skills/yoanbernabeu/producthunt-skills/ph-conversion-tracking

ph-conversion-tracking

SKILL.md

Product Hunt Conversion Tracking

This skill helps you measure the real business impact of your Product Hunt launch through conversion tracking and ROI analysis.

When to Use This Skill

  • Setting up conversion measurement
  • Tracking launch day conversions
  • Analyzing funnel performance
  • Calculating launch ROI
  • Comparing to other acquisition channels

The Conversion Funnel

Standard PH Conversion Path

PRODUCT HUNT
    ├─── Impressions (people who see your listing)
    │         │
    │         ▼ [View Rate]
    ├─── Page Views (people who click)
    │         │
    │         ▼ [Click-through Rate]
    ├─── Website Visitors
    │         │
    │         ▼ [Engagement Rate]
    ├─── Engaged Visitors (>30s, 2+ pages)
    │         │
    │         ▼ [Signup Rate]
    ├─── Signups / Trials
    │         │
    │         ▼ [Activation Rate]
    ├─── Activated Users (reached value)
    │         │
    │         ▼ [Conversion Rate]
    └─── Paying Customers

Key Conversion Points

Stage Typical Rate What It Measures
View → Click 15-30% Listing appeal
Click → Visit 70-90% Page load, relevance
Visit → Signup 5-15% Landing page effectiveness
Signup → Activation 30-60% Onboarding quality
Activation → Paid 10-30% Product-market fit

Setting Up Conversion Tracking

1. Define Your Conversions

Primary Conversion (Pick One):

  • Signup completed
  • Trial started
  • Purchase made
  • App installed

Secondary Conversions:

  • Email collected
  • Demo booked
  • Free tier activated
  • Feature used

2. Technical Implementation

Google Analytics 4 Events:

// Signup conversion
gtag('event', 'generate_lead', {
  'event_category': 'signup',
  'event_label': 'producthunt',
  'value': 0
});

// Purchase conversion
gtag('event', 'purchase', {
  'transaction_id': 'T_12345',
  'value': 99.00,
  'currency': 'USD',
  'items': [{
    'item_name': 'Pro Plan',
    'price': 99.00
  }]
});

Server-Side Tracking:

# When signup occurs
def track_signup(user, source):
    analytics.track(user.id, 'Signed Up', {
        'source': source,  # 'producthunt'
        'plan': user.plan,
        'timestamp': datetime.now()
    })

3. Attribution Setup

First-Touch Attribution:

  • Capture source on first visit
  • Store in cookie/database
  • Associate with eventual conversion

UTM Tracking:

https://yoursite.com?utm_source=producthunt&utm_medium=launch&utm_campaign=jan2024

Referrer Tracking:

// Capture referrer on page load
if (document.referrer.includes('producthunt.com')) {
  localStorage.setItem('acquisition_source', 'producthunt');
}

Measuring Conversions

Real-Time Tracking (Launch Day)

Hourly Log Template:

Hour PH Visitors Signups Conv Rate Revenue
00:00 45 3 6.7% $0
01:00 89 7 7.9% $99
02:00 67 5 7.5% $0
...
Total

Conversion Rate Calculations

Visitor to Signup Rate:

Signup Rate = (Signups / PH Visitors) × 100

Example: 156 signups / 1,234 visitors = 12.6%

Trial to Paid Rate:

Conversion Rate = (Paid / Trials) × 100

Example: 23 paid / 156 trials = 14.7%

Revenue per Visitor:

RPV = Total Revenue / Total Visitors

Example: $2,277 / 1,234 = $1.85 per visitor

Funnel Analysis

Identifying Drop-Offs

Funnel Visualization:

PH Page Views:     2,500 (100%)
                      ▼ 49% continue
Website Visits:    1,234 (49%)
                      ▼ 38% continue
Engaged (>30s):      469 (19%)
                      ▼ 33% continue
Signup Started:      156 (6.2%)
                      ▼ 90% complete
Signup Done:         140 (5.6%)
                      ▼ 16% convert
Paid:                 23 (0.9%)

Drop-Off Analysis:

  • PH → Site: 51% drop → Is listing compelling?
  • Site → Engaged: 62% drop → Is landing page relevant?
  • Engaged → Signup: 67% drop → Is CTA clear?
  • Signup → Complete: 10% drop → Is form too long?
  • Complete → Paid: 84% drop → Is value delivered?

Optimization Opportunities

For each drop-off point:

  1. High Drop-Off? → Investigate why
  2. Identify Pattern → What's different about converters?
  3. Hypothesis → What change might help?
  4. Test → A/B test the change
  5. Measure → Did conversion improve?

ROI Calculation

Basic ROI Formula

Launch ROI = (Revenue Generated - Costs) / Costs × 100

Comprehensive ROI Analysis

Revenue Side:

Immediate Revenue:
- Direct purchases: $2,277

Projected Revenue (LTV-based):
- 23 customers × $480 LTV = $11,040

Total Value: $13,317

Cost Side:

Time Investment:
- Preparation: 40 hours × $100/hr = $4,000
- Launch day: 16 hours × $100/hr = $1,600
- Follow-up: 8 hours × $100/hr = $800

Direct Costs:
- Design assets: $500
- Tools/subscriptions: $100
- Promotional offer cost: $300

Total Costs: $7,300

ROI Calculation:

ROI = ($13,317 - $7,300) / $7,300 × 100 = 82.4%

Customer Acquisition Cost

CAC from PH = Total Launch Costs / Customers Acquired
            = $7,300 / 23
            = $317.39 per customer

Compare to Other Channels:

Channel CAC Quality
Product Hunt $317 High
Google Ads $150 Medium
Content Marketing $200 High
Cold Outreach $500 Low

Cohort Analysis

PH Users vs Other Sources

Track these metrics by acquisition source:

Metric PH Users Organic Paid Ads
Activation Rate 45% 38% 28%
Day 7 Retention 35% 32% 22%
Day 30 Retention 25% 24% 15%
Upgrade Rate 18% 12% 8%
Avg LTV $520 $380 $240

What This Tells You

  • PH users often higher quality
  • Worth the launch investment?
  • Should you launch again?

Benchmarks & Goals

Industry Benchmarks

B2B SaaS from PH:

Metric Low Average High
Visit → Trial 3% 8% 15%
Trial → Paid 10% 18% 30%
Launch Revenue $500 $3,000 $15,000+

Consumer Apps from PH:

Metric Low Average High
Visit → Signup 5% 15% 30%
Signup → Active 20% 40% 60%
Launch Downloads 200 1,000 5,000+

Setting Your Goals

PRE-LAUNCH CONVERSION GOALS

Visitors (from PH): [Target]
↓ [Target]% conversion
Signups: [Target]
↓ [Target]% conversion
Trials: [Target]
↓ [Target]% conversion
Paid: [Target]
↓ $[Avg Price]
Revenue: $[Target]

Post-Launch Conversion Analysis

Analysis Template

CONVERSION ANALYSIS: [Product Name]
Launch Date: [Date]

FUNNEL SUMMARY:
PH Views → Site: [X] ([Y]%)
Site → Signup: [X] ([Y]%)
Signup → Paid: [X] ([Y]%)

KEY METRICS:
Total PH Visitors: [X]
Total Signups: [X]
Signup Rate: [X]%
Total Paid: [X]
Conversion Rate: [X]%

REVENUE:
Immediate: $[X]
Projected LTV: $[X]
Total Value: $[X]

COSTS:
Time: $[X]
Direct: $[X]
Total: $[X]

ROI: [X]%
CAC: $[X]

COMPARED TO GOALS:
Visitors: [Actual] vs [Goal] ([Over/Under])
Signups: [Actual] vs [Goal] ([Over/Under])
Revenue: [Actual] vs [Goal] ([Over/Under])

INSIGHTS:
- [Key learning 1]
- [Key learning 2]
- [Key learning 3]

OPTIMIZATION PRIORITIES:
1. [Biggest drop-off to fix]
2. [Second priority]
3. [Third priority]

Conversion Tracking Checklist

Setup Phase

  • Primary conversion defined
  • Tracking code implemented
  • Attribution model set
  • Goals configured in analytics
  • Test conversions verified

Launch Day

  • Real-time tracking active
  • Hourly logging in progress
  • Conversion alerts working
  • No tracking issues

Post-Launch

  • All conversions captured
  • Funnel analyzed
  • ROI calculated
  • Cohort analysis done
  • Learnings documented

Output Format

CONVERSION REPORT: [Product Name]

EXECUTIVE SUMMARY:
Launch Date: [Date]
Total Visitors: [X]
Total Conversions: [X]
Conversion Rate: [X]%
Revenue: $[X]
ROI: [X]%

FUNNEL BREAKDOWN:
[Step 1] → [Step 2]: [X]%
[Step 2] → [Step 3]: [X]%
[Step 3] → [Step 4]: [X]%

BIGGEST DROP-OFF: [Step] ([X]% loss)
RECOMMENDATION: [Action to improve]

COMPARISON TO BENCHMARKS:
[Metric]: [Actual] vs [Benchmark] - [Status]

NEXT STEPS:
1. [Priority action]
2. [Secondary action]
3. [Tertiary action]
Weekly Installs
16
GitHub Stars
9
First Seen
Jan 24, 2026
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