Google Ads Reports & Analysis: The Complete Guide 2026
Reality: Most only look at clicks and costs. The truly important metrics are ignored. This guide shows which KPIs really matter and how to optimize data-driven.
Why the Right Metrics Are Critical
Example "Vanity Metrics" vs. "Business Metrics":
Campaign A (looks good):
Clicks: 5,000 (many!)
CTR: 8% (high!)
CPC: €0.80 (low!)
→ "Successful campaign!" ❓
But:
Conversions: 15
Cost per Conversion: €267
ROAS: 180%
→ UNPROFITABLE! ❌
Campaign B (looks bad):
Clicks: 800 (few)
CTR: 2.5% (low)
CPC: €4.50 (high!)
→ "Bad campaign"? ❓
But:
Conversions: 45
Cost per Conversion: €80
ROAS: 625%
→ HIGHLY PROFITABLE! ✅
Lesson: Clicks, CTR, CPC are "vanity metrics". Conversions, CPA, ROAS are "business metrics"!
The Most Important Google Ads KPIs
A note on the guide values: The ratings in this section are rough orientation values from my practice, not industry statistics. Your most important yardstick is your own previous periods and your margin.
Tier 1: Business Metrics (most important!)
1. Conversions
What: Number of goal actions (purchases, leads, etc.)
Where: Google Ads → Campaigns → Column "Conversions"
Goal: Maximize (at acceptable CPA)
2. Cost per Conversion (CPA)
What: Cost per conversion
Calculation: Cost / Conversions
Example: €3,000 / 50 conversions = €60 CPA
Orientation from my practice (e-commerce):
- Under €50: ✅ Excellent
- €50-€100: 😐 Ok
- Over €100: ❌ Expensive (depending on product)
Orientation from my practice (B2B lead-gen):
- Under €50: ✅ Cheap
- €50-€150: 😐 Ok
- Over €150: ❌ Expensive
3. ROAS (Return on Ad Spend)
What: Revenue per €1 ad spend
Calculation: Revenue / Cost × 100%
Example: €15,000 revenue / €3,000 cost = 500% ROAS
→ €1 spent brings €5 revenue
Blanket ROAS benchmarks won't help much, your margin decides.
Break-even ROAS = 1 / margin:
Margin 40% → Min. 250% ROAS (break-even)
Margin 30% → Min. 333% ROAS
Margin 20% → Min. 500% ROAS
4. ROI (Return on Investment)
What: Actual profit after deducting all costs
Calculation: (Revenue - Cost - Product costs) / Cost × 100%
Example:
Revenue: €15,000
Google Ads cost: €3,000
Product costs (60%): €9,000
Profit: €15,000 - €3,000 - €9,000 = €3,000
ROI: €3,000 / €3,000 × 100% = 100%
→ For every €1 spent, €1 profit
Profitable from: >0% ROI (profit after ad and product costs, fixed costs not yet deducted)
5. Conversion Rate
What: % of clicks that convert
Calculation: Conversions / Clicks × 100%
Example: 50 conversions / 2,000 clicks = 2.5%
Orientation from my practice (e-commerce):
- Over 3%: ✅ Excellent
- 2-3%: 😐 Good
- 1-2%: ⚠️ Average
- Under 1%: ❌ Problem
Orientation from my practice (lead-gen):
- Over 10%: ✅ Excellent
- 5-10%: 😐 Good
- 3-5%: ⚠️ Ok
- Under 3%: ❌ Problem
Tier 2: Performance Metrics
6. CTR (Click-Through Rate)
What: % of impressions that lead to clicks
Calculation: Clicks / Impressions × 100%
Example: 200 clicks / 10,000 impressions = 2%
Important for: Quality Score (expected CTR is one of its three components, but according to Google the QS itself is only a diagnostic tool)
Orientation from my practice (Search):
- Over 5%: ✅ Excellent
- 3-5%: 😐 Good
- 2-3%: ⚠️ Average
- Under 2%: ❌ Bad
Orientation from my practice (Display):
- Over 0.5%: ✅ Good
- 0.3-0.5%: 😐 Ok
- Under 0.3%: ❌ Low
7. CPC (Cost per Click)
What: Average cost per click
Calculation: Cost / Clicks
Example: €500 / 250 clicks = €2 CPC
Important: CPC alone says nothing about profitability!
Low CPC + low CR = high CPA (bad)
High CPC + high CR = low CPA (good)
8. Impression Share
What: % of possible impressions you receive
Example: 1,000 impressions / 2,000 possible = 50% IS
Components:
- Search Lost IS (budget): Lost due to budget
- Search Lost IS (rank): Lost due to Ad Rank (bid, ad quality and other factors)
Goal:
- Brand keywords: >90% IS
- Generic keywords: >60% IS (if profitable)
9. Quality Score
What: Google's relevance rating (1-10)
Where: Google Ads → Keywords → Columns "Quality Score"
Important: According to Google a diagnostic tool, not a direct auction input. It shows where the ad, keyword or landing page needs work.
Goal:
- QS 8-10: ✅ Excellent
- QS 6-7: 😐 Ok
- QS 4-5: ⚠️ Needs improvement
- QS 1-3: ❌ Critical
Tier 3: Diagnostic Metrics
10. Bounce Rate
What: % of sessions without engagement (in GA4 = 100% minus engagement rate)
Source: Google Analytics 4
Example: 2,000 non-engaged sessions / 4,000 sessions = 50%
Note: The old definition "left after 1 page" comes from
Universal Analytics, which was shut down in July 2023.
Orientation from my practice:
- Under 40%: ✅ Excellent
- 40-60%: 😐 Ok
- 60-70%: ⚠️ High
- Over 70%: ❌ Problem (landing page irrelevant?)
11. Time on Site
What: Average time on website (in GA4: "Average engagement time")
Source: GA4
Orientation from my practice (by industry):
- E-commerce: 2-4 min good
- B2B: 3-6 min good
- Content: 5-10 min good
Under 30 seconds: ❌ Problem (irrelevant traffic)
12. Pages per Session
What: Average pages per visit (in GA4: "Views per session")
Source: GA4
More pages = higher engagement (usually good)
But: E-commerce "too many" = user can't find → leaves
The Weekly Performance Check
Monday morning routine (15 min):
Check 1: Overall performance
Google Ads → Overview (last 7 days vs. previous 7 days)
→ Checklist (rules of thumb from my practice):
✓ Conversions: +/- 20% normal, +/-50% = investigate!
✓ CPA: +/- 15% normal, +30% = problem!
✓ ROAS: +/- 10% normal, -20% = alarm!
✓ Cost: Budget fully spent?
Check 2: Campaign performance
Campaigns → Sort by "Conversions"
→ Checklist:
✓ Top campaigns: Running stable? Budget fully spent?
✓ Bottom campaigns: Why bad? Pause?
✓ New campaigns: First conversions after 1-2 weeks?
Check 3: Keyword performance
Keywords → Filter: "Last 7 days" + "Min. 10 clicks"
→ Sort by CPA (highest first)
→ Checklist:
✓ Keywords with CPA >150% above goal: Pause!
✓ Keywords with 0 conversions but >50 clicks: Review (pause?)
✓ New keywords: Performance?
Check 4: Search terms
Campaigns → Insights and reports → Search terms
→ Checklist:
✓ Add irrelevant terms as negative keywords
✓ Add high-performing terms as exact-match keywords
✓ Strange queries = check Broad Match keywords
Check 5: Budget status
Campaigns → Columns: "Budget" + "Cost"
→ Checklist:
✓ "Limited by Budget"? → Increase (if ROAS good)
✓ Budget underutilized (<80%)? → Increase bids
Between your weekly checks, you can get budget and anomaly alerts by email, for example with Google Ads scripts you write with AI.
The Most Important Google Ads Reports
Note on the bid adjustments in the examples: The plus and minus values apply to manual bidding. According to Google's help, Smart Bidding doesn't support these adjustments, one exception being a -100% device exclusion.
Report 1: Campaign Performance Dashboard
Setup:
Google Ads → Campaigns → Report editor → Predefined reports (dimensions)
→ "Campaign Performance"
→ Add columns:
- Conversions
- Cost per Conversion
- Conversion Rate
- ROAS (or conversion value/cost)
- Impression Share
Time period: Last 30 days vs. previous 30 days
Analysis:
- Sort by ROAS → Identify top performers
- Budget shifts from low to high performers
Report 2: Keyword Performance Report
Setup:
Reports → Keywords
→ Columns:
- Clicks
- Conversions
- CPA
- Conversion Rate
- Quality Score
- Impression Share
→ Filter: Min. 20 clicks (rule of thumb against random outliers, not statistical significance)
Analysis:
- Keywords with CPA >150% of goal: Pause
- Keywords with QS <5: Optimize or pause
- Keywords with IS <50% (budget): Increase budget
Report 3: Search Terms Report (critical!)
Setup:
Campaigns → Insights and reports → Search terms
→ Filter: Last 30 days
→ Sort by: Clicks (highest first)
Analysis:
- Irrelevant terms (e.g., "free", "used"): As negative keywords
- High performers (high CR, low CPA): Add as exact-match keywords
- Waste (many clicks, 0 conversions): Negative keywords
Do weekly! (top-priority report)
Report 4: Device Performance
Setup:
Reports → Device
→ Columns: Conversions, CPA, Conversion Rate
→ Time period: Last 30 days
Analysis:
Mobile: 1,000 clicks, 25 conv, €50 CPA
Desktop: 500 clicks, 30 conv, €40 CPA
Tablet: 100 clicks, 2 conv, €120 CPA
Action:
- Mobile: +20% bids (good performance)
- Desktop: +40% bids (best performance!)
- Tablet: -50% bids (poor performance)
Report 5: Location Performance
Setup:
Reports → Locations (Geo)
→ Columns: Conversions, CPA
→ Filter: Min. 10 conversions
Analysis:
Munich: 50 conv, €45 CPA ✅
Berlin: 35 conv, €60 CPA 😐
Hamburg: 20 conv, €90 CPA ⚠️
Rest: 15 conv, €120 CPA ❌
Action:
- Munich: +50% bids (scale!)
- Rest: -40% bids or exclude
Report 6: Time-Based Performance
Setup:
Reports → Time → Day of week
Reports → Time → Hour
→ Columns: Conversions, Conversion Rate, CPA
Analysis:
Day of week:
Mon-Fri: 80 conv, €50 CPA ✅
Sat-Sun: 15 conv, €95 CPA ❌
Hour (Mon-Fri):
09:00-18:00: 60 conv, €48 CPA ✅
18:00-23:00: 15 conv, €70 CPA 😐
23:00-09:00: 5 conv, €110 CPA ❌
Action:
- Mon-Fri 09-18: +40% bids
- Night: -60% bids or pause
Report 7: Audience Performance (remarketing)
Setup:
Reports → Audiences
→ Columns: Conversions, CPA, ROAS
Analysis:
Cart abandoners: 25 conv, €30 CPA, 900% ROAS ✅✅
Website visitors: 18 conv, €55 CPA, 520% ROAS ✅
Cold audience: 8 conv, €110 CPA, 180% ROAS ❌
Action:
- Cart abandoners: +200% bids (gold!)
- Cold audience: Reduce budget
Google Analytics 4 Integration
Why GA4 additionally?
- Google Ads: Campaign focus, attribution to keywords
- GA4: User journey focus, deeper insights, cross-device
Setup: Link GA4 + Google Ads
GA4 → Admin → Product Links → Google Ads Links
→ Link
→ Auto-tagging: ON
→ Then create Google Ads conversions from your GA4 key events
The Most Important GA4 Reports for Google Ads
1. Landing page performance:
GA4 → Reports → Engagement → Landing Pages
→ Filter: Source/Medium = "google / cpc"
→ Metrics:
- Sessions
- Engagement Rate
- Conversions
- Bounce Rate
Analysis: Which landing pages convert best?
→ More budget to these campaigns/keywords
2. User journey (path exploration):
GA4 → Explore → Path Exploration
→ Starting point: "google / cpc"
→ Shows: Which pages after Google Ads click?
Example:
google/cpc → Landing Page → Product page → Cart → Checkout
→ 60% drop after landing page (problem!)
→ Optimize landing page!
3. Conversion funnel:
GA4 → Explore → Funnel Exploration
→ Funnel:
1. Landing Page
2. Product page
3. Add to Cart
4. Checkout
5. Purchase
Analysis: Where do users drop?
→ Biggest drop = biggest optimization opportunity
4. Demographics (age/gender):
GA4 → Reports → User Attributes
→ Filter: google / cpc
→ Metrics: Conversions, Conv Rate
Example:
25-34 years: 45 conv, 4.5% CR ✅
55-64 years: 8 conv, 1.2% CR ❌
Action:
- Google Ads → Demographics → 25-34 years: +50% bids
5. Device & browser:
GA4 → Reports → Tech → Device
→ Deeper insights than Google Ads device report
Example:
iPhone: 3.5% CR
Android: 2.1% CR
→ iOS users convert better!
Attribution & Multi-Touch
Problem: Last-click attribution ignores customer journey!
Example real journey:
Day 1: Display ad → Website visited
Day 3: YouTube ad → Back to website
Day 7: Google Search "brand" → Purchase
Last-click: Search gets 100% credit
Reality: All 3 touchpoints important!
Attribution Models
Google Ads now offers only two attribution models: last click and data-driven. Google retired first click, linear, time decay and position-based in 2023 and switched the affected conversion actions to data-driven attribution. If you still see those models in older guides: you can no longer select them in Google Ads.
1. Data-driven (default, recommended):
Analyzes the actual conversion paths in your account
Assigns credit based on each touchpoint's measured influence
Default for most conversion actions
Data volume:
- Available for every conversion action, regardless of volume
- For better results Google recommends at least 200 conversions
and 2,000 ad interactions within 30 days
2. Last click:
Last clicked touchpoint = 100% credit
Problem: Ignores the journey before it
Use: Simple, easy-to-follow baseline for comparison
Setup Data-Driven Attribution
Google Ads → Goals → Summary
→ Click the conversion action → Edit settings
→ Attribution model: "Data-driven" → Save
Compare models: Goals → Attribution → Model comparison
Custom Dashboards (Data Studio / Looker Studio)
Why custom dashboards?
- All metrics at a glance
- CEO/CMO-friendly (not for ads experts)
- Automatic update (no manual reports!)
Dashboard 1: Executive Summary
KPIs:
[Time period: Last 30 days vs. previous 30 days]
1. Cost: €X,XXX (+/-X%)
2. Conversions: XXX (+/-X%)
3. Cost per Conversion: €XX (+/-X%)
4. ROAS: XXX% (+/-X%)
5. ROI: XXX% (+/-X%)
[Line Chart: Conversions over time]
[Pie Chart: Conversions by campaign]
Dashboard 2: Performance Deep-Dive
Sections:
1. Campaign Performance (Table)
- Columns: Campaign, Conversions, CPA, ROAS
2. Top Keywords (Table)
- Columns: Keyword, Conversions, CPA, QS
3. Device Performance (Bar Chart)
4. Geo Performance (Map + Table)
5. Hourly Performance (Heatmap)
Setup in Data Studio
Google renamed Looker Studio back to Data Studio in April 2026, so older guides still use the old name.
1. datastudio.google.com → Blank Report
2. Add data source: Google Ads
3. Select metrics & dimensions
4. Create charts (drag & drop)
5. Filters (date range, campaigns)
6. Share (view-only link for stakeholders)
Templates: Google offers pre-made templates (faster start!)
Data-Driven Optimization Decisions
Decision 1: Pause keyword?
Data needed:
- Enough data: my rule of thumb is min. 30 clicks, better spend of 1-2 target CPAs (that's still not statistical significance)
- CPA vs. target CPA
- Conversion rate vs. campaign average
Decision matrix:
CPA <Goal + CR >Average: ✅ Keep, increase bids!
CPA <Goal + CR <Average: 😐 Keep, observe
CPA >150% Goal: ❌ Pause (only once there's enough data, see above)
0 conversions after 50 clicks: ❌ Pause
Decision 2: Increase budget?
Data needed:
- ROAS vs. target ROAS
- Impression Share (Budget)
- Search Lost IS (budget)
Decision:
ROAS >Goal + IS <80% + Lost IS (budget) >20%:
→ ✅ Increase budget! (scale)
ROAS <Goal:
→ ❌ DON'T increase budget! (optimize first)
Budget underutilized (<80% spent):
→ Increase bids (NOT budget)
Decision 3: Switch bidding strategy?
Data needed:
- Conversions/month
- Conversion stability (not too volatile?)
- Current bidding strategy performance
Decision:
<30 conv/month: Manual or Maximize Conversions (without a target)
30-50 conv/month: Maximize Conversions, first tests with Target CPA
50+ conv/month: Target CPA or Target ROAS
100+ conv/month: Maximize Conversion Value
After switch: 4-6 weeks without major changes (learning phase)
The conversion thresholds and the 4-6 weeks are rules of thumb from my practice. Enhanced CPC (eCPC) used to be the usual intermediate step here, but Google retired eCPC for Search and Display campaigns in March 2025. Whether the new strategy really performs better is something you can measure under equal conditions with a Google Ads experiment before you apply it.
Common Analysis Mistakes
Mistake 1: Too early conclusions
❌ Problem: Keyword with 5 clicks, 0 conversions → pause ✅ Solution: Wait for more data. My rule of thumb: min. 30 clicks or spend of 1-2 target CPAs (that's still not statistical significance, just protection against judging on chance)
Mistake 2: Only look at last-click
❌ Problem: Display shows "bad" in last-click ✅ Reality: Display often assist (first touchpoint) ✅ Solution: Use data-driven attribution (the default in Google Ads) and check in model comparison how credit shifts versus last click
Mistake 3: Focus on vanity metrics
❌ Problem: "CTR is high → good!" ✅ Reality: CTR says nothing about profitability ✅ Solution: Focus on conversions, CPA, ROAS
Mistake 4: Too short time periods
❌ Problem: Judge performance after 3 days ✅ Solution: Min. 7-14 days (better: 30 days)
Mistake 5: No segmentation
❌ Problem: Only look at overall performance ✅ Solution: Segment by campaign, device, geo, time
Tools for Reporting & Analysis
Google native:
- Google Ads Reports (built-in, free)
- Google Analytics 4 (free)
- Data Studio, called Looker Studio until April 2026 (free)
Third-party:
- Supermetrics: Data export
- Optmyzr: Advanced reports
- AgencyAnalytics: White-label reports
Spreadsheets:
- Google Sheets with Google Ads add-on (free)
- Excel with Supermetrics
I deliberately don't list prices for third-party tools: they change constantly, so check the current terms directly with each provider.
Conclusion
Data-driven decisions = basis for Google Ads success
Weekly routine (setup):
Monday 9am (15 min):
- Overall performance check (conversions, CPA, ROAS)
- Campaign performance (identify top/bottom)
- Budget status (fully spent? underutilized?)
Wednesday 9am (30 min):
- Search terms review (add negative keywords!)
- Keyword performance (pause/optimize)
End of month (1-2h):
- Monthly deep dive (all reports)
- Strategy adjustments (budget shifts, new tests)
- Stakeholder report (Data Studio dashboard)
Most important metrics: Conversions, CPA, ROAS (not clicks/CTR!) They are only reliable with clean tracking, and that is exactly what I check in every Google Ads audit.
FAQ: Google Ads Reporting & Analysis
Which Google Ads metrics are most important?
Top 3 business metrics (most important!): 1) Conversions (number of purchases/leads), 2) Cost per Conversion / CPA (cost per conversion), 3) ROAS (Return on Ad Spend - revenue per €1 spend). Not: Clicks, CTR, impressions (vanity metrics!). Most common mistake: Focus on CTR/clicks instead of conversions/profitability. Rule of thumb: If metric doesn't directly correlate with profit → secondary! Focus: Conversions, CPA, ROAS.
How often should I check my Google Ads performance?
Recommended frequency: Daily (5 min): Quick check (conversions, cost - everything normal?). Weekly (30-60 min): Performance review (campaigns, keywords, search terms, budget). Monthly (2-3h): Deep dive (all reports, strategy adjustments, stakeholder report). NOT: Hourly (too frequent! Let AI work). NOT: Monthly only (too rare! Problems detected too late). Optimal: Weekly rhythm (Monday morning routine).
What is a good ROAS for Google Ads?
It depends mainly on your margin, blanket benchmarks won't help much. Calculate break-even ROAS: 1 / margin. Margin 40% → min. 250% ROAS (break-even). Margin 30% → 333%. Margin 20% → 500%. Below that, you lose money on every sale. A good ROAS sits above that value with a buffer that covers returns, fixed costs and profit. How big the buffer needs to be follows from your own numbers.
What's the difference between CPA and ROAS?
CPA (Cost per Acquisition) = cost per conversion (€X per lead/purchase). Best for: Lead-gen, all conversions equally valuable. Example: €50 CPA → each lead costs €50. ROAS (Return on Ad Spend) = revenue per €1 spend (%). Best for: E-commerce, different order values! Example: 400% ROAS → €1 spend brings €4 revenue. When what? Lead-gen / same conversion values → CPA. E-commerce / different values → ROAS.
How do I use Google Analytics 4 with Google Ads?
Setup: GA4 → Admin → Product Links → Google Ads → Link. Auto-tagging: ON, then create Google Ads conversions from your GA4 key events. Benefits: 1) Deeper user journey insights (which pages after click?), 2) Landing page performance (which LPs convert?), 3) Funnel analysis (where do users drop?), 4) Demographics (age, gender), 5) Cross-device tracking. Google Ads = campaign focus. GA4 = user focus. Both together = complete picture!
What is attribution and why is it important?
Attribution = credit distribution across touchpoints. Problem: Last-click ignores the journey. Example: User sees Display ad (day 1) → YouTube ad (day 3) → Google Search (day 7) → Purchase. Last-click: Search gets 100% credit. Data-driven attribution: credit based on each touchpoint's measured influence. Google Ads now only offers two models: last click and data-driven (Google retired first click, linear, time decay and position-based in 2023). Data-driven is the default for most conversion actions and available for every conversion action, regardless of volume. To change it: Goals → Summary → conversion action → Edit settings → Attribution model. Important for: Budget allocation (Display and YouTube often look weaker in last-click than they are).
Should I create custom dashboards?
YES! Why? 1) All metrics at a glance (instead of 10 reports), 2) Automatically updated (no manual copy-paste), 3) Stakeholder-friendly (CEO/CMO understand it), 4) Faster decisions. Tool: Data Studio (called Looker Studio until April 2026, free!). Setup: 5-10h initially, but saves hours/week afterward. Minimum: Executive dashboard (conversions, CPA, ROAS over time). Advanced: Performance deep dive (campaigns, keywords, geo, device). Templates: Google offers pre-made (faster start)!
How do I analyze which keywords I should pause?
Decision framework: 1) Wait for enough data (my rule of thumb: min. 30 clicks or spend of 1-2 target CPAs, which is still not statistical significance), 2) CPA check: Over 150% of target CPA → pause, 3) Conversion rate: 0 conv after 50+ clicks → pause, 4) Quality Score: QS 1-3 + high CPCs → pause. DON'T pause when: Few clicks (<30), seasonal keyword (outside season), high QS (7+) despite low volume. Important: Pause NOT delete (historical data!). Review monthly (reactivation possible).
