How Dating App Algorithms Work and How To Choose One for Your App

10 min read

How do humans choose a romantic partner? If you’re stumped, that’s not surprising.

Frank L.
Frank L.
Published April 10, 2023

Everyone goes about dating in different ways.  

Yet dating app algorithms are designed to predict romantic attraction. So, how does the algorithm decide who to pair up?

Just like any algorithm, a dating app's algorithm tells your app the rules for decision-making. It's the set of instructions the app uses to find and sort potential matches based on things like user surveys or behavior. If a user has a tendency to like profiles of users who are outdoorsy extroverts with jobs in academia, the algorithm is the bit of math that the app uses to notice the pattern and prioritize similar profiles. 

How your dating app matches people up will greatly affect users' experience and therefore affect the success of your app. And there's a lot to consider when creating the algorithm.

What To Consider Before Choosing a Dating App Algorithm

Talk about dating apps, and you'll hear about the almighty algorithm as if it's some all-knowing mathematical equation that can predict the human heart. The truth is that your algorithm is only one part of your app. It's an important part, to be sure, but the algorithm underlying any matching app isn't going to be some kind of silver bullet for success.

Because the algorithm is only the equation used to match one profile to another, there's a lot you need to know before even choosing your algorithm.

What Does Success Look Like for Your App?

Your algorithm is an extension of your product philosophy. So, what is your dating app's purpose? What would success even be for you? Get clear on what you want your app to do if you want to have any hope of being successful.

Do you want to build a dating app for gamers, like Kippo? Then you need an algorithm that prioritizes matching people based on common interests and facilitates discussions. 

Or maybe, like Chorus, you're looking to add a social aspect to your matchmaking by letting friends pick matches for each other. In that case, you'll need an algorithm that can handle two different user roles on the app (likely with differing and sometimes even incompatible opinions).

Your algorithm needs to reflect the kind of dating app you want to create. So, first, define what a successful match would look like on your app and what you want your user experience to be.

What Kind of Data Will You Use?

It's all well and good to have a great idea for a dating app or even a great algorithm, but when it comes down to making that app a reality, you need to consider the data you put into the algorithm. The data your algorithm uses will make a huge difference in whether your app can live up to its goals.

To start, define what kind of data you'll need and decide how you're going to get it from your users.

Based on your purpose, what kind of information should your algorithm consider? If you were building a dating app based around astrology, like NUiT, your app would need to be able to handle astrological charts, but otherwise, it will handle data much like any other dating app.  

If you were building an app that emulated the feel of TikTok's short videos, like Snack, you'd need an algorithm that can incorporate video data, something that's a lot more complicated than a text-based dating app, like Lex, where you'd only need an algorithm that can handle the smaller file size of text data. 

What kind of data you have available and what you need your algorithm to get out of that data will help you decide what you need from your algorithm. 

How Will You Balance Complexity With Practicality?

Finally, you need to consider how much complexity you want to add. There is a tradeoff, though. The more complex your algorithm, the more you can fine-tune your matches. But at some point, the size of the equation overpowers its ability to function. 

As the authors of this article on matching algorithms put it, "a perfect map of the world would be as large as the world itself." In other words, it's probably not possible to build a dating app that's as complex as romance due to the high complexity of human social relationships. Therefore, you have to make some concessions and oversimplify some aspects of your algorithm in order to make the algorithm simple enough.

Your app has limitations; it can handle a finite amount of data and calculations. So, as you decide on and start building your algorithm, you need to keep in mind that you must balance complexity with practicality. How complicated does your app need to be? Do you have the tools and staff able to make an algorithm of that complexity functional? And will your users be happy with the level of complexity?

Answer these questions first before attempting to choose your algorithm, or you may find you have to backtrack and rethink your algorithm later in the process. For example, you may want a detailed, home-built algorithm but discover that your core audience has no patience for filling out surveys. In that case, it would have been better to understand your ideal users and how complex they want their dating apps to be before choosing your algorithm.

It's not easy to get an inside look at how most dating apps pair up their users. In fact, it's become somewhat of the norm in the dating app industry to guard algorithms closely. Search for dating app algorithms, and you'll find only a small number of brands openly discuss theirs. Bumble, Match, eHarmony, and many others don't get into it publicly.

But that said, if you know where to look, you can learn a lot about how app creators and algorithm builders approach matchmaking with math.


Hinge is one of the only dating apps that's open about its algorithm. According to Logan Ury, the director of relationship science at Hinge, the company's app uses the Gale-Shapley algorithm. This algorithm is a classic and a great option for any matching scenario. If you must simply choose an algorithm that's already proven effective, go with the stable matching method of Gale-Shapley.

Since the 1960s, the Gale-Shapley algorithm has been matching medical students with hospitals for their residencies as well as organ donors to recipients — and now romantic couples.

Gale-Shapley is effective because it uses "stable matching." In this sense, it's a true matchmaker because it considers both sides of the match. What's unique about Hinge's app is that it considers not just what kind of person the user might want to date but also how much that person would like the user back. 

For a dating app to be a success, the parties matched up must both be happy with their matches, but not everyone will like the people who like them. So, Hinge's algorithm does more than simply choose what will make one party happy; it balances how one party is perceived by other users. Each person is paired up with the person best suited to them based on their preferences and vice versa. In this way, there's a holistic consideration of everyone's feelings at once. 


Before OkCupid, dating apps tended to work one of two ways: 

  1. A search function gave users a series of profiles to read based on preferences. 
  2. The algorithm delivered only a handful of random profiles to users to review each day.

The makers of OkCupid went with a hybrid of these two methods that included a matching system that also gave users the option to search through profiles and even review their compatibility with other users.

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Complexity is the name of the game at OkCupid. Its matching method works because it pulls from a large volume of data on each user that is generated by an extensive survey. 

When a user answers OkCupid questions, the algorithm weighs three factors against each other for each question: 

  1. How much it thinks your match will like your answer
  2. What you said you wanted your match to answer
  3. How important it is to you that your match's answer aligns with your expectations

Then the app calculates a match percentage and averages the percentages for each question both users answered. Based on the averages for the questions, the algorithm calculates an overall match percentage of the pairing.

However, the algorithm behind OkCupid's matching system is home-built, so if you want to do something similar, you'll need the help of an expert. This is also the most expensive route, as it will require not only developers to build the app and implement an algorithm but also the creation of the algorithm itself.

This in-house approach gives you the best chance to stand out in a crowded dating app marketplace. If you have the time and budget like OkCupid, you can develop a unique matching algorithm that you can point to as a way to differentiate your app from others.


For a long time now, Tinder has been a giant in the dating app world --- the app all the others aim to beat. Launched in 2012 as a "flirting game" called Matchbox, Tinder quickly got a lot of press for its unique user interface. Tinder gamified dating by introducing swiping.

Instead of filling out long profiles or hoping the app would send them appealing matches, Tinder users are presented with profiles and can quickly say yes or no to each. With the release of Tinder, suddenly, dating was almost a game. Tinder was quick and easy to use, it didn't require the time and effort required to fill out long surveys, it was free, and most importantly, it was fun.

When it launched, Tinder used the Elo rating system, an algorithm created for chess competitions. With this formula, a win increases the person's score, and a loss lowers their score. Tinder applied those same rules to swiping, so someone swiping left on a profile was considered a "loss" for that profile, and someone swiping right was considered a "win." Tinder calculated user scores based on that and matched users with people who had similar scores.

Tinder was already fighting the idea that it was a hookup app when a 2016 article appeared in Fast Company explaining the Elo rating system in detail and discussing the user score that resulted. Rumor spread that Tinder scored every user on attractiveness, a half-truth that obviously wasn't the message Tinder wanted to send about its app. 

Today, Tinder is vocal that it no longer uses the Elo rating system. The company doesn't go into detail on what it's using now, though. The most it'll say is that the best way to get matches is to be online and swiping a lot.

Now, the company is working on "Tinder Vault," a new offering that's expected to cost $500 a month. But so far, Tinder has been tight-lipped about what the new offering will entail or what algorithms it will use.


Another approach, one that might be called the anti-OkCupid, is to ditch the complex matching algorithms entirely. That's what Grindr did, giving users a chance to bump into people more organically. 

On Grindr, users are shown profiles that match their stated basic preferences (like gender or age), their current location, and when they were last online. That's it. There's no complex matching system to show users the profiles they might like the most.

The app does use some "automated decision-making" for security, like identifying bots, but for the most part, Grindr's aim is to let users connect with whoever is nearest and also online.

This approach has a lot of benefits. First of all, it's easier to implement. Grindr doesn't have to worry about a complex algorithm with plenty of opportunities for bugs. It also doesn't need to implement new features. That saves the product team a lot of money and employee time.

But this simplicity comes with some drawbacks, too. The lack of a unique matching algorithm means an app will also lack any clear way to differentiate itself from others based on its matching algorithm.

Still, Grindr clearly hasn't found that to be an issue, as according to this Fast Company article, Grindr reports 12 million users a month as of the end of 2022.

How To Implement a Dating App Algorithm

1. Decide on In-house or Third-party 

When choosing whether to build your own algorithm or use one that already exists, it's important to carefully consider what kind of algorithm will best serve your app's purpose and lead to your definition of success.

Do you have time to build an algorithm from scratch? If you want to differentiate your app based on a unique approach to matching users, you might need to build one in-house. Then again, if you need an app up and running fast and your algorithmic needs aren't complex, a third-party app would make more sense.

2. Make a List of Needed Resources

Once you've decided on the algorithm that will work best for you, you'll need to figure out what resources you'll need to make it happen.

This includes hiring any additional team members you may need, securing funding to cover development costs (as well as ongoing maintenance), and acquiring any tools that your team needs to build and/or implement your algorithm effectively.

For more on how to launch a new product, our Product Launch Checklist will take you through each step of the process.

3. Validate and Test Frequently

Once you have assembled your team and acquired the necessary resources, it's time to begin the development process. If you don't have developers on staff to build the app in-house, you might use a low-code builder, like or Spring Boot

However, it is crucial to test the app frequently to ensure that it is up to the desired standard. This will allow you to identify and address any issues that may arise during the development process and make the necessary adjustments along the way. 

Regular testing can also help you to identify areas of the app that may require additional attention and fine-tune the app so the final product meets the needs and expectations of your target audience.

For example, if your app concept is built around introducing users to lots of new profiles, but testers keep seeing the same 10 profiles over and over again, your app won't be able to fulfill its mission for its users. You'll need to test frequently to make sure users get fresh matches frequently enough to encourage them to keep using the app.

Choose Your Chat Features Wisely

Once you've got your algorithm in place, you'll need to build out a place for your users to start talking. After all, the point of a dating app is to connect people and allow them to get to know each other. You can accomplish this by integrating a chat API.

After the algorithm and primary user interface, chat is the most important feature for a dating app. Make sure you have all the functionality your users need to make the kind of connections they're looking for. It's how they first interact and get to know each other. When choosing a chat feature, go with a tool that can offer both customization and scalability, so you can build the chat function that's best for your users and know that the tool can grow with your app.

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