---
name: keyword-research-saas
slug: keyword-research-saas
description: This skill should be used when the user asks to "do keyword research", "find keywords for SaaS", "keyword research for B2B", "find search terms to target", "build a keyword list", "keyword research strategy", "find SEO keywords", "research what people search for", or any variation of conducting, planning, or executing keyword research for B2B SaaS SEO and content strategy.
category: general
---

# Keyword Research for SaaS

Keyword research for B2B SaaS is fundamentally different from e-commerce or publisher keyword research. SaaS buyers don't search for products to buy — they search for problems to solve, categories to evaluate, and tools to compare. Your keyword strategy must map to the B2B buying journey, not just search volume.

The output of keyword research is not a list of keywords. It's a prioritized content plan that maps buyer intent to page types.

## The SaaS Keyword Framework

### The four intent layers

Every keyword falls into one of four intent layers. Each layer maps to a funnel stage and a page type.

| Intent layer | Buyer stage | Example queries | Page type | Conversion potential |
|-------------|-------------|----------------|-----------|---------------------|
| Problem-aware | "I have a problem" | "why is my pipeline forecast wrong", "crm data quality issues" | Educational blog post | Low (TOFU) |
| Solution-aware | "Solutions exist" | "best pipeline forecasting tools", "how to improve sales forecasting" | Listicle, how-to guide | Medium (MOFU) |
| Product-aware | "I'm evaluating specific tools" | "hubspot vs salesforce", "gong alternatives" | Comparison page, alternatives page | High (MOFU/BOFU) |
| Purchase-ready | "I'm ready to buy" | "hubspot pricing 2026", "gong demo" | Pricing page, demo page | Very high (BOFU) |

**Most SaaS companies over-index on problem-aware keywords (blog content) and under-index on product-aware keywords (comparison pages).** Product-aware keywords have 5-10x higher conversion rates.

---

## Keyword Research Process

### Step 1: Seed keyword generation

Start with seeds from four sources:

| Source | What it gives you | Process |
|--------|------------------|---------|
| Your product | Core features, use cases, integrations | List every feature, use case, and integration as a keyword seed |
| Your competitors | Their brand names, product names | List every direct competitor name for vs/alternatives pages |
| Your buyers | Problems they describe in their own words | Mine sales calls, support tickets, G2 reviews for language |
| AI search queries | How buyers ask AI about your category | Test 30+ queries in ChatGPT/Perplexity, note phrasing |

**Target: 50-100 seed keywords across all four sources.**

### Step 2: Keyword expansion

Expand each seed into a cluster of related queries.

**Expansion tools and methods:**

| Tool/method | What it generates | Best for |
|------------|------------------|---------|
| Ahrefs Keywords Explorer | Related terms, questions, volume data | Primary research tool |
| Google Search Console | Queries you already rank for (opportunity keywords) | Finding quick wins |
| Google "People Also Ask" | Question-format queries | FAQ and AEO optimization |
| Google autocomplete | Long-tail variations | Discovering natural language patterns |
| Ahrefs Content Gap | Keywords competitors rank for that you don't | Competitive gap analysis |
| ChatGPT/Perplexity testing | How AI engines phrase related queries | AEO keyword discovery |
| Reddit/community search | How real people phrase questions | Natural language keywords |

### Step 3: Keyword qualification

Not every keyword is worth targeting. Score each keyword cluster:

| Factor | 1 point | 2 points | 3 points |
|--------|---------|----------|----------|
| Search volume | < 100/month | 100-1,000/month | 1,000+/month |
| Business relevance | Tangential to your product | Related to your category | Directly about your product/category |
| Intent alignment | Problem-aware only | Solution-aware | Product-aware or purchase-ready |
| Ranking difficulty | DR 70+ competitors dominate | Mix of high and medium authority | Beatable competitors (DR < 50 or thin content) |
| AEO opportunity | AI engines answer well | AI engines answer partially | Weak AI answers (opportunity to be cited) |
| Content feasibility | Need extensive external research | Can write from internal knowledge | Have proprietary data or unique POV |

**Score 14-18:** Priority 1 — target immediately. **9-13:** Priority 2 — target this quarter. **Below 9:** Deprioritize.

### Step 4: Keyword clustering

Group qualified keywords into clusters. Each cluster becomes one page.

**Clustering rules:**
- Keywords with the same intent and same best page type → same cluster
- One primary keyword per cluster (highest volume + most precise intent)
- 3-10 secondary keywords per cluster (variations, long-tail, questions)
- Never create two pages for keywords in the same cluster (causes cannibalization)

**Example cluster:**

| Role | Keyword | Volume |
|------|---------|--------|
| Primary | "hubspot vs salesforce" | 8,100/month |
| Secondary | "hubspot vs salesforce crm" | 1,200/month |
| Secondary | "difference between hubspot and salesforce" | 900/month |
| Secondary | "hubspot or salesforce for small business" | 500/month |
| Secondary | "is hubspot better than salesforce" | 400/month |
| FAQ | "which is cheaper hubspot or salesforce" | 300/month |

→ One comparison page targets all of these.

### Step 5: Map clusters to content plan

| Cluster | Primary keyword | Volume | Intent | Page type | Priority |
|---------|----------------|--------|--------|-----------|----------|
| HubSpot vs Salesforce | hubspot vs salesforce | 8,100 | Product-aware | Comparison page | P1 |
| Best CRM for startups | best crm for startups | 2,400 | Solution-aware | Listicle | P1 |
| What is CRM | what is crm | 12,000 | Problem-aware | Definition page | P2 |
| CRM pricing comparison | crm pricing comparison | 1,100 | Purchase-ready | Pricing comparison | P1 |

---

## SaaS-Specific Keyword Types

### Comparison keywords (highest ROI)

| Pattern | Example | Volume range | Conversion |
|---------|---------|-------------|-----------|
| [Brand A] vs [Brand B] | "hubspot vs salesforce" | 500-10,000 | Very high |
| [Brand] alternatives | "salesforce alternatives" | 500-5,000 | Very high |
| [Brand] competitors | "hubspot competitors" | 200-2,000 | High |
| best [category] tools | "best crm for saas" | 500-5,000 | High |
| [category] comparison | "crm comparison 2026" | 200-2,000 | High |

### Feature keywords

| Pattern | Example |
|---------|---------|
| [category] with [feature] | "crm with email tracking" |
| [feature] software | "lead scoring software" |
| how to [task] in [tool] | "how to set up workflows in hubspot" |

### Integration keywords

| Pattern | Example |
|---------|---------|
| [tool A] [tool B] integration | "salesforce slack integration" |
| does [tool] integrate with [tool] | "does hubspot integrate with jira" |
| connect [tool] to [tool] | "connect hubspot to salesforce" |

### Pricing keywords

| Pattern | Example |
|---------|---------|
| [tool] pricing | "hubspot pricing" |
| [tool] pricing [year] | "salesforce pricing 2026" |
| [category] pricing comparison | "crm pricing comparison" |
| [tool] free plan | "hubspot free crm" |

---

## Common Keyword Research Mistakes

| Mistake | Why it's wrong | Fix |
|---------|---------------|-----|
| Only targeting high-volume head terms | Head terms are dominated by high-DR competitors. You'll never rank | Target long-tail (100-1,000 volume) with high intent |
| Ignoring comparison keywords | These have the highest conversion rate in SaaS | Build comparison pages for every competitor |
| Targeting keywords based on volume alone | High volume + low intent = traffic that doesn't convert | Score by business relevance and intent, not just volume |
| Creating separate pages for keywords in the same cluster | Causes keyword cannibalization — pages compete with each other | One page per cluster. Include all variations |
| Not including AI search queries | AI engines use different phrasing than Google | Test queries in ChatGPT/Perplexity and include conversational variants |
| Doing keyword research once | Markets, competitors, and buyer language evolve | Refresh keyword research quarterly |

---

## Pre-Research Checklist

- [ ] Seed keywords generated from product, competitors, buyers, and AI queries (50-100 seeds)
- [ ] Keyword research tool access confirmed (Ahrefs, Semrush, or equivalent)
- [ ] Google Search Console access for existing ranking data
- [ ] Competitor list defined (5-10 competitors for content gap analysis)
- [ ] Intent layer framework understood (problem, solution, product, purchase)
- [ ] Scoring rubric adopted (14+ = priority 1)
- [ ] Clustering rules defined (one page per cluster)
- [ ] Content plan template ready to receive clusters
- [ ] AI search query testing completed (30+ queries in ChatGPT/Perplexity)
- [ ] Quarterly refresh schedule set

---

## Anti-Pattern Check

- Targeting "CRM" (1M volume, impossible to rank) → Target "best crm for 50-person saas startup" (500 volume, rankable, high intent). Long-tail with intent beats head terms every time
- All keywords are problem-aware → Your content plan will be 100% blog posts with low conversion. Add solution-aware and product-aware keywords (comparisons, alternatives, pricing) for pipeline impact
- Keyword list has 500 entries with no prioritization → An unprioritized list is useless. Score every keyword cluster and focus on the top 20 first. Quality of targeting beats quantity
- Creating 3 pages for "crm comparison", "best crm tools", and "top crm software" → These are the same intent. One page targets all three. Multiple pages causes cannibalization
- Never looking at what competitors rank for → Ahrefs Content Gap shows keywords competitors rank for that you don't. This is the fastest way to find high-value opportunities you're missing
- Skipping AI search query research → Buyers ask AI engines differently than they search Google. "What's the best CRM for a 50-person SaaS startup?" is an AI query that a standard keyword tool won't surface. Test in AI engines directly