How to Build Recurring Revenue With a Dating Membership Site

Understanding Recurring Revenue Metrics

Before building your subscription model, understand the metrics that matter.

Key Recurring Revenue Metrics

MRR (Monthly Recurring Revenue) Total revenue from all active subscriptions in a given month.

Example: 1,000 paying users x $12/month = $12,000 MRR

This is your primary metric. Track it weekly. It tells you if you're growing or dying.

ARR (Annual Recurring Revenue) MRR x 12. This is easier to think about for annual reports.

1,000 users x $12/month x 12 = $144,000 ARR

Churn Rate (Monthly) The percentage of subscribers who cancel each month.

Formula: (Subscribers lost this month) / (Subscribers at start of month)

Example: 50 cancellations / 1,000 subscribers = 5% churn

5% churn is the breakeven for most SaaS. Below 3% is excellent. Above 8% means your product isn't sticky.

Retention Cohort Analysis What percentage of users who sign up in Month 1 are still paying in Month 2, 3, 6, 12?

Example:

• Month 0 (signup): 1,000 subscribers
• Month 1: 950 (95% retention)
• Month 3: 880 (88% retention)
• Month 6: 800 (80% retention)
• Month 12: 700 (70% retention)

This tells you if products are getting better or worse. If Month 6 retention is 80% in 2024 but 75% in 2025, your product is degrading.

LTV (Lifetime Value) Total profit you'll earn from a subscriber before they churn.

Formula: (Average MRR per user) / (Monthly churn rate)

Example: $12/month / 0.05 (5% churn) = $240 LTV

This means each new user is worth $240 in profit (before acquisition cost).

CAC (Customer Acquisition Cost) Total marketing spend divided by new customers acquired.

Formula: Marketing spend / New subscribers

Example: $5,000 spend / 250 new subscribers = $20 CAC

Your LTV needs to be 3x your CAC to be healthy. If LTV is $240 and CAC is $20, you're doing great.

Payback Period How many months until you recoup the cost to acquire a customer.

Formula: CAC / (Monthly profit per customer)

Example: $20 CAC / $10 profit per customer = 2 months

Healthy payback is less than 6 months. Less than 3 months is excellent.

Tracking These Metrics

Use a simple spreadsheet or analytics tool. Update weekly.

Churn is going up and LTV is going down. This is bad. Investigate before it gets worse.

Building Your Subscription Model

The 3-Part Decision Framework

1. What are you selling?

• Access to platform (matching, messaging)
• Features (boosts, advanced search, verification)
• Safety/trust (verified members, offline verification)
• Experiences (events, travel trips)

2. Who is the customer?

• Everyone (mainstream positioning)
• Niche (high-net-worth, specific age, specific community)
• Power users (high-engagement users)

3. What are they willing to pay?

• Research competitor pricing
• Survey your users
• Test different prices with ads

The Simplest Model

Start with this. Add complexity later.

This is it. Two tiers. Free with friction, premium with features.

Why this works:

• Free tier acquires users at zero cost (no paywall friction)
• Premium tier is obvious (3 messages is clearly not enough)
• Pricing is standard (most dating apps price at $9.99)
• Maintenance is simple (two tiers = less confusion)

Adding Complexity Gradually

At 5,000 paying users, consider adding a premium tier:

At 20,000 paying users, consider adding annual billing and bundles:

Don't launch with 5 tiers. You'll confuse yourself and users. Start with 2, add complexity as revenue justifies.

Freemium vs Premium-Only

Freemium Model

Users download for free, try the product, upgrade if they like it.

Pros:

• Largest addressable market (free users = volume)
• Lower friction to first user
• Network effects (more free users = more potential matches)
• Natural funnel (free trial leads to conversions)
• Better analytics (you see user behavior before they pay)

Cons:

• Lower conversion rates (2-8% of free users pay)
• Higher CAC (need to acquire free users who never convert)
• Server costs increase (free users are expensive)

When to use: Mainstream platforms, broad-market apps, platforms where network effects matter (dating is this)

Premium-Only Model

No free tier. 7-14 day trial, then paywall.

Pros:

• Higher conversion rate (5-15% of trial users convert)
• Better unit economics (high ARPU, no free-user overhead)
• Cleaner product (no need to restrict features)
• Attracts high-intent users (willingness to pay signals seriousness)

Cons:

• Smaller total addressable market (fewer people will try)
• Network effects suffer (fewer users = fewer matches)
• Higher churn (easy to cancel during trial)
• Analytics blindness (hard to see user behavior before trial ends)

When to use: Niche platforms (high-net-worth dating), premium positioning, communities with strong intent

The Hybrid Model

Free tier + optional paid tier + trial upsell. Used by some platforms, rarely optimal.

Usually results in: free users cannibalize paid, premium users feel resentful, confusing messaging.

Recommendation: Pick freemium or premium-only. Don't try to do both.

Subscription Tier Architecture

How to Price Each Tier

The goal is to make people self-segment. Low willingness-to-pay goes to basic tier. High willingness-to-pay goes to premium.

!Key concept for article 20 *Visual breakdown of how to build recurring revenue with a dating membership site*

Why 80/20 split? Experience shows:

• 80% of users are price-sensitive or unsure if premium is worth it
• 20% are power users or have high intent

If your split is 95/5, basic tier isn't valuable enough. Move features from premium to basic.

If your split is 50/50, basic tier has too many features. Move features to premium.

Pricing Anchoring

Psychology matters. Users judge price relative to the tier above.

Bad approach:

• Basic: $4.99
• Premium: $19.99

Users think: "Why would I pay 4x more for a few extra features?"

Good approach:

• Basic: $9.99
• Premium: $19.99

Users think: "Premium is just double, and it has much more value. Reasonable."

Best approach:

• Basic: $9.99
• Premium: $19.99
• Elite: $29.99

Users think: "Premium is a good value between Basic and Elite. I'll go Premium."

The top tier anchors users to the middle tier. This is standard in SaaS pricing.

Grandfathering vs Price Changes

When you raise prices, what do you do with existing subscribers?

Grandfathering (keep old price for existing users):

• Good for customer loyalty
• Bad for revenue (new users pay more than old users for same service)
• Creates awkward cohorts (new user pays $12.99, old user pays $9.99)

Migration (move existing users to new tier immediately):

• Good for revenue
• Bad for loyalty (feels like a betrayal)
• Churn increases 5-15%

Compromise (raise price at next renewal):

• Existing users keep old price until subscription renews
• New subscribers pay new price
• After 12 months, old users see new price at renewal

Use the compromise approach. It's fair to users and protects revenue.

Monthly vs Annual Strategy

Why Annual Matters

Annual subscribers have higher LTV (they're locked in for 12 months). They also have lower churn (annual churn is 10-20% vs monthly churn is 3-8% per month).

Example:

• Monthly subscriber: 12 months x (1 - 0.05 churn)^12 = 5.5 months average tenure
• Annual subscriber: 12 months 90% of the time (some don't renew)

Monthly users churn out faster. Annual users stay longer.

Pricing Annual Subscriptions

Standard discount: 30-40%

Example:

• Monthly: $9.99
• Annual: $99.99 (vs $119.88 if monthly x 12)
• Discount: 16% (save $19.89)

This works. But many SaaS companies go aggressive:

Example:

• Monthly: $9.99
• Annual: $79.99
• Discount: 33% (save $40)

Aggressive discounts drive annual penetration (40-50% of users choose annual). But be careful. If your CAC is high, aggressive annual discounts hurt economics.

Promoting Annual

Show savings explicitly. Instead of: "$9.99/month or $99.99/year"

Show: "$9.99/month or $99.99/year (Save $20!)"

Or better, show effective monthly price: "$9.99/month or $8.33/month when you choose annual"

This makes annual feel like a better deal (which it is for users who stay).

Buyer Psychology

Research shows that people decide between monthly and annual based on:

• Confidence in the product (not sure = monthly; sure = annual)
• Available cash (monthly for people with tight cashflow)
• Intention length (planning to stay long = annual)

Recommendation: Default to monthly at signup. Offer annual as an upgrade after 30 days (once they're confident).

Managing Churn and Retention

Churn is the killer of recurring revenue. A 5% monthly churn rate means half your cohort is gone in 14 months.

Why Users Cancel

Run a survey when users cancel. Ask "why did you cancel?"

Typical reasons:

1. Found a partner / no longer dating (40%)
2. Features don't match my needs (20%)
3. Too expensive (15%)
4. No good matches in my area (10%)
5. App has a bug / poor experience (10%)
6. Took a break from dating (5%)

You can't fix #1 (that's success). You can fix #2-6.

The Churn Funnel

Track where users are most likely to churn:

Most churn happens in first 3 months (30% loss). If you can get users to Month 3 sticky, they're likely to stay.

Tactics to Reduce Churn

Win-back emails (pre-cancellation)

When you detect low engagement (no logins in 7 days), send an email: "Hey Sarah, we haven't seen you in a week. Here are 5 new matches in your area. [Click to see matches]"

Expected impact: 5-10% reduction in churn

Pause instead of cancel

Instead of cancellation, offer 3-month pause: "Take a break from dating for 3 months. Your subscription pauses. Come back anytime."

Expected impact: 20-30% of would-be cancelers choose pause instead. 40% return within 3 months.

Discount retention offers

When user tries to cancel, offer discount: "Would you stay for 2 months at 50% off ($5)?"

Expected impact: 10-20% of would-be cancelers accept offer

Re-engagement campaigns

Send "we miss you" emails monthly to inactive users: "It's been 2 weeks. Here are 10 new matches."

Expected impact: 3-5% of inactive users log back in

Product improvements

If churn reason is "no good matches," fix matching. If it's "too many fakes," add verification.

Expected impact: Large (depends on what's broken)

Retention vs Acquisition

Early on, focus on acquisition (growth). Once retention is sub-5% monthly churn, focus on retention.

At 1,000 users with 5% churn:

• Acquiring 100 new users maintains growth
• Reducing churn to 3% requires less acquisition (60 new users needed)

Retention is cheaper than acquisition.

Billing and Payment Processing

Payment Processors

!Payment Processors data breakdown for How to Build Recurring Revenue With a Dating *Detailed breakdown of the data presented above*

Use Stripe as primary. Apple and Google are required for app stores (they take 30%, so in-app is expensive).

Billing Cadence

• Monthly subscription: Bills on day 1 of month, every month
• Annual subscription: Bills on anniversary date

Track failed payments. Stripe will retry 3 times over 3 days. If still fails, mark user as delinquent.

Delinquent users: Send email, offer to update payment method. After 30 days, cancel subscription.

Handling Payment Failures

10-15% of payments fail (expired card, moved, account closed).

Have a retry logic:

1. Payment fails
2. Day 1: Retry payment
3. Day 3: Retry payment
4. Day 5: Retry payment
5. Send email asking to update payment method
6. Day 10: Email asking to update
7. Day 15: Cancel subscription (unless payment updated)

This catches 80% of failures (usually the user just needs to update card).

Fraud Prevention

Dating apps attract fraud (fake accounts, chargeback fraud, etc.).

Use a fraud detection service (Stripe Radar is built-in).

Flag:

• Signups with VPN
• Multiple signups from same card/IP
• High chargeback rate

Don't over-block (false positives hurt good users), but do block obvious fraud.

Communicating Value to Users

Users won't upgrade if they don't understand the value.

The Paywall

When free user hits a limit (3 messages sent), show a paywall:

"You've sent 3 messages. Unlimited messaging with premium:"

Good paywalls show:

1. What they're missing (you can't send more messages)
2. What they'll gain (unlimited messages)
3. How much (price)
4. Social proof (1,000+ members upgraded)

Bad paywalls:

• Don't show what they're missing
• Use jargon
• Ask for payment without context

Feature Comparison

Show a comparison table of features:

Make clear which features matter. "Unlimited messaging" is worth $9.99. "Advanced search" might not be.

Onboarding

Best time to educate users about premium is during onboarding, not after they're frustrated.

In onboarding, show: "You get 3 free messages to explore. Upgrade to unlimited messaging and get better matches."

This frames the limit as a tryout, not a wall.

In-App Messaging

Use in-app banners to promote premium:

• "Top 10% of users have unlimited messaging. Upgrade?"
• "See who liked you with premium"
• "2,000 active members using premium in your area"

Keep messaging light. One banner per session, not 5.

Optimizing for LTV and Unit Economics

The Equation

Revenue = Users x ARPU x Months subscribed Profit = Revenue - Costs

Your goal: maximize profit, not users or revenue.

Example:

• 1,000 users x $12 ARPU x 8 months = $96,000
• 500 users x $20 ARPU x 20 months = $200,000

Same users and timeframe, but wildly different revenue because of ARPU and churn.

Levers to Improve Unit Economics

1. Increase ARPU (Average Revenue Per User)

• Add higher-priced tiers
• Upsell annual subscriptions (higher LTV)
• Add à la carte features (boosts, verification)
• Raise prices for new cohorts

Expected impact: 10-30% ARPU increase

2. Decrease churn

• Improve product quality
• Better onboarding
• Engagement campaigns
• Retention discounts

Expected impact: 1-3 percentage point churn reduction

3. Improve CAC (Customer Acquisition Cost)

• Organic growth (word-of-mouth, SEO)
• Efficient paid channels
• Referral programs
• Partnership channels

Expected impact: 20-50% CAC decrease

The Trade-off

Raising price improves ARPU but may increase churn. Adding features improves retention but costs money.

Balance them. A 10% price increase and 1% churn increase might be a net positive if price increase is 10% and churn increase is 1%.

Example:

• Current: 1,000 users x $12 x 12 months = $144,000 ARR
• Raise price to $13.20 (+10%), churn increases 1% (from 5% to 6%)
• New: 1,000 users x $13.20 x 10 months = $132,000 ARR

In this case, the price increase isn't worth the churn increase.

But if price increase is 10% and churn only increases 0.5%:

• Current: 1,000 users x $12 x 12 months = $144,000 ARR
• New: 1,000 users x $13.20 x 11.5 months = $151,800 ARR

This is worth it.

Cohort Analysis

Track cohorts by acquisition month:

March cohort has better LTV than January. Why? Investigate:

• Better product (you fixed bugs)
• Better onboarding (users understood value)
• Better pricing (you raised prices)
• Better acquisition (more committed users)

Use this insight to improve all future cohorts.

Common Mistakes

Mistake 1: Launching With Too Many Tiers

5-tier pricing paralyzes users. They don't know which to pick.

Start with 2 tiers. Add a third at 10,000 paying users. Stop at 3.

Mistake 2: Not Communicating Value

Users don't upgrade because they don't understand what they're missing.

Show the limit in context ("You've sent 3 messages") and the benefit ("Unlimited with premium").

Mistake 3: Raising Price Too Aggressively

Going from $9.99 to $24.99 will tank conversion.

Raise in small increments ($9.99 -> $11.99 -> $13.99). Test each step.

Mistake 4: Ignoring Annual Strategy

Monthly users churn faster. Annual users stay longer.

Push annual hard. Offer 30-40% discount. Make it the default (optional monthly if they prefer).

Mistake 5: Not Tracking Retention

You could be losing 10% of users per month and not notice for 3 months (revenue is flat because new users offset churn).

Track retention weekly. Know your churn rate.

Mistake 6: Optimizing for MAU Instead of Paying Users

"We have 100,000 MAU!" Sounds great. "We have 2,000 paying users" is the real metric.

Focus on paying users. MAU is vanity.

Key Takeaways

• Recurring revenue is built on two foundations: a product people want to keep using (low churn) and pricing they're willing to pay (high ARPU).
• Start with 2 tiers: free with friction, premium with unlimited features. Don't overcomplicate.
• Freemium is best for mainstream dating apps. Premium-only works only for niche/premium platforms.
• Monthly churn of 3-5% is healthy. Track it weekly. If it's increasing, investigate and fix.
• Annual subscriptions have 2-3x higher LTV than monthly. Push annual with 30-40% discounts.
• Paywall users in context. "You've sent 3 messages. Unlimited messaging costs $9.99/month."
• LTV needs to be 3x CAC for healthy unit economics. If it's not, either increase ARPU, decrease churn, or decrease CAC.
• Retention is cheaper than acquisition. Focus on retention once product is solid.
• Track cohorts. New cohorts should have better LTV than old cohorts (product is improving).
• Test price increases quarterly in small segments (10% of users). If conversion impact is less than 5%, implement across all users.

*This article is part of our Monetisation and Revenue pillar. See also "Dating Site Premium Features That Members Actually Pay For" and "How to Price a Dating App for Different Markets."*