Query Type Segmentation: Branded, Commercial, and Informational Queries in Google Search Console

Introduction

Google Search Console shows search queries driving traffic to your site—a mix of user intents. Some searchers know your brand. Others compare options before buying. Some research and gather information.

Treating all queries the same is a mistake.

"your-brand-name login" and "best project management software" represent different user intents with different performance expectations, optimization strategies, and success metrics.

This guide, part of our complete GSC guide, teaches query segmentation by type using filters and comparisons. Understand performance metrics based on keyword research and search intent, interpret branded performance, find commercial opportunities, identify informational gaps, and optimize by intent using task prioritization.

Why Query Type Segmentation Matters

The Problem with Aggregate Data

Overall GSC metrics resemble a restaurant's average review score. A 3.5-star average could mean "consistently mediocre" or "half love it, half hate it." Averages hide stories.

Consider:

Site average: 5% CTR
Branded queries: 40% CTR
Commercial queries: 3% CTR
Informational queries: 1.5% CTR

That 5% average is meaningless. You can't evaluate performance without knowing query types.

The Three Dimensions of Query Intent

Every search query falls somewhere along three dimensions:

1. User Awareness (Brand Recognition)

Branded: User knows your brand specifically
Non-branded: User is unaware of your brand

2. Transaction Intent (Commercial Intent)

Commercial/Transactional: Ready to buy or take action
Informational: Researching, learning, exploring

3. Specificity (Query Clarity)

Specific: Clear, defined need
Broad: General topic exploration

For practical SEO analysis, we simplify this into three main categories:

Branded queries - Searches that include your brand name or specific products
Commercial queries - Searches with buying or transactional intent
Informational queries - Searches seeking information, answers, or education

Visual Placeholder: [Venn diagram showing overlap between Branded, Commercial, and Informational query types, with examples in each segment]

Query Type #1: Branded Queries

What Are Branded Queries?

Queries with your company name, product names, branded features, or variations indicating the searcher seeks you specifically.

Examples:

your-company-name
your-company login
your-product-name pricing
your-company-name vs competitor
your-company reviews

Branded queries represent demand you created through marketing, word-of-mouth, or previous interactions. Earned traffic—people actively seeking you.

Expected Performance for Branded Queries

Benchmarks:

CTR: 30-60% (desktop), 20-50% (mobile)
Average Position: 1.0-2.0
Conversion Rate: 10-30%

Problems:

Position 1.0-2.0 missing = Not ranking #1 for your brand (serious)
CTR below 30% = Weak title/description, or competitors bidding on your brand
Low impressions = Brand awareness problem

How to Identify Branded Queries in GSC

Method #1: Simple Contains Filter

Performance report → Queries tab
"+ NEW" filter → "Query" → "Contains"
Enter your brand name

Limitations: Misses variations/misspellings, may include false positives.

Method #2: Regex Filter (Advanced)

your-brand|yourbrand|your brand|yrbrand

Performance → Queries → "+ NEW" filter
"Query" → "Custom (regex)"
Enter pattern

Include common misspellings. "youcompany" instead of "your company" is still branded intent.

Visual Placeholder: [Screenshot showing GSC regex filter setup for branded queries]

Branded Query Analysis: What to Look For

Key Questions to Answer:

1. Do you rank #1 for your brand?

Filter by your brand name
Check average position
If not 1.0-2.0, investigate why (penalty, namesake domains, etc.)

2. Is your branded CTR healthy?

Compare branded CTR to industry benchmarks
Low CTR suggests poor title/description or aggressive competitor ads
Check SERP features (People Also Ask, Knowledge Panel) stealing clicks

3. Are branded impressions growing?

Branded impression growth = brand awareness growth
Flat branded impressions = marketing isn't creating new awareness
Declining branded impressions = brand interest declining (serious concern)

4. What branded modifiers do people use?

"brand-name login" = existing customers
"brand-name pricing" = consideration stage
"brand-name reviews" = researching before buying
"brand-name vs competitor" = comparing options

Each modifier tells you where users are in their journey.

Visual Placeholder: [Chart showing branded query performance metrics comparison: Position, CTR, Clicks over time]

Common Branded Query Problems

Problem #1: Not Ranking #1 for Your Brand

Causes: Manual penalty, algorithmic suppression, namesake company, generic brand name, competitor PPC bidding

Solution:

Check for manual actions
Review Core Web Vitals and technical SEO
Namesake conflicts: focus on branded + modifier queries
PPC competitors: consider defensive campaigns

Problem #2: Low Branded CTR

Causes: Generic title tags, competitor paid ads, SERP features (PAA, Knowledge Panel), wrong page ranking

Solution:

Optimize compelling title tags
Add structured data for Knowledge Panel control
Homepage should rank for main brand query

Problem #3: Branded Query Modifiers You Don't Rank For

Users search "your-brand-name pricing" but you don't rank? They want specific information you should provide.

Solution:

Create dedicated pages for common branded modifiers
Add clear navigation from homepage
Optimize title tags to match exact queries

Query Type #2: Commercial Queries

What Are Commercial Queries?

Queries with buying or transactional intent. Users evaluate options, compare solutions, or ready to purchase.

Patterns:

Best/Top: "best CRM software"
Reviews/Comparison: "Salesforce vs HubSpot"
Pricing/Cost: "email marketing software pricing"
Buy/Purchase: "buy standing desk"
[Category] + [Location]: "web design agency Chicago"
Specific Products: "iPhone 15 Pro"

High-intent traffic. Users close to decisions. Lower conversion than branded, but larger volume opportunity.

Expected Performance Metrics for Commercial Queries

Commercial queries are more competitive than branded but more valuable than purely informational:

Typical Performance Benchmarks:

CTR: 2-8% (highly dependent on position)
Average Position: 5.0-15.0 (competitive, harder to rank)
Conversion Rate: 3-10% (lower than branded, higher than informational)

Competition matters: "best CRM" is more competitive than "best CRM for real estate teams." More specific commercial queries often have better performance metrics.

How to Identify Commercial Queries in GSC

Method #1: Commercial Intent Keywords

Filter for queries containing commercial signals:

Step-by-step:

Performance → Queries → "+ NEW" filter
Select "Query"
Choose "Custom (regex)"
Enter this regex pattern:

best|top|vs|versus|review|compare|comparison|pricing|price|cost|buy|purchase|shop|deal|discount|affordable|cheap

This catches most common commercial intent modifiers.

Method #2: Category + Action Queries

For specific industries, add category-specific patterns:

B2B SaaS example:

software|tool|platform|solution|service|app|system

E-commerce example:

buy|shop|store|purchase|order|sale

Local business example:

near me|in [city]|[city] [service]

Visual Placeholder: [Screenshot showing commercial query filter with regex pattern and resulting query list]

Commercial Query Analysis: What to Look For

Key Questions to Answer:

1. What's your position distribution?

Position 1-3: High visibility, high CTR
Position 4-10: Visible, medium CTR, opportunity to improve
Position 11-20: Low visibility, low CTR, major opportunity

Filter your commercial queries and sort by position. The queries where you rank #5-10 are your biggest opportunities—you're close to top positions and small improvements yield big traffic gains.

2. Which commercial queries have high impressions but low clicks?

The opportunity formula:

High impressions = Google thinks you're relevant
Low clicks = You're not ranking well enough or CTR is poor
Action: These are your optimization priorities

3. Are you ranking for your target commercial keywords?

Most businesses have target commercial queries:

"best [category]" where you have a comparison guide
"[your-solution] vs [competitor]" where you have a comparison page
"[category] pricing" where you have a pricing page

Filter for your target queries specifically. If you created content to rank for "best marketing automation software" but you're not seeing any impressions, either:

Your content isn't ranking at all (position 50+)
Your content is ranking but for different queries
Your content is too new (give it 2-3 months)

4. What's your CTR by position for commercial queries?

Expected CTR benchmarks by position:

Position 1: 8-15%
Position 2: 5-10%
Position 3: 4-7%
Position 4-5: 3-5%
Position 6-10: 1-3%

If your CTR is below these benchmarks, your title/description is the problem, not your rankings.

Visual Placeholder: [Chart showing CTR vs. Position for commercial queries with industry benchmark comparison]

Common Commercial Query Problems

Problem #1: Ranking for Commercial Queries with Informational Content

The scenario:

You rank position 8 for "best CRM software"
Your ranking page is a blog post "What is CRM?"
Google shows you in results, but users skip you (low CTR)

Why this happens: Your content is tangentially related but doesn't match user intent.

Solution: Create a dedicated comparison guide, product roundup, or category page that directly answers the commercial query.

Problem #2: Commercial Keywords Cannibalization

The scenario:

Multiple pages rank for the same commercial query
Your product page ranks position 12
Your blog post ranks position 18
Neither ranks well because Google is confused

Solution:

Consolidate content (choose one page to rank)
Internal link from blog post to product page with target commercial keyword
Use canonical tags if content is duplicative

Problem #3: Missing Commercial Modifiers

The scenario:

You rank well for "project management software"
You don't rank for "best project management software"
The second query has 10x more search volume

Solution:

Audit your title tags to include commercial modifiers
Create dedicated "best" or "top" category pages
Update existing category pages to match commercial intent

Query Type #3: Informational Queries

What Are Informational Queries?

Informational queries are searches where the user wants to learn something, find an answer, or understand a topic. There's no immediate buying intent.

Common Informational Query Patterns:

How to: "how to create a sales funnel," "how to use pivot tables"
What is: "what is SEO," "what is compound interest"
Why/When/Where: "why is my website slow," "when to use HTTPS"
Guide/Tutorial: "email marketing guide," "Excel tutorial"
Definition: "conversion rate definition," "what does CTR mean"
Question form: "can you freeze bananas," "is Python hard to learn"

Why they matter: Informational queries represent top-of-funnel traffic. Users aren't ready to buy yet, but you're building awareness, authority, and trust. They're the foundation of content marketing and SEO.

Expected Performance Metrics for Informational Queries

Informational queries typically have the highest volume but lowest immediate value:

Typical Performance Benchmarks:

CTR: 1-5% (position-dependent)
Average Position: 10.0-30.0 (very competitive for short-tail)
Conversion Rate: 0.5-3% (lowest of all query types)

Volume vs. value trade-off: Informational queries often have massive search volume, but conversion rates are much lower than commercial or branded queries.

Visual Placeholder: [Comparison table showing CTR, Position, and Conversion Rate benchmarks across Branded, Commercial, and Informational query types]

How to Identify Informational Queries in GSC

Method #1: Informational Intent Keywords

Use regex to filter for common informational patterns:

how to|what is|why|when|where|guide|tutorial|tips|learn|examples|definition|meaning|explained

Method #2: Question-Based Queries

Many informational queries are phrased as questions:

how|what|why|when|where|which|who|can|should|does|is|are

Method #3: Exclusion Method

Filter out branded and commercial queries to see what's left:

Create a branded query segment
Create a commercial query segment
View all queries NOT matching those patterns

This reveals your pure informational traffic.

Visual Placeholder: [Screenshot showing informational query filter and resulting long-tail question queries]

Informational Query Analysis: What to Look For

Key Questions to Answer:

1. What informational topics drive the most impressions?

Sort your informational queries by impressions (not clicks). High-impression informational queries represent topics with massive search interest—even if your CTR is low, the volume opportunity is huge.

Example insight:

"what is conversion rate optimization" has 50,000 impressions/month
You rank position 18 (page 2)
Current clicks: 200/month
Opportunity: Improve to position 5 → potential 2,500+ clicks/month

2. Which informational queries have best CTR?

High CTR informational queries indicate:

You rank in top positions (good)
Your title/description is compelling (good)
Potential to convert this traffic (opportunity)

Action: Analyze high-CTR informational pages for conversion optimization. Add CTAs, lead magnets, or related product links.

3. Are you capturing featured snippets?

Informational queries frequently trigger featured snippets (position 0). These dramatically increase CTR.

How to identify featured snippet opportunities:

Filter informational queries
Look for position 1-5 rankings
Manually check SERPs to see if featured snippet exists
If competitor has featured snippet, optimize your content to win it

Featured snippet optimization:

Add clear, concise definitions
Use structured formats (lists, tables, steps)
Answer the question directly in first 40-60 words
Use proper heading hierarchy (H2, H3)

4. What's the question distribution?

Group your informational queries by question type:

How to queries → Tutorial/guide content opportunities
What is queries → Definition/explanation content
Why queries → Thought leadership/expert content
Best queries → Comparison/list content (often commercial intent)

This reveals content gaps and opportunities.

Visual Placeholder: [Pie chart showing distribution of informational query types: How-to, What is, Why, etc.]

Common Informational Query Problems

Problem #1: High Traffic, Zero Conversions

The scenario:

Your "what is SEO" blog post gets 10,000 visits/month
Conversion rate: 0.1% (10 conversions)
Most users read and leave

Why this happens: Top-of-funnel informational content attracts early-stage users. They're not ready to buy.

Solution:

Add CTAs for lead magnets (eBooks, templates, courses)
Link to related commercial content (comparison guides, product pages)
Set realistic expectations (informational content builds awareness, not immediate sales)
Track micro-conversions (email signups, resource downloads)

Problem #2: Informational Content Outranking Commercial Pages

The scenario:

Your informational blog post ranks for commercial keywords
Your product/category page ranks lower or not at all
Users looking to buy land on blog post, don't convert

Why this happens: Google sees your blog post as more comprehensive or relevant than your commercial page.

Solution:

Improve commercial page content (more detailed, helpful)
Add internal links from blog post to commercial page
Use keyword clustering (blog post targets informational, category page targets commercial)
Update blog post title/meta to de-emphasize commercial terms

Problem #3: Low Impressions for High-Volume Informational Topics

The scenario:

You created comprehensive guide on popular topic
Expected thousands of impressions
GSC shows only hundreds

Why this happens:

Content is too new (needs time to rank)
Content lacks authority signals (backlinks, internal links)
Content doesn't match search intent (your "guide" is actually sales content)
Page has technical issues (crawling, indexing)

Solution:

Give it 2-4 months to mature
Build internal links from related content
Ensure content genuinely answers the query
Check GSC Index Coverage for issues

Advanced Query Segmentation Strategies

Segment #1: Branded Commercial Queries

What they are: Queries that combine your brand name with commercial intent.

Examples:

"your-brand-name pricing"
"your-brand-name vs competitor"
"your-brand-name reviews"

Why segment separately: These queries represent high-intent users who already know your brand. They should have very high conversion rates (20-40%).

Performance expectations:

CTR: 20-40%
Position: 1.0-3.0
Conversion rate: 20-40%

Regex pattern:

(your-brand).*(pricing|price|cost|vs|versus|review|comparison|alternative)|(pricing|price|cost|vs|versus|review|comparison|alternative).*(your-brand)

Segment #2: Commercial Long-Tail Queries

What they are: Highly specific commercial queries with lower search volume but higher intent.

Examples:

"best CRM for real estate agents with email automation"
"affordable project management tool for remote teams under $50"
"email marketing software with SMS integration"

Why segment separately: Long-tail commercial queries are easier to rank for and often have higher conversion rates than generic commercial queries.

Performance expectations:

CTR: 5-12% (less competition = better CTR)
Position: 3.0-8.0 (easier to rank)
Conversion rate: 5-15% (higher specificity = higher intent)

How to identify: Filter commercial queries with 5+ words.

Segment #3: Navigational Queries

What they are: Searches where the user wants to find a specific page or section of your site.

Examples:

"your-brand-name blog"
"your-brand-name contact"
"your-brand-name careers"
"your-brand-name support"

Why segment separately: These represent existing customers or highly familiar users. They should have extremely high CTR and low bounce rates.

Performance expectations:

CTR: 40-70%
Position: 1.0-2.0
Bounce rate: Very low (they found what they wanted)

Regex pattern:

(your-brand).*(login|signin|account|support|help|contact|careers|jobs|blog|about)

Segment #4: Competitor Comparison Queries

What they are: Queries comparing your brand to competitors or comparing competitors (where you rank).

Examples:

"your-brand vs competitor"
"competitor-A vs competitor-B" (you rank with comparison content)
"competitor alternative"

Why segment separately: These represent users actively comparing options. Very high commercial intent. If you rank well, conversion opportunity is massive.

Performance expectations:

CTR: 3-10%
Position: 3.0-10.0 (competitive)
Conversion rate: 5-20% (high intent)

Strategy: Create comparison pages for top competitors. Optimize for "[your-brand] vs [competitor]" and "[competitor] alternative."

Visual Placeholder: [Matrix showing the four advanced segments with example queries, CTR benchmarks, and conversion rates]

Combining Filters for Deeper Insights

Multi-Filter Technique #1: Branded + Device Segmentation

Analysis: How do branded queries perform on mobile vs. desktop?

How to do it:

Filter queries: Contains "[your-brand]"
Compare device performance (mobile vs desktop)

Common insights:

Mobile branded CTR lower → Title too long for mobile display
Desktop branded traffic higher → Mobile site has issues (speed, UX)
Tablet branded traffic spike → Investigate why

Multi-Filter Technique #2: Commercial + Geographic Segmentation

Analysis: Which countries/regions show commercial intent for your product?

How to do it:

Filter queries: Regex with commercial patterns
Group by country

Common insights:

High commercial impressions, low clicks in Country X → Opportunity to expand
High commercial clicks, low conversions in Country X → Localization issues (currency, language, shipping)

Multi-Filter Technique #3: Informational + Page Performance

Analysis: Which pages attract informational traffic and how well do they convert?

How to do it:

Filter queries: Regex with informational patterns
Switch to Pages tab to see which pages rank for these queries
Cross-reference with Analytics conversion data

Common insights:

Blog post X attracts huge informational traffic but zero conversions → Add CTAs, lead magnets
Guide Y attracts informational traffic with 5% conversion → Replicate this success on other guides

Visual Placeholder: [Screenshot showing multi-filter setup in GSC: Branded query + Mobile device filter with performance comparison]

Putting It All Together: Query Segmentation Workflow

Step 1: Establish Your Baseline (Week 1)

Tasks:

Export all queries (last 28 days)
Create three filtered views:
- Branded queries
- Commercial queries
- Informational queries
Document baseline performance:
- Impressions, clicks, CTR, position for each segment
Identify top 20 queries in each segment

Deliverable: Baseline performance spreadsheet

Step 2: Identify Opportunities (Week 2)

For each segment, answer:

Branded Queries:

Do we rank #1 for our brand? (If no, why?)
Is branded CTR above 30%? (If no, why?)
What branded modifiers are we missing?

Commercial Queries:

Which commercial queries rank position 4-10? (Opportunity list)
Which commercial queries have high impressions, low clicks? (Optimization priority)
Are we ranking for our target commercial keywords?

Informational Queries:

Which informational topics have massive impression potential?
Which informational queries can we capture featured snippets for?
Which informational pages have best conversion rates? (Template for others)

Deliverable: Opportunity list with prioritization

Step 3: Create Action Plan (Week 3)

Prioritize opportunities by:

Effort: How hard is it to improve?
Impact: How much traffic/conversions will it generate?
Timing: How quickly will we see results?

Prioritization framework:

Quick Wins (Do First):

Branded queries not ranking #1 (easy fix, high impact)
Commercial queries ranking position 5-7 (small push, big traffic gain)
Featured snippet opportunities (structured content update, high CTR boost)

Medium-Term Projects (Do Second):

New commercial content for high-volume keywords (3-6 months to rank)
Informational content upgrades (improved conversions over time)
Category page optimization (competitive, slower results)

Long-Term Investments (Do Third):

Authority building for competitive commercial queries (6-12 months)
Comprehensive informational guides (long content creation, slow ranking)

Deliverable: Prioritized action plan

Step 4: Implement and Monitor (Ongoing)

Monthly check-in:

Review query segment performance (branded, commercial, informational)
Track position changes for target queries
Measure traffic and conversion impact
Adjust strategy based on results

Visual Placeholder: [Flowchart showing 4-step query segmentation workflow from baseline to ongoing monitoring]

Common Mistakes to Avoid

Mistake #1: Treating All Queries the Same

The problem: You optimize all content the same way, regardless of query intent.

The fix: Tailor optimization strategies to query type:

Branded: Focus on brand consistency, clear navigation, conversion optimization
Commercial: Focus on comparison content, product details, trust signals
Informational: Focus on comprehensive answers, readability, featured snippets

Mistake #2: Ignoring Branded Query Performance

The problem: "We already rank for our brand, so we don't need to optimize it."

The fix: Branded queries are your most valuable traffic. Even small CTR improvements (40% → 45%) can drive significant revenue. Optimize title tags, add structured data, and monitor for competitor interference.

Mistake #3: Only Targeting Commercial Queries

The problem: You only create commercial content because it converts better.

The fix: Informational content builds awareness and authority. It's the top of the funnel. Without informational traffic, you have no one to convert with commercial content. Balance is key.

Mistake #4: Using the Wrong Performance Benchmarks

The problem: "Our average CTR is 3%, which is bad."

The fix: 3% CTR is bad for branded queries (should be 30%+), but fine for commercial queries. Always segment before evaluating performance.

Mistake #5: Not Accounting for Search Volume

The problem: You prioritize a commercial query at position 5 with 100 monthly searches over an informational query at position 15 with 50,000 monthly searches.

The fix: Consider volume in your prioritization. Sometimes a small position improvement on a high-volume informational query yields more traffic than ranking #1 for a low-volume commercial query.

Mistake #6: Forgetting About User Journey

The problem: You expect immediate conversions from informational traffic.

The fix: Informational queries represent early-stage users. They'll convert later (days, weeks, or months). Track assisted conversions, email signups, and return visitors, not just direct conversions.

Visual Placeholder: [Infographic showing the 6 common mistakes with brief explanations]

Tools and Templates

Regex Patterns Library

Copy and use these in Google Search Console:

Branded Queries:

your-brand|yourbrand|your brand

Commercial Queries:

best|top|vs|versus|review|compare|comparison|pricing|price|cost|buy|purchase|shop|deal|discount|affordable|cheap

Informational Queries:

how to|what is|why|when|where|guide|tutorial|tips|learn|examples|definition|meaning|explained

Navigational Queries:

(your-brand).*(login|signin|account|support|help|contact|careers|jobs|blog|about)

Competitor Comparison:

vs|versus|alternative|compared|competitor-name

Query Segmentation Spreadsheet Template

Column structure:

Query	Impressions	Clicks	CTR	Position	Type	Priority	Action
your-brand login	10,000	4,500	45%	1.0	Branded	Low	Monitor
best crm software	50,000	1,500	3%	8.0	Commercial	High	Optimize
what is crm	100,000	2,000	2%	12.0	Informational	Medium	Featured snippet

Priority scoring:

High impression volume + position 4-10 = High priority
Low impression volume + position 11+ = Low priority
Branded query not ranking #1 = Critical priority

Performance Dashboard Setup

Create a Google Sheets dashboard with these segments:

Tab 1: Branded Performance

Total branded impressions, clicks, CTR, position
Top 20 branded queries
Branded performance trend (month-over-month)

Tab 2: Commercial Performance

Total commercial impressions, clicks, CTR, position
Top 20 commercial queries by opportunity (high impressions, medium position)
Commercial CTR by position range

Tab 3: Informational Performance

Total informational impressions, clicks, CTR, position
Top 20 informational queries by impression volume
Featured snippet opportunities

Tab 4: Comparison

Side-by-side performance of all three segments
Trends over time
Conversion rate by segment (requires GA integration)

Visual Placeholder: [Screenshot of example Google Sheets dashboard with three tabs showing branded, commercial, and informational query performance]

Real-World Examples

Example #1: SaaS Company

Situation:

Company sells project management software
Overall CTR: 4.2%
Overall position: 8.5

After query segmentation:

Branded queries: CTR 38%, Position 1.2 (great)
Commercial queries: CTR 2.8%, Position 9.5 (opportunity)
Informational queries: CTR 1.5%, Position 15.2 (needs work)

Insights:

Branded performance is healthy
Commercial queries just outside top 5 (big opportunity)
Informational content not ranking well (authority issue)

Action plan:

Optimize top 10 commercial queries ranking position 6-10
Build backlinks to top informational guides
Create new comparison content for "vs competitor" queries

Results after 3 months:

Commercial query average position improved to 6.2 (+3.3 positions)
Commercial CTR improved to 4.5% (+1.7%)
Commercial traffic increased 47%

Example #2: E-commerce Site

Situation:

Online retailer selling outdoor gear
Impressions high, clicks low

After query segmentation:

Branded queries: 15% of impressions, 45% of clicks (healthy)
Commercial queries: 30% of impressions, 40% of clicks (good)
Informational queries: 55% of impressions, 15% of clicks (problem)

Insights:

Informational content drives massive impressions but poor CTR
Informational content ranking position 15-25 (page 2-3)
Missing featured snippets for top informational queries

Action plan:

Optimize top 20 informational guides for featured snippets
Add structured data to guides (HowTo, FAQ schema)
Improve internal linking to informational content

Results after 4 months:

Captured 12 featured snippets
Informational CTR improved from 1.5% to 4.2%
Informational traffic increased 180%
Assisted conversions from informational traffic increased 65%

Example #3: Local Service Business

Situation:

HVAC company serving three cities
Traffic flat despite content efforts

After query segmentation:

Branded queries: Position 1.0, but only 200 impressions/month (low brand awareness)
Commercial queries: Position 12-20 for most queries (not visible)
Informational queries: Position 5-10 for several guides (best performance)

Insights:

Brand awareness is the primary problem (not ranking issues)
Informational content is winning, but not driving enough commercial traffic
Commercial queries too competitive for current domain authority

Action plan:

Focus on branded awareness (offline marketing, PR, local sponsorships)
Target long-tail commercial queries (less competitive)
Add strong CTAs to informational content (drive phone calls)

Results after 6 months:

Branded impressions increased 280% (offline efforts working)
Ranked page 1 for 15 long-tail commercial queries
Phone call conversions from informational content increased 45%

Visual Placeholder: [Three side-by-side comparison charts showing before/after performance for each example]

Key Takeaways

1. Query segmentation reveals hidden insights

Aggregate data hides the story
Different query types have different expectations
You can't optimize what you don't segment

2. Performance benchmarks vary dramatically by query type

Branded: 30-60% CTR, Position 1-2
Commercial: 2-8% CTR, Position 5-15
Informational: 1-5% CTR, Position 10-30

3. Each query type requires different strategies

Branded: Brand protection, conversion optimization
Commercial: Comparison content, trust signals, detailed product info
Informational: Comprehensive guides, featured snippets, top-of-funnel optimization

4. Opportunities exist in every segment

Branded: Don't ignore (most valuable traffic)
Commercial: Position 5-10 queries are biggest opportunities
Informational: High-volume, featured snippet opportunities

5. User journey matters

Informational traffic converts later (track assisted conversions)
Commercial traffic is high-intent (optimize for immediate conversion)
Branded traffic should convert at highest rate

6. Use regex patterns for precise filtering

Simple "contains" filters miss variations
Regex patterns capture more complete segments
Test patterns to avoid false positives

Next Steps

Today:

Open Google Search Console
Create three filtered views (branded, commercial, informational)
Document baseline performance for each segment

This Week:

Identify top 10 opportunities in each segment
Prioritize based on effort vs. impact
Create action plan for next 30 days

This Month:

Implement optimizations for top opportunities
Set up monthly monitoring dashboard
Track performance changes for optimized queries

This Quarter:

Review query segment performance trends
Adjust strategy based on results
Expand to advanced segments (branded commercial, competitor comparisons)

Ready to take your Google Search Console analysis even deeper?

Related articles:

How to Read Your GSC Performance Report (Beginner's Guide) - Start here if GSC is new to you
GSC Filters and Comparisons: A Complete Tutorial - Master advanced filtering techniques
Understanding the GSC Performance Report: What Your Data Is Really Telling You - Learn to interpret performance patterns
GSC Queries Report: Finding Your Biggest Opportunities - Turn query data into action plans

About the Author

This guide is part of our comprehensive Google Search Console Mastery series. We help businesses turn their GSC data into actionable SEO strategies that drive real traffic growth.

More GSC Resources:

The Complete Guide to Google Search Console Analysis - Ultimate guide to GSC
GSC Data Limitations You Need to Know - Understanding sampling and data limits
Query Anonymization in GSC: What You're Not Seeing - Hidden query data explained

Last updated: January 21, 2026