The Algorithms Behind Your Dating App Are Just If-Else Statements in a Trench Coat

The Dating App Algorithm Scam: If-Else Statements in a Trench Coat

The dating app industry is gaslighting singles everywhere with claims about “sophisticated matching algorithms” and “AI-powered compatibility.” I’ve reverse-engineered three major apps, and guess what? Their groundbreaking tech is essentially IF both_swiped_right THEN create_match. That’s it. Your romantic future is being determined by code that wouldn’t pass a freshman CS assignment at a community college during a power outage.

”Proprietary Algorithm” = Basic Sorting Function Written During Lunch Break

When these companies boast about their “proprietary matching technology,” what they really mean is “we sort users by attractiveness and occasionally throw in a wildcard to keep the ugly people hopeful.” The entire billion-dollar dating industry is built on algorithms with the complexity of a sorting hat, except with more body-shaming and less magic. Even Harry Potter’s Hogwarts had better matching technology, and they were using a literal hat from the 10th century.

These algorithms have as much sophistication as a toddler sorting M&Ms by color, except the toddler has better ethics and doesn’t claim to be using neural networks.

One major dating app recently bragged about their “revolutionary ML-based compatibility system” in their investor deck. I got my hands on their codebase, and their “revolutionary ML” was literally:

// Our sophisticated AI compatibility algorithm
// (Written by an intern who had a Wikipedia-level understanding of machine learning)
function calculateCompatibility(userA, userB) {
  // Give attractive people higher scores because evolution or something
  let score = 50; // Everyone starts at "meh"
  
  // Are they both hot? That's all that matters really
  if (userA.attractivenessScore > 7 && userB.attractivenessScore > 7) {
    return 95; // Match made in heaven! Or at least in our shareholders' dreams!
  }
  
  // Boost score if they're in the same income bracket (aka can afford our premium)
  if (Math.abs(userA.incomeLevel - userB.incomeLevel) < 2) {
    score += 20; // Nothing says romance like similar tax brackets
  }
  
  // They both like "travel" and "food" (like literally everyone with a pulse)
  if (userA.interests.includes("travel") && userB.interests.includes("travel")) {
    score += 10; // Wow, they both enjoy leaving their house occasionally!
  }
  
  // Make sure low-engagement users see some matches to keep them on platform
  if (userA.daysSinceLastMatch > 7 || userB.daysSinceLastMatch > 7) {
    score += 15; // Desperation boost activated
  }
  
  // If user is about to cancel subscription, suddenly discover their soulmate
  if (userA.subscriptionAboutToExpire || userB.subscriptionAboutToExpire) {
    score += 25; // Financial desperation is our love language
  }
  
  return Math.min(score, 99); // Cap at 99% because "perfect" doesn't exist (and we need to leave room for that premium feature)
}

This isn’t just bad code—it’s malicious mediocrity masquerading as science. It’s as if someone rebranded a Fisher-Price toy as a supercomputer and nobody bothered to check under the hood.

The Data Science Grift: SQL Queries Wearing Lab Coats

The “data scientists” behind these apps are just SQL query writers with good PR and a Medium blog. They’re collecting terabytes of your most intimate preferences and reducing your personality to a handful of binary flags. Your carefully crafted profile? Compressed into three variables: attractiveness_score, response_rate, and will_pay_for_premium.

Most dating app data science teams consist of one person who took an online course in R programming, another who can make fancy charts in Tableau, and a former psychology student who once skimmed a paper about attraction. Together, they’ve created a system with all the nuance of a Magic 8-Ball but with more predatory pricing.

A former lead engineer at [REDACTED DATING APP] confessed over drinks: “Our most sophisticated algorithm is the one that strategically shows you people who’ll never see your profile, keeping you hopelessly swiping.” This isn’t love science—it’s digital purgatory with a monthly subscription fee. Dante missed a circle of hell in his Inferno: endless swiping while getting carpal tunnel syndrome.

The Great AI Washing: If THIS is AI, My Toaster is Skynet

When pressed about ethical concerns, these companies retreat behind buzzwords like “proprietary matching technology” faster than a poorly optimized query on an unindexed database. They’ll throw around terms like “neural networks” and “deep learning” when what they’re actually doing could be replicated with an Excel spreadsheet and a random number generator.

Dating apps aren’t using AI to find you love—they’re using basic loops with enough randomization to seem magical. It’s the same psychological trick casinos use: occasional wins amidst consistent losses, perfectly timed to keep you playing. The house always wins, and in this case, the house is swiping right on your credit card while swiping left on your happiness.

The Most Complex Algorithm: Keeping You Single and Paying

The dirtiest secret? Dating apps are financially incentivized to keep you single. Their entire business model collapses if they’re actually good at creating lasting matches. This creates the tech industry’s most perfect moral hazard: apps that promise relationships while algorithmically ensuring you stay single enough to keep paying.

The most complex algorithm they’ve implemented is the one that strategically shows you matches who’ll never see your profile, keeping you hopelessly swiping but occasionally matching just enough to maintain the illusion that the system works. It’s like a slot machine designed by a sociopath—it pays out just enough to keep you seated, never enough to let you walk away happy.

One ex-PM told me: “We specifically engineered the system to create ‘hope patterns’—showing an attractive person every 12-15 swipes to keep engagement high, regardless of whether you had any real chance with them. We called it ‘intermittent reinforcement’ in meetings, but really it was just ‘manipulative bullshit.’”

The same team that tries to optimize your “love life” has A/B tested exactly how many unanswered messages it takes before you’ll pay for a boost feature. It’s not cupid shooting arrows—it’s a statistician shooting at your wallet.

Dating App Code Leaked: What They’re REALLY Running

I managed to obtain some more code snippets from another major dating app’s matching algorithm:

// Determines when to show someone their "perfect match"
function timePerfectMatchReveal(user) {
  if (user.isPremium && user.subscriptionDaysLeft < 7) {
    return "NOW"; // Quick, before they cancel!
  }
  
  if (user.loginFrequency < 3 && !user.isPremium) {
    return "NOW"; // Quick, before they abandon the app!
  }
  
  if (user.engagementMetrics.declining) {
    return "NEXT_SESSION"; // They're losing interest, deploy the dopamine hit
  }
  
  return "WAIT"; // They're engaged and paying, make them work for it
}

// What factors actually determine matches
const MATCH_WEIGHT_FACTORS = {
  bothAttractiveUsers: 75,
  similarIncomeLevel: 15,
  sharedInterests: 5, // Barely matters
  locationProximity: 3, // Even less important
  personalityCompatibility: 2, // Literally a rounding error
  revenueOptimization: 90, // The REAL factor
};

How To Game The System (Because It’s Already Gaming You)

Want to beat these pathetic algorithms at their own game? Here’s how:

1. Reset your account every month. Most apps penalize profiles that have been active too long. Their algorithm assumes you’re undesirable if you’ve been on the platform for a while, which says more about their algorithm than it does about you.

2. Don’t use the app daily. Algorithms prioritize showing inactive-but-not-gone users to boost retention metrics. They’re like a needy ex—they want you most when they think you’re losing interest.

3. Answer profile questions strategically, not honestly. They’re not using your answers for compatibility—they’re building marketing segments. Your authentic self means nothing compared to which demographic bucket helps them sell more premium subscriptions.

4. Deliberately swipe in patterns, not based on interest. Many apps track your behavior to build a “taste profile.” Throw them off by swiping in specific patterns (e.g., right, right, left, right, left, left) to confuse their data collection.

5. Use multiple dating apps simultaneously. Each company thinks they have proprietary algorithms, but they’re all doing basically the same thing. It’s like choosing between generic acetaminophen and brand-name Tylenol—the active ingredient is identical, but one costs three times more.

Dating App Code vs. Actual Tinder IRL

The next time a dating app tries to sell you on their advanced matching technology, remember: you’re basically paying to have your data harvested by if-else statements wearing a lab coat. You’d have better odds writing your phone number on a bathroom wall.

At least then the rejection would be honest, and you wouldn’t be charged $29.99/month for the privilege.

Confidential to Silicon Valley: Please stop trying to disrupt human connection with overengineered spreadsheets masquerading as emotional intelligence. Even a Magic 8-Ball has a 50% success rate, which is higher than most of your platforms.