K-Factor
Viral coefficient
Funnel
Conversion stages
A/B Testing
Optimize incentives
Cohorts
User segments
Calculating K-Factor
Sylphx automatically calculates your K-factor based on referral activity. Here's how to access and interpret the data.
Fetch K-factor metrics
import { platform } from '@/lib/platform'
// Get current K-factor and components
const viralMetrics = await platform.referrals.getViralMetrics({
period: 'last_30_days',
})
// Response:
{
kFactor: 0.42,
components: {
averageInvitesSent: 2.8, // i: users send 2.8 invites on average
inviteConversionRate: 0.15, // c: 15% of invites convert
},
trend: {
previous: 0.38,
change: 0.04,
changePercent: 10.5,
direction: 'up',
},
breakdown: {
byChannel: {
email: { invites: 1.2, conversion: 0.18 },
twitter: { invites: 0.8, conversion: 0.12 },
whatsapp: { invites: 0.5, conversion: 0.22 },
copy: { invites: 0.3, conversion: 0.08 },
},
byUserSegment: {
free: { kFactor: 0.28 },
premium: { kFactor: 0.65 },
},
},
projectedGrowth: {
usersIn30Days: 1250,
usersIn90Days: 3800,
timeToDouble: 45, // days
},
}K-Factor Over Time
Historical K-factor
// Track K-factor trends over time
const historicalK = await platform.referrals.getViralMetrics({
period: 'last_90_days',
granularity: 'week',
})
// Response:
{
series: [
{ date: '2024-01-01', kFactor: 0.35, invites: 2.4, conversion: 0.146 },
{ date: '2024-01-08', kFactor: 0.38, invites: 2.6, conversion: 0.146 },
{ date: '2024-01-15', kFactor: 0.42, invites: 2.8, conversion: 0.150 },
{ date: '2024-01-22', kFactor: 0.45, invites: 3.0, conversion: 0.150 },
// ...
],
insights: [
{
type: 'improvement',
metric: 'invites_sent',
change: '+25%',
cause: 'New share button placement',
},
{
type: 'opportunity',
metric: 'conversion_rate',
suggestion: 'Test higher referee reward to improve conversion',
},
],
}Referral Funnel Stages
Understand where users drop off in the referral process to optimize each stage.
Referral Link Views
Users who see their referral link
10,000
100%
Shares Initiated
Users who click a share button
2,800
28%
Link Clicks
Referred users who click the link
1,500
15%
Signups
Referred users who create an account
450
4.5%
Conversions
Referred users who convert to paid
180
1.8%
Fetch funnel data
const funnel = await platform.referrals.getFunnel({
period: 'last_30_days',
})
// Response:
{
stages: [
{
name: 'link_views',
count: 10000,
rate: 1.0,
dropoff: 0.72, // 72% don't share
},
{
name: 'shares_initiated',
count: 2800,
rate: 0.28,
dropoff: 0.46,
byChannel: {
copy: 1200,
email: 800,
twitter: 500,
whatsapp: 300,
},
},
{
name: 'link_clicks',
count: 1500,
rate: 0.15,
dropoff: 0.70,
},
{
name: 'signups',
count: 450,
rate: 0.045,
dropoff: 0.60,
},
{
name: 'conversions',
count: 180,
rate: 0.018,
dropoff: 0,
},
],
bottleneck: {
stage: 'link_views_to_shares',
dropoff: 0.72,
recommendation: 'Improve share prompt visibility and incentive messaging',
},
}Conversion Rate Optimization
Identify and fix bottlenecks in your referral funnel with data-driven optimization.
Key Metrics to Track
| Property | Type | Description |
|---|---|---|
Share Rate | percentage | Users who share their referral link (aim for >20%) |
Click-through Rate | percentage | Share recipients who click (aim for >30%) |
Signup Rate | percentage | Clicks that become signups (aim for >25%) |
Conversion Rate | percentage | Signups that convert to paid (aim for >30%) |
Time to Convert | days | Average days from click to conversion |
Optimization Strategies by Stage
// Problem: Low share rate (users don't share their link)
// Solutions:
// 1. Make referral link more visible
// 2. Add share prompts at key moments
// 3. Show social proof (other users' success)
// 4. Improve reward messaging
// Track share prompt effectiveness
const sharePromptMetrics = await platform.referrals.getMetrics({
metric: 'share_prompt_conversion',
groupBy: 'prompt_location',
})
// {
// onboarding_complete: { shown: 5000, shared: 1200, rate: 0.24 },
// settings_page: { shown: 8000, shared: 400, rate: 0.05 },
// after_upgrade: { shown: 1000, shared: 350, rate: 0.35 }, // Best!
// sidebar_widget: { shown: 50000, shared: 1000, rate: 0.02 },
// }
// Insight: Prompt after upgrade has highest conversionA/B Testing Referral Incentives
Test different reward structures to find what drives the most referrals and conversions.
Create an experiment
// Create a referral reward experiment
const experiment = await platform.referrals.createExperiment({
name: 'reward_value_test',
description: 'Test different reward amounts',
variants: [
{
name: 'control',
weight: 0.33,
config: {
referrerReward: { type: 'points', amount: 500 },
refereeReward: { type: 'discount', amount: 10 },
},
},
{
name: 'higher_referrer',
weight: 0.33,
config: {
referrerReward: { type: 'points', amount: 1000 }, // 2x
refereeReward: { type: 'discount', amount: 10 },
},
},
{
name: 'higher_referee',
weight: 0.34,
config: {
referrerReward: { type: 'points', amount: 500 },
refereeReward: { type: 'discount', amount: 20 }, // 2x
},
},
],
metrics: ['shares', 'signups', 'conversions', 'ltv'],
minimumSampleSize: 1000,
confidenceLevel: 0.95,
})
// Check experiment results
const results = await platform.referrals.getExperimentResults({
experimentId: experiment.id,
})
// Response:
{
status: 'completed',
winner: 'higher_referee',
confidence: 0.97,
results: {
control: {
users: 1050,
shares: 294, // 28%
signups: 126, // 12%
conversions: 38, // 3.6%
avgLTV: 89,
},
higher_referrer: {
users: 1020,
shares: 357, // 35% (+25%)
signups: 143, // 14%
conversions: 41, // 4.0%
avgLTV: 85,
},
higher_referee: {
users: 1030,
shares: 309, // 30%
signups: 185, // 18% (+50%) Winner!
conversions: 59, // 5.7%
avgLTV: 92,
},
},
recommendation: 'Higher referee reward drives more signups without hurting LTV',
}Test One Variable at a Time
For clear results, only change one variable per experiment. Test reward amount separately from reward type, and referrer rewards separately from referee rewards.
Common Tests to Run
Reward Amount
Find the optimal reward value that maximizes referrals vs. cost
Reward Type
Compare cash/credits, discounts, free months, and feature unlocks
Two-sided vs One-sided
Test rewarding both parties vs. only referrer or referee
Timing
Immediate rewards vs. delayed (after conversion/verification)
Identifying Top Referrers
Find and nurture your most valuable referrers - they often drive a disproportionate share of growth.
Top referrers analysis
// Get top referrers by various metrics
const topReferrers = await platform.referrals.getTopReferrers({
period: 'last_90_days',
limit: 100,
sortBy: 'conversions', // or 'signups', 'ltv_generated', 'revenue'
})
// Response:
{
referrers: [
{
userId: 'user_123',
name: 'Alice Chen',
email: 'alice@example.com',
metrics: {
shares: 156,
clicks: 420,
signups: 85,
conversions: 32,
ltvGenerated: 2880,
rewardsEarned: 320,
},
rank: 1,
percentile: 99.5,
segment: 'power_referrer', // Top 1%
},
{
userId: 'user_456',
name: 'Bob Smith',
metrics: {
shares: 89,
clicks: 245,
signups: 52,
conversions: 21,
ltvGenerated: 1890,
rewardsEarned: 210,
},
rank: 2,
percentile: 99.0,
segment: 'power_referrer',
},
// ...
],
distribution: {
top1Percent: { users: 10, referrals: 340, share: 0.42 }, // 42% of referrals
top10Percent: { users: 100, referrals: 580, share: 0.72 }, // 72% of referrals
remaining: { users: 900, referrals: 230, share: 0.28 },
},
insights: [
{
type: 'concentration',
message: 'Top 1% of referrers drive 42% of all referrals',
},
{
type: 'opportunity',
message: '230 users have shared but 0 conversions - consider nurturing',
},
],
}Referrer Segments
Power Referrers
Top 1% by conversions
VIP treatment, exclusive rewards, early access
Active Referrers
Top 10% by conversions
Bonus rewards, personalized thank-yous
Emerging Referrers
Recent first successful referral
Encouragement, tips to refer more
Dormant Referrers
Past referrals, inactive >30 days
Re-engagement campaigns, new incentives
Automated segmentation
// Automatically segment and engage referrers
await platform.referrals.configureSegments({
segments: [
{
name: 'power_referrer',
criteria: { conversions: { gte: 10 }, period: '90d' },
actions: [
{ type: 'tag', tag: 'vip' },
{ type: 'email', template: 'power_referrer_thanks' },
{ type: 'reward_multiplier', multiplier: 1.5 },
],
},
{
name: 'emerging_referrer',
criteria: { conversions: { gte: 1, lte: 3 }, period: '30d' },
actions: [
{ type: 'email', template: 'referral_tips' },
],
},
{
name: 'dormant_referrer',
criteria: {
totalConversions: { gte: 1 },
lastReferral: { daysAgo: { gte: 30 } },
},
actions: [
{ type: 'email', template: 'referral_reengagement' },
{ type: 'offer', reward: { type: 'points', amount: 200 } },
],
},
],
})Cohort Analysis
Analyze how referral behavior and quality varies across user cohorts over time.
Cohort analysis
// Analyze referral behavior by signup cohort
const cohortAnalysis = await platform.referrals.getCohortAnalysis({
cohortBy: 'signup_month',
metrics: ['referral_rate', 'avg_referrals', 'referral_ltv'],
period: 'last_12_months',
})
// Response:
{
cohorts: [
{
cohort: '2024-01',
users: 1200,
metrics: {
referralRate: 0.15, // 15% made at least 1 referral
avgReferrals: 0.45, // Average referrals per user
referralLTV: 125, // LTV of users they referred
timeToFirstReferral: 12, // Days after signup
},
},
{
cohort: '2024-02',
users: 1350,
metrics: {
referralRate: 0.18, // Improved!
avgReferrals: 0.52,
referralLTV: 132,
timeToFirstReferral: 10,
},
},
// ...
],
insights: [
{
type: 'trend',
message: 'Referral rate improving month-over-month (+20% since Jan)',
},
{
type: 'quality',
message: 'Q1 referrals have 15% higher LTV than Q4 referrals',
},
],
}
// Compare referred vs non-referred user cohorts
const referredCohorts = await platform.referrals.getCohortAnalysis({
cohortBy: 'acquisition_source', // 'referred' vs 'organic' vs 'paid'
metrics: ['retention_d30', 'conversion_rate', 'ltv'],
})
// {
// cohorts: [
// {
// cohort: 'referred',
// users: 2500,
// metrics: {
// retentionD30: 0.65, // 65% still active after 30 days
// conversionRate: 0.32, // 32% converted to paid
// ltv: 145,
// },
// },
// {
// cohort: 'organic',
// users: 8000,
// metrics: {
// retentionD30: 0.52, // Referred users retain better
// conversionRate: 0.24,
// ltv: 112,
// },
// },
// {
// cohort: 'paid_ads',
// users: 5000,
// metrics: {
// retentionD30: 0.45,
// conversionRate: 0.18,
// ltv: 95,
// },
// },
// ],
// }
// Insight: Referred users have 25% better retention and 29% higher LTVReferred User Quality
Referred users typically have higher retention, conversion rates, and LTV than users from other channels. Use this data to justify investment in your referral program.
Dashboard & Reports
Access all referral analytics through the Sylphx dashboard or export reports.
Generate reports
// Generate a comprehensive referral report
const report = await platform.referrals.generateReport({
period: 'last_30_days',
sections: [
'overview',
'k_factor',
'funnel',
'top_referrers',
'cohort_analysis',
'experiment_results',
],
format: 'pdf', // or 'csv', 'json'
})
// Schedule recurring reports
await platform.referrals.scheduleReport({
name: 'Weekly Referral Summary',
frequency: 'weekly',
dayOfWeek: 'monday',
recipients: ['team@company.com'],
sections: ['overview', 'k_factor', 'top_referrers'],
})
// Real-time metrics for dashboards
const realtime = await platform.referrals.getRealtimeMetrics()
// {
// today: {
// shares: 145,
// clicks: 89,
// signups: 23,
// conversions: 8,
// },
// activeReferrers: 42, // Currently sharing
// pendingRewards: 15, // Awaiting fulfillment
// }Ready to build your referral program?
Explore the full API reference for all referral endpoints, or check out the pre-built components.