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Overview

The CTAAnalyzer class analyzes Call-to-Action (CTA) elements in landing pages, evaluating quality, placement distribution, and alignment with conversion goals.

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Installation

from data_sources.modules.cta_analyzer import CTAAnalyzer, analyze_ctas

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Initialization

analyzer = CTAAnalyzer(conversion_goal='trial')
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conversion_goal
str
default:"trial"
Conversion goal: ‘trial’, ‘demo’, or ‘lead’

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Methods

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analyze

Analyze CTAs in landing page content. 
result = analyzer.analyze(content)
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content
str
required
Landing page content (markdown)
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result
dict
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summary
dict
High-level metrics
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total_ctas
int
Total number of CTAs found
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average_quality_score
float
Average quality score (0-100)
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distribution_score
float
Distribution score (0-100)
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goal_alignment_score
float
Goal alignment score (0-100)
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overall_effectiveness
float
Weighted overall score (0-100)
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ctas
list
Individual CTAs with quality scores
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distribution
dict
CTA placement analysis
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goal_alignment
dict
Goal alignment details
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recommendations
list
Prioritized recommendations

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CTA Quality Scoring

Each CTA is scored (0-100) based on:

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Action Verb Strength (+5 to +30)

  • Strongest (+30): start, get, claim, unlock, discover
  • Strong (+25): try, begin, launch, create, download, book, schedule
  • Moderate (+15): learn, see, find, explore, read, watch
  • Weak (+5): submit, click, enter, continue, next
  • None (-10): No clear action verb

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Benefit Words (+10 to +15)

  • free, instant, immediate, today, now
  • unlimited, exclusive, premium, full
  • easy, fast, quick, simple

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Urgency (+10)

  • now, today, immediately, instant
  • limited, hurry, soon, before
  • don’t miss, last chance, expires, only

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Specificity (+10)

  • Numbers: “14-day trial”, “30-day guarantee”
  • Amounts: “$100 off”, “50% discount”
  • Time: “in 5 minutes”, “instant access”
  • No requirements: “no credit card”, “no commitment”

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Length Optimization

  • Optimal (+5): 2-5 words
  • Too long (-10): 8+ words

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Format Bonus (+5)

  • Button-style CTAs: [Text], **[Text]**, [Text →]

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CTA Distribution

CTAs should be distributed throughout the page:
  • Above the fold (first 20%): Essential
  • Mid-page (30-70%): Recommended
  • Closing (last 20%): Recommended
Distribution quality:
  • Excellent: CTAs in all three zones
  • Good: CTAs in two zones
  • Poor: CTAs in one zone
  • None: No CTAs found

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Goal Alignment

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Trial Goal Patterns

Primary:
  • “start your free trial”
  • “try free for 14 days”
  • “get started free”
Secondary:
  • “sign up free”
  • “create account”
  • “launch your [product]“

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Demo Goal Patterns

Primary:
  • “book a demo”
  • “get a demo”
  • “see it in action”
Secondary:
  • “schedule a call”
  • “talk to sales”
  • “contact us”

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Lead Goal Patterns

Primary:
  • “download the guide”
  • “get instant access”
  • “claim your free [asset]”
Secondary:
  • “subscribe”
  • “join newsletter”
  • “get updates”

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Recommendations

The analyzer generates prioritized recommendations:

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High Priority

  • Missing CTA above the fold
  • No closing CTA
  • CTAs don’t align with conversion goal

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Medium Priority

  • Too few CTAs (< 3 for SEO, < 2 for PPC)
  • Low quality CTAs (score < 60)
  • Poor action verbs

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Low Priority

  • Consider adding more goal-specific language
  • Add benefit words to CTAs
  • Improve CTA placement

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Convenience Function

from data_sources.modules.cta_analyzer import analyze_ctas

result = analyze_ctas(
    content=page_content,
    conversion_goal='trial'
)

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Example Usage

from data_sources.modules.cta_analyzer import CTAAnalyzer

# Read landing page
with open('landing-pages/podcast-hosting.md', 'r') as f:
    content = f.read()

# Analyze CTAs
analyzer = CTAAnalyzer(conversion_goal='trial')
result = analyzer.analyze(content)

print("=== CTA Analysis Report ===")
print(f"\nSummary:")
print(f"  Total CTAs: {result['summary']['total_ctas']}")
print(f"  Average Quality: {result['summary']['average_quality_score']}/100")
print(f"  Distribution Score: {result['summary']['distribution_score']}/100")
print(f"  Goal Alignment: {result['summary']['goal_alignment_score']}/100")
print(f"  Overall Effectiveness: {result['summary']['overall_effectiveness']}/100")

print(f"\nCTAs Found:")
for cta in result['ctas']:
    print(f"  [{cta['position_pct']:.0f}%] \"{cta['text']}\" (Score: {cta['quality_score']})")
    if cta.get('scoring_factors'):
        for factor in cta['scoring_factors'][:3]:
            print(f"    {factor}")

print(f"\nDistribution: {result['distribution']['distribution_quality']}")
for issue in result['distribution']['issues']:
    print(f"  ⚠️  {issue}")

print(f"\nGoal Alignment ({result['goal_alignment']['goal']}):")
print(f"  Primary matches: {result['goal_alignment']['primary_matches']}")
print(f"  Secondary matches: {result['goal_alignment']['secondary_matches']}")

if result['recommendations']:
    print(f"\nTop Recommendations:")
    for rec in result['recommendations'][:3]:
        print(f"  [{rec['priority'].upper()}] {rec['recommendation']}")

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Example CTA Scoring

# Excellent CTA (Score: 95)
"[Start Your Free Trial Today →]"  
# +30 (strongest verb: start)
# +15 (benefit words: free, today)
# +10 (urgency: today)
# +10 (specificity implied)
# +5 (optimal length: 5 words)
# +5 (button format)
# Total: 75 base + bonuses = 95

# Good CTA (Score: 75)
"[Try Free for 14 Days]"
# +25 (strong verb: try)
# +15 (benefit words: free)
# +10 (specificity: 14 days)
# +5 (optimal length: 5 words)
# +5 (button format)
# Total: 60 base + bonuses = 75

# Weak CTA (Score: 45)
"[Submit]"
# +5 (weak verb: submit)
# -10 (too short, no context)
# Total: 45

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Source Code Reference

Location: data_sources/modules/cta_analyzer.py:16 See also:

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