the highest-converting keywords you can target.
Real Examples from the Prompt Engineering Space
Prompt engineering has gone from a niche topic to a saturated content category in 18 months. Here is what the keyword landscape actually looks like:
Saturated (hard to rank):
- "prompt engineering" — 40,500 searches/month, KD 78, dominated by OpenAI docs and major publishers
- "ChatGPT prompts" — 110,000 searches/month, KD 82
- "best AI prompts" — 27,100 searches/month, KD 71
Competitive but winnable:
- "prompt engineering for code generation" — 1,200 searches/month, KD 42
- "how to write system prompts for Claude" — 880 searches/month, KD 35
- "few-shot prompting examples" — 2,400 searches/month, KD 38
Low competition, solid intent:
- "prompt chaining tutorial" — 390 searches/month, KD 22
- "Claude prompt for data extraction" — 320 searches/month, KD 18
- "llm prompt template json output" — 260 searches/month, KD 15
The low competition examples have volumes that sound small but compound: 260 searches/month at 30% CTR is 78 visitors/month. 50 such posts is 3,900 qualified visitors/month from long-tail keywords alone.
The Competitor Keyword Gap Analysis
The fastest way to find keyword opportunities for an AI tools company is to analyze what your competitors rank for and you do not.
Process in Ahrefs:
- Enter your domain in Site Explorer
- Go to Content Gap
- Add 3-4 competitor domains
- Filter for keywords where competitors rank in positions 1-10 and you do not rank at all
- Sort by traffic volume, filter by keyword difficulty below your target threshold
This surfaces keywords that have proven search demand (competitors are ranking for them), are relevant to your content area (same competitors), and where you have an opportunity (you do not rank yet).
For a new site targeting the AI tools space, a keyword difficulty threshold of 20-30 is realistic to rank for within 6-12 months with good content. Sites with DA 50+ can target KD 40-60.
Building a Keyword Master List
The output of keyword research should be a prioritized master list, not a sprawling spreadsheet.
Columns that matter: keyword, search volume, keyword difficulty, intent category, current ranking (if any), priority (high/medium/low), assigned to (topic cluster).
Priority scoring: volume x intent value / difficulty. Commercial investigation keywords get a 2x intent multiplier. Informational keywords get 1x.
Review and update the master list monthly. Keyword opportunities shift as the AI tools landscape evolves. In 2024, "GPT-4 API" was high difficulty. In 2026, with five comparable models, "GPT-4o vs Claude 3.5 for [specific task]" is much more achievable.
Keep Reading
- A Content Strategy for a Technical Blog That Drives Signups — How to turn keyword research into a content calendar
- Link Building Strategies That Still Work — The other half of SEO: building the authority to rank
- Why Refreshing Old Content Beats Writing New Content — When the best SEO move is not to write something new
Pristren builds AI-powered software for teams. Zlyqor is our all-in-one workspace — chat, projects, time tracking, AI meeting summaries, and invoicing — in one tool. Try it free.
