The Unit Economics of Dating Apps (Part 2)
The Golden Formula for Scalable Growth.
Let’s continue studying the core formula of the dating business.
Expected Income = (Number of New Buyers × LTV) – Marketing Costs
Last time, we examined LTV in detail in this article:
Today, we will talk about the Number of New Buyers.
Generating the Energy
You launched a Facebook campaign.
In the video banner, for instance, you show a successful man: you show how he cooks, how he goes to the gym, and how he walks his dog on the beach.
If a user is allergic to dogs, they obviously won’t click on this banner. But let’s assume they have no allergies and no life partner—they are single. And the time has come for them to find a partner.
They are tired of endlessly scrolling through their Instagram feed, and they are frankly sick of the photos of their mega-successful acquaintances. The moment is right, and with great hope, they click on this banner.
The banner created a vision of a desired goal; the user is excited and wants to find a partner right now.
Of course, they won’t land on a date with this handsome man from the banner immediately after the click. But the banner and the image of the goal have charged them with energy, and they are ready to overcome almost any difficulty. Thank this banner for that energy; we will still need it in the future.
The Harsh Reality
Next, the harsh reality begins. The user lands on your app listing in the App Store (or Google Play).
Also, Web2App funnels have become very popular recently: this is when you send users from an ad to your web application, where they undergo registration, fill out a profile, buy a subscription, and only after that proceed to the listing to download the app from the App Store or Google Play.
Why do this and complicate the path for users?
Because you pay a 15% to 30% commission to Apple and Google on every transaction.
If you have a new app and you earn up to $1 million per year, you will give away 15% (as a member of the Small Business Program).
If you exceed this threshold, you will start paying 30%.
I sincerely wish for you to exceed this threshold as soon as possible.
So, when a user pays not through Apple/Google, but enters their card details and pays via a Payment Gateway (for example, Stripe), the commission in the US is only 2.9% + $0.30, which is much less than 20-30%. That is exactly why Web2App funnels have acquired such popularity. There are even ready-made funnel builders that allow you to create them without developers. I will review them in detail in a separate article.
By the way, many beginners think that Web2App is technically difficult. In reality, there is no “magic”: the user registers and pays on the mobile site, and then downloads the app and simply logs in with the same email and password. Your database sees the “Premium” status and opens access. This is a simple synchronization available to any development team.
Important Note on Payments in the US
Recently, following the legal battles between Epic Games and Apple, developers in the US were allowed to place links to external payment methods directly inside the app (you might have seen a “Pay via Credit Card” button in Tinder).
Does this solve the problem? No. Apple still charges a commission on these transactions (around 27%), plus it requires complex reporting.
The Verdict: For a startup, a Web2App funnel is still the superior strategy. Don’t try to cheat the system from inside the app; it’s better to lead the user to the website from the start.
ASO and Installation
Next, let’s talk about how the user looks at screenshots and how important they are, as well as the icon and reviews — nobody reads the app description, so it is important to convey the essence through screenshots and headers. Screenshots and icons are so important that Apple/Google created a mechanism for A/B testing screenshots and icons.
Then, the user downloads the app.
Verification
Next, as a rule, is SMS verification. It helps to filter out lazy scammers, serving as a minimum defense. But you must be aware of two critical threats:
SMS Pumping Attacks (Toll Fraud). This is a nightmare scenario where fraudsters use bots to trigger thousands of SMS verification codes to premium-rate numbers that they control (usually in high-cost regions like Indonesia or parts of Africa). The math is scary: You pay Twilio/Telesign $0.10 per SMS. The fraudster gets a kickback of $0.03 from the corrupt telecom provider. They run a bot for one night, sending 100,000 requests. You wake up to a $10,000 bill, and they walk away with $3,000 profit. This is a topic for a separate article, but you need to set rate limits immediately.
Disposable Phone Numbers. These are temporary virtual numbers (often VoIP or SIM farms) that anyone can rent for minutes to receive a code and then discard.
This means SMS is not a 100% protection against scammers.
The Next Step — Get the User’s Email
This is critically important because email is our main tool for Retention (returning users to the app).
How exactly to get it? The classic “Email + Password” combo is already outdated and considered unsafe. Users often set weak passwords, making them vulnerable to Account Takeover (ATO) through brute-force attacks.
Therefore, I strongly recommend using Email OTP (One-Time Password). This is a “passwordless” method: the user simply enters their email, a 4-digit code is sent to them, they enter it, and they are in. No password needs to be remembered, and it cannot be stolen.
Also, add Google SSO and Apple SSO. This is even faster for the user, and for you, it is a huge plus that you do not need to verify the email — Google and Apple have already done this for you; you get a guaranteed valid email.
Important advice: Do not make a login via Facebook. Trust in it has fallen, and people are afraid to share their data through this social network.
Date of Birth
Next, we request the Date of Birth. We categorically must not let in users under 18 years old. However, the strictness of the check directly depends on your niche.
Mainstream Dating Apps (Tinder, Bumble): For ordinary dating apps hosted in the App Store and Google Play, a standard DOB Picker (selecting the date of birth in the interface) is currently enough. At the moment, this is enough to comply with store policies, although requirements are gradually tightening.
Adult Industry: Such projects are usually banned in mobile stores and live exclusively on the Web. And here, legislation (especially in the US and EU) requires strict Age Assurance. You cannot simply trust the entered date — it is illegal. You are obliged to use advanced mechanisms:
Selfie verification with AI age estimation (liveness check).
Full document check (Government ID verification).
This topic is a legal and technical minefield. In the future, I will make a separate big article about age verification, where we will consider all the pitfalls.
Filling the Profile: Energy vs. Friction
Next, we ask the user to fill out various important fields, for example: Height, Education, Job, Smoking habits, etc.
By the way, what do you think: if we don’t make these fields mandatory and request them only after the user has gotten inside the app — will they fill them out?
Actually, as my experience and other apps like Tinder, Hinge, and others show — people willingly fill out mandatory fields during registration that can be entered quickly (dropdown-based). But if you make them optional, people do not fill them out.
The secret is that during registration, people are excited and they have that energy which was created by your marketing and that video banner. And this energy, these expectations, become the fuel that, despite the friction, moves the user through the many steps of registration.
But if you make these fields optional, users get inside the app, and many of them then simply leave and do not return.
Retention Day 1 after registration for new dating apps is 10-20%, meaning 80-90% of users registered and left. And if they didn’t fill out the profile, nothing remains of them in your catalog. But if they filled out the profile but churned, then later some other user might write to this user and resurrect them.
And what do you think, what percentage of people will fill out the “About Me” field during registration if it is optional? And is it worth making photos mandatory? How many photos to request? And how does profile completeness and the presence of photos affect the reply rate? I will publish a separate article on all these questions.
The Setup Moment
Okay, the user filled out the profile, uploaded a photo, what next? Next, they get inside the app. What do they do? They look around — look at other people’s profiles, like others, and so on.
But do other people see this user? No, because moderators haven’t checked the profile yet; what if there is nudity in the photo? We cannot show it to other people, and we cannot deliver any types of messages from this user to others until they are approved.
As a rule, this moment when the user can use the product and has already performed the necessary settings is called the Setup Moment. In our case, the user must have a filled profile, they must have at least 1 photo, and they must be approved by moderators (meaning a human/system must check their profile data and their photos).
Sounds expensive? Don’t be scared. You don’t need to hire a staff of moderators from the start. In the beginning, you can (and should) do this yourself to feel the audience. And a bit later, plug in AI solutions (like AWS Rekognition), which cost pennies and automatically filter 95% of forbidden content.
Switching Modes: From Funnel to Product
Our hero has overcome all barriers: downloaded the app, passed SMS verification, completed the profile, and was approved.
They are inside. Phew.
This means we have successfully closed two stages at once: Sign Up Moment and Setup Moment (the user is technically ready to use the product).
Here we need to pause and change optics.
Until this moment, we looked at the process through the eyes of a Marketer and a Developer. Now we must put on the glasses of a Product Manager.
Why? After all, we are talking about money (Number of New Buyers), why not simply ask for payment right now?
Because in Dating Apps, Money is a consequence of Value. If we try to sell a subscription to a user who simply filled out a profile but hasn’t yet understood why they are here, we will burn the budget.
To make our business model work, it remains for us to lead the user through the next two steps:
Aha Moment (First Value). The moment when the user for the first time gets a real result and thinks: “Oh, this is what I need!”. It is exactly this realization that forms their willingness to pay.
Habit Moment (Habit). The moment when using the app becomes part of their routine. This guarantees that they will not just make a one-time purchase, but will attach to us and pay again and again while this habit is active.
But to understand when exactly these moments occur, we first need to define the global meaning of our app for the user.
Global Goal (NSM)
The ultimate goal of any dating app is to create a happy couple. That is the “Product Vision.”
But as a business, we have a problem: We cannot track happiness. It happens offline, away from our servers.
To find a metric we can track, we need to reverse-engineer the “Happy Path” of a user. Let’s trace the steps backward from the goal:
Happy Couple (The Goal)
Can we measure this? No.
Offline Dates
Can we measure this? Generally, no. We cannot stand next to them with a candle to see if they actually met at Starbucks.
Exchange of Contacts (Phone number / Instagram / FaceTime)
Can we measure this? YES. This is a digital action inside our chat.
Active Dialogue
Can we measure this? YES.
The “Offline Blindness” Problem
Most apps go blind the moment users leave the chat. Exception: Hinge is trying to solve this. They built a feature called “We Met.” After an exchange of phone numbers, the app eventually asks: “Did you go on a date?”
If the user clicks “Yes,” Hinge asks a follow-up quality question: “Is she/he the type of person you’d see again?”
It is a brilliant attempt to feed offline data back into their online algorithm.
However, for most apps, we cannot rely on users to report back. We have to trust the data we have.
That is why our North Star Metric—the most reliable “thermometer” of success—is the step just before the offline date:
NSM = The number of dialogues that result in a Contact Exchange.
The Aha Moment
In product analytics, the next big moment after Setup is called the Aha Moment. This is the moment when the user experiences the core value prop for the first time, meaning in our case, when their first dialog took place.
In our case with dating, the Aha Moment is when the user has spoken with at least one person within 1 week after registration.
Examples of Aha Moments for other products:
Airbnb: Booked night turns out well.
Pinterest: I’ve found something cool in an interesting feed.
The Habit Moment
The next important moment is Habit. This is the moment when a habit appears in the user around this core value prop. In our case, this is the dialogs with other users. That is, when a user has spoken with, for example, 10 people within 1 week after registration. This means that the user has developed a habit, and they will remain with us with a very high probability and will use our product further.
Examples of Habit Moments from other spheres:
Pinterest: “I find cool things on Pinterest every week.”
Airbnb: Booking second stay within one year.
The Engagement Moment
The next stage is the Engagement Moment — when the user has not just formed a habit, but continues to actively use the app. Moreover, they do not just come to the app, but perform the core action often, which in our case is participation in chats. And we will measure engagement in dating with such metrics:
Daily Active Chatters / Weekly Active Chatters. The meaning of the metric is we want people ideally to come to us every day and talk to at least someone. This is an indicator that measures the frequency of engagement.
Examples of how Engagement Frequency is measured for other products:
Airbnb: Frequency - QAG/YAG (Quarterly active guests / Yearly active guests).
Pinterest: Frequency - DAR/WAR (Daily Active Pins/Repins / Weekly Active Pins/Repins).
The Finale: Synchronizing Value and Revenue
We examined the user’s value track with you, but where is the Number of New Buyers here? Well, first I wanted to show how the user receives value from dating apps.
And now that value is received, is it time for us to earn on this?
Here we approach the main question: how to synchronize Value and Revenue?
The main decision that a founder must make: where exactly to place the Paywall relative to the Aha Moment?
If you ask for money too early, when there is no trust yet — the user will leave. If too late — you will leave money on the table.
Let’s compare how market leaders do this.
Two Dominant Monetization Models
1. The Tinder Model (Freemium): Payment as an Accelerator and Competitive Advantage
In this model, the Aha Moment (dialogue) is technically free. Two users can match and start corresponding without spending a penny.
Why then do they pay?
They pay for Speed (Tinder Gold): Swiping at random is work. Guessing “did they like me or not” is stress. By buying access to the “Who Likes You” list, the user cuts a corner: they immediately see those who have already shown interest. This is the monetization of impatience and curiosity.
They pay for Visibility (Tinder Platinum): The market is oversaturated. Beautiful girls simply do not see the likes of ordinary users in the pile. By buying Platinum, a man pays for his like to be shown first (Priority Likes). This is already the monetization of competition.
The essence of the strategy: Value is available for free, but efficiency costs money.
2. The Seeking Model (Paywall): Payment as a Pass
In niche apps or models with high intention, the Aha Moment is strictly behind a paywall.
You can look at profiles, you can add them to favorites, but you physically cannot enter into a dialogue without payment.
The essence of the strategy: We monetize access. The user cannot experience the Aha Moment (dialogue) until they become a buyer.
In this model, Purchase is a prerequisite for receiving value.
Main Metric: Reg-to-Paid Conversion
Regardless of which model you choose, for the variable Number of New Buyers in our formula, one metric is critically important: Registration-to-Purchase Conversion.
This is the bridge between the world of product and the world of finance.
User’s view: “I register -> Fill out profile (Setup) -> See value -> Pay”.
Business view: “Traffic -> Setup -> First purchase -> LTV”.
To maximize the quantity of new buyers, you must minimize friction at the Setup stage (make entry simple), but maximize motivation before the Paywall (make being in a free status “painful” or ineffective).
Summary
Let’s look at our formula one more time:
Expected Income = (Number of New Buyers × LTV) – Marketing Costs
In this article, we analyzed the first variable — Number of New Buyers.
We found out that this is not simply “buying clicks” on Facebook. This is a complex chain:
Funnel: Efficient delivery of the user from advertising to download (preferably via Web2App to save 30%).
Setup: Guiding the user through verification and filling out the profile on the energy created by marketing.
Trigger: Installing the paywall exactly where the user’s motivation reaches a peak — whether it is a desire to cut the path (as in Tinder) or get access (as in Seeking).
What’s Next? We have already covered LTV in Part 1. In the final article of this series, we will tackle the last variable of our equation — Marketing Costs. We will discuss how to lower your CAC (Customer Acquisition Cost), how to test creatives efficiently, and how to scale without burning your budget.
Why Build From Scratch?
Setting up monetization logic, fighting SMS fraud, and optimizing the onboarding flow is hard enough without having to code the entire platform yourself.
This is why we built SkaDate.
We provide the complete technical engine—native mobile apps, flexible paywalls, and robust anti-spam tools—ready from Day 1. Ready to skip the development nightmare?
You focus on finding the users; we’ll make sure the technology keeps them there.