ph-conversion-tracking

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]