Table of Contents
Online Dating Background
The Genesis of Match Group
The Tinder Cash Cow
Match Group Business Overview
Business Quality – Key Issues
Low user information density
High levels of user churn
Reputational issues
Management turmoil
User demographic constraints
The Future of Match Group
Extracting more value from power users
Pricing-led growth is great if you can get it
Hinge – stealing the show
Upside optionality from App Store fee changes
Valuation
Key Takeaways
Match Group is a holding company of online dating apps. MTCH’s brands are incredibly dominant: more than 50% of relationships that start on a dating app/site begin on a Match Group brand.
Tinder, which comprises the majority of MTCH’s earnings, is now raising prices and rearchitecting their subscription plans (introduction of weekly subscriptions as well as an imminent super-premium tier that monetizes power users) after a period of falling behind on price increases relative to competitors. Bumble’s average revenue per paying user is 87% higher than Tinder’s. The large pricing difference bodes well for Tinder’s ability to raise prices and at the recent Citi conference, the CFO said Tinder was going to hit double-digit top-line growth a quarter earlier than previously expected, indicating good traction with these initiatives.
Hinge growth is accelerating, and the $400m FY23 revenue guide implies the business will hit a 50% Q4 revenue growth exit rate. As Hinge becomes an increasingly large value driver (within five years Hinge is likely to be contributing >80% of incremental MTCH revenue dollars and at improved margins), the narrative is likely to shift away from the mature Tinder cash cow towards the more promising, high growth Hinge asset. The greenfield geographic expansion opportunity (Hinge is in just 20 countries compared to Tinder in 200) and a product that’s resonating with daters could see Hinge become a greater than $1 billion top-line business alone.
Almost 70% of MTCH’s COGS are paid to the Apple and Android app stores via in app purchase fees. Recent legislation and litigation are putting pressure on these internet gatekeepers to lower their take rate which could result in a 9 ppt one-time margin boost for MTCH.
MTCH trades at 14x forward earnings and an 8% FCF yield, despite accelerating business metrics. We can reasonably underwrite $5.80/sh in FY27 FCF, implying a 14% IRR and 2x MOIC. Under a bull case scenario where app store fee relief is granted, MTCH could achieve a 31% IRR over the next 5 years, a 3.8x MOIC.
Online Dating Background
“Dating” means different things to different people. It could be serious or casual. Short-term or long-term. Monogamous or open. Straight or gay. However, at its core, dating involves two people coming into contact and interacting. The process of finding that person has historically been hyperlocal. Aziz Ansari, in his book Modern Romance, interviewed a swath of seniors in a New York retirement home. Astonishingly, over one-third of those interviewees met their spouses within a block or two of their childhood home. This revelation extends beyond the anecdotal accounts of these New York seniors.
A 1932 study by Brossard examined the addresses found on 5,000 Philadelphia marriage licenses, showing that one-sixth of the couples lived within a block of one another, one-third lived within five blocks, and 51.9% lived within twenty blocks of each other. With numerous technological advancements in the interim since that study – cars, planes, and most importantly, smartphones – there has been a proliferation of dating options that has complicated and irrevocably changed the dating landscape. The Internet, and the subsequent emergence of online dating, has been a key contributor to that tectonic shift.
Online dating dissolved the historical propinquity that characterized dating for centuries – that is, the physical proximity that would nurture kinship. Suddenly people had access to dating prospects from all over the globe, no longer bound by the need to physically approach someone to start an interaction. It was 1995 when the world’s first online dating website, Match.com, was launched. The site was open to anyone over 18 years old with an email address. It heralded a step change in the experience of searching for a mate.
Dating on the Internet obviated the need to frequent dingy clubs in the wee hours of the morning, risking cold, hard rejection from a would-be companion. Rather, rejection in the online sphere was silent and unfelt. Better still, the search could be undertaken in your pajamas from the comfort of your own home. The genius of Match.com was that it addressed the pitfalls and inefficiencies of dating in the analog world; social shyness, fear of rejection, and the need for physical proximity melted away as impediments to starting an interaction. The follow-on effects from what Match.com started were profound. Nowadays, according to Match Group, 40% of all relationships in the U.S. start online and 1/3 of marriages begin on an app.
The Genesis of Match Group
Match.com was revolutionary: not only did it wildly expand the market for dating candidates, but it also allowed searches to be filtered based on selected criteria. Co-founder of Match.com, Gary Kremen, was obsessed with data. He would provide users with a questionnaire, with granular and occasionally bizarre questions, where the output was used to pair users based on their preferences.[1] Never had a data-driven approach to dating been married with the scale of the internet. The results were impressive. Within a year and a half, Match.com had 100,000 registrations[2].
The website monetized its users by charging a monthly subscription fee, with discounts for longer-term subscriptions. In 1997 Match.com was acquired by Cendant, who later sold the business to USA Networks Inc. (later renamed IAC) on June 14, 1999 for a total purchase price of $43.3 million (interestingly, the entity within USA Networks Inc. that purchased Match.com was Ticketmaster Inc.). At the time it was purchased by IAC, Match.com had more than four million user registrations and approximately 560,000 active users[3]. Below is a snapshot of what the Match.com user interface looked like.
Source: LowEndMac
Within the fold of IAC, Match.com was joined by a range of other online dating properties which IAC purchased. IAC had a reputation for being a highly acquisitive holding company. Its playbook was to buy and build up companies before spinning them off. The brainchild of billionaire media mogul, Barry Diller, IAC was a hodgepodge assortment of media assets which over time came to include Ticketmaster (later spun off by IAC as a standalone entity in 2008 and then merged with Live Nation in 2010), Expedia, Angi’s List, Lending Tree, Investopedia, and many others. The strategy was very successful, generating immense value for IAC shareholders when incorporating the value from these distributed assets.
Match Group was incorporated in February 2009, combining all the dating properties that IAC had acquired. Match Group then completed its initial public offering on November 19, 2015 – it listed for $12.00 per share. On December 19, 2019, Match Group and IAC entered into a Transaction Agreement to split into two, separate public companies. The separation was completed on July 1, 2020. Barry Diller, Chairman of IAC, commented on the transaction: “We’ve long said IAC is the 'anti-conglomerate' – we’re not empire builders”. It is helpful to understand this history of how Match Group came about, particularly the acquisitive growth that resulted in dozens of dating properties being housed within the group.
Match Group Business Overview
Match Group, as we have explored, is a portfolio holding company that owns online dating assets. Its dating brands are extremely dominant, with more than 50% of relationships that start on a dating site/app beginning on a Match Group brand[4]. The company earns the vast majority of its revenue directly from users in the form of recurring subscriptions and, to a lesser extent, à la carte purchases. Subscriptions enable users to access various features for a specified period of time. This might include unlimited likes, no advertisements, or the ability to “passport” to another location. Below are the Tinder subscription tiers and the benefits you get by purchasing a subscription.
Source: Tinder
Source: Tinder
Users may still use flagship apps such as Tinder for free, but their experience will be hindered by limits on the number of profiles you can interact with, amongst other curtailments designed to push users to upgrade from free to a paid subscription. À la carte purchases involve the unbundling of these subscription packages, allowing users to purchase additional units of features such as “super likes” and “boosts”, etc. Below are some details on some of the most popular a la carte features:
Super Likes (~$3 each) – helps you stand out by prioritizing your profile for the person you’ve sent it to.
Boost ($6-8 each) – allows you to be one of the top profiles in your area for 30 minutes, increasing your chances of getting a match via an up to 10x boost to your profile views.
Super Boost ($40+ each) – similar to Boost but can get a user up to 100x more potential matches.
In addition to the forms of direct revenue discussed above, Match Group also receives a much smaller percentage of its revenue from indirect revenue sources, namely advertising revenue.
Match Group’s portfolio of brands includes Tinder, Hinge, Match, Meetic, OkCupid, Pairs, Plenty Of Fish, The League, Azar, Hakuna, and others. Below is a logo summary of key Match Group dating apps:
While Match has a lot of dating brands, Tinder is what really matters for this business, given that Tinder direct revenues comprise 56% of Match’s total revenue (FY22). Tinder is the most downloaded dating app worldwide as well as the #1 grossing lifestyle app overall worldwide[5]. Hinge is a distant second within the Match Group stable of brands, with its direct revenue making up 9% of consolidated revenues. It’s worth noting that Tinder’s scale means that it enjoys very high margins, resulting in an even greater portion of Match’s earnings deriving from Tinder. For these reasons, much of the focus of the analysis will be on Tinder and Hinge.
The Tinder Cash Cow
Tinder uses a double opt-in matching system, whereby both users must like each other in order to exchange messages. Users “swipe right” to like a user’s profile, or “swipe left” to reject that profile. The original prototype for Tinder was developed by Sean Rad and Joe Munoz at a hackathon held at the Hatch Labs incubator in West Hollywood in 2012. Some fun trivia: Hatch Labs was launched by IAC in 2011, meaning that IAC incubated Tinder from the beginning before ultimately acquiring it in 2017[6]. Later in 2012, Rad and co-founders Justin Mateen and Whitney Wolfe soft-launched Tinder in the App Store.
Tinder developed a frictionless onboarding system that abandoned the filling out of forms that characterized previous online dating services. Rather, new users could simply login with their Facebook profile and then could start swiping on user profiles. This enabled viral growth that was unprecedented for a dating app. The growth hack to supercharge Tinder’s early user growth was by visiting college campuses and recruiting students to the app. In an interview with Bloomberg, Tinder’s technical co-founder Joe Munoz explained:
[Whitney Wolfe] would go to chapters of her sorority, do her presentation, and have all the girls at the meetings install the app. Then she’d go to the corresponding brother fraternity — they’d open the app and see all these cute girls they knew.
Tinder started off with less than 5,000 students before Wolfe embarked on her college recruiting trip and had around 15,000 by the time she returned. The growth that followed over the ensuing years was astronomical. After just two years, Tinder was racking up 1 billion swipes per day and 12 million matches per day[7]. Tinder was rumored at the time to be approaching 50 million active users[8]. Users were logging into Tinder on average 11 times per day, spending up to 90 minutes each day on the app[9]. In 2017 Tinder became the highest grossing app on the Apple App Store[10]. That is wild. Tinder was making more money from iOS users than popular apps such as Candy Crush and Netflix.
Source: Insider via Apple
A corollary of this early virality is that Tinder could grow at a breakneck pace and spend de minimis on marketing. While this is coveted growth, it has created issues that Match Group is currently grappling with (we will explore these later). Below is a snapshot of the Tinder app:
Source: TechCrunch via Tinder
Tinder’s revenues have grown strongly at a 22% CAGR over the last four years (note that the 100% YoY Tinder revenue increase in 2018 stems from acquisition timing, with Tinder merging with IAC in July 2017 such that Match Group recognized only a partial year of Tinder revenue in 2017).
Source: Bristlemoon Capital; Company filings
While a 22% revenue CAGR is nothing to scoff at, the growth trajectory has markedly slowed, with just 9% YoY Tinder direct revenue growth in 2022. The numbers look much worse when we observe the rapid quarterly growth deceleration for Tinder. Tinder direct revenue was growing at north of 20% in 2021 before a dramatic deceleration to flat growth in 4Q23 and 1Q23. The most recent quarter (2Q23) has shown some life in Tinder direct revenues, growing 5.7% YoY.
Source: Bristlemoon Capital; Company filings
That’s a very ugly chart for a company’s revenue growth. Match Group investors who were underwriting the business as a 20% grower received a rude shock from the Tinder slowdown. The prospect of Match Group’s Tinder cash cow stalling created investor consternation, with the stock subsequently declining 83% peak-to-trough, falling from a high of $182 down to just under $31 per share.
Source: Koyfin (Bristlemoon readers can get 20% off a Koyfin subscription via this link)
So what’s going on at Tinder? Sensor Tower data has shown Tinder downloads to be declining over the last few years. This is at a time when other dating apps such as Bumble and Hinge are rapidly gaining users.
What is even more concerning is that the growth in the number of paying Tinder users has stalled. In fact, the number of Tinder payers has declined year-over-year for the last two consecutive quarters, with three consecutive quarters of sequential declines.
Source: Bristlemoon Capital; Company filings
Source: Bristlemoon Capital; Company filings
This signals deeper product issues that are causing users to churn and not reactivate, and/or would-be swipers to skip Tinder altogether in favor of other apps. We can think of Tinder’s userbase as a (very) leaky bucket, with water being poured in (new users/old users reactivating) and then leaking out of holes in the bucket (users that stop using the app and churn out of the service). Without series data for total Tinder users, we can look at the reported number of Tinder payers as a proxy for the well-being of the Tinder community (although this proxy has been weakened by recent developments around Tinder price increases and the introduction of weekly subscription tiers).
The declining number of Tinder payers we have observed in recent quarters is a red flag, signaling deteriorating health for the app. A former Match Group employee opined that both active users and payers were declining in tandem: “I think it's a combination both of active users that have been dipping and payers that have been just failing to resubscribe or failing to find a good option or not feeling that they're getting the value for what they're paying, and so just letting their subscriptions lapse”[11].
In the 2Q23 Match Group Shareholder Letter, there were some useful disclosures around Tinder Daily New Users. While still negative, there has been a sustained improvement in the trajectory of daily new Tinder users since February 2023. While we don’t know if there’s a base effect at play by lapping easy prior year comparisons, it’s encouraging that Tinder’s new campaign, It Starts with a Swipe™, is positively impacting Tinder’s new user trends. It was noted in the 2Q23 earnings result that Tinder is seeing a “significant increase” in both new user signups and reactivations in the U.S. and other key markets. Female users in particular have shown a “particularly notable improvement” in daily new user trends since the beginning of the year.
Source: Company filings
There are potentially several reasons for the issues that have been afflicting Tinder: 1) low user information density; 2) inherent churn hurts the LTV/CAC equation; 3) reputational damage; 4) management turmoil; and 5) user demographic constraints. We will explore these issues and assess the likelihood of Match Group’s management team being able to rectify these problems.
Low user information density
Easy onboarding of users is a double-edged sword for Tinder. On the one hand it enabled viral growth by removing sign-up frictions. On the other hand, faster onboarding also results in a lower information density for user profiles, given that there are less questions or prompts that can be used by Tinder to capture user information. On the 1Q23 call, it was mentioned that Tinder new user onboarding takes three to four minutes. At Hinge, the process can take more than 5x that, implying a 15–20-minute sign up time as users spend more time inputting information to complete their profiles. Below are the screens users progress through when signing up to Tinder for the first time.
Source: Tinder
The paucity of user information for Tinder users limits what the app can do to effectively match users to other users. A former Director of Corporate Strategy at Match Group articulated this conundrum for Tinder during a Tegus call:
there's a lot of user liquidity, but there's really nothing special about it, and you actually have to do a lot of work to find someone that might be in your preferences because Tinder doesn't have a good way to filter and people don't usually put a lot of information in their bios. So even though you can do some searching, it's not very effective.
The filtering options on Tinder are fairly basic. Users can filter profiles according to distance and age.
Source: Tinder
The filtering capabilities of Tinder pale in comparison to other apps that have filters allowing you to specify preferences regarding educational background, religion, political bent, family plans, drinking, smoking and drug use, and other personal attributes such as body type and ethnicity. Bumble, for example, allows for much greater filtering functionality once a user upgrades to a premium profile.
Source: Bumble
Low user information density is a problem because it hinders Tinder’s ability to curate user profiles. Without rich profile information, it becomes more difficult to show a user the profiles of other users they’re most likely to be interested in. This problem becomes even more pernicious as the platform scales. We can think of Tinder’s scale and unrivaled user liquidity as both a blessing and a curse. Having the most users on a dating platform holds immense promise that Tinder is the app where you will meet someone. The problem is that at some point the quality of incremental subscribers – that is, their attractiveness as dating candidates – degrades. That sounds harsh but the reality is that the majority of the population is unlikely to be of burning interest to the average dating app user. Jerry Seinfeld put it bluntly in the Seinfeld episode “The Wink” when he presented a rather downbeat assessment of the attractiveness of people:
Jerry Seinfeld : Elaine, what percentage of people would you say are good looking?
Elaine Benes : 25 percent.
Jerry Seinfeld : 25 percent, you say? No way! It's like 4 to 6 percent. It's a 20 to 1 shot.
Elaine Benes : You're way off.
Jerry Seinfeld : Way off? Have you been to the motor vehicle bureau? It's like a leper colony down there.
Elaine Benes : So what you are saying is that 90 to 95 percent of the population is undateable?
Jerry Seinfeld : UNDATEABLE!
Source: Seinfeld via IMBD
These real-world dynamics – that is, who we find attractive and the relatively small pool of people that fulfil these criteria – create problems for the scalability of a network business such as Tinder. The very best network businesses benefit from a long runway of increasing returns to scale. In other words, the network becomes stronger with each additional user that joins. This does not appear to be the case for Tinder or dating apps in general. Rather, there’s a point where the network effects asymptote. This idea is captured in a great article from a16z[12]. The authors, D’Arcy Coolican and Li Jin, talk about “network contaminants” – that is, incremental users who degrade the user experience for other users. Network contaminants weaken the network effects of a platform; this creates a situation where a platform can actually become less valuable as it continues to onboard new users, provided that those new users worsen the product/service for existing users.
Source: Bristlemoon Capital; a16z
Initially when Tinder was onboarding college students around campus, the network strengthened with each new user. This is because having more college students on the platform reinforced the value of that community by creating a larger pool of users who went to the same school and are also in close proximity. However, let’s take an extreme example and say that Tinder hypothetically manages to onboard every single person on planet earth. You’d have literally billions of people to scroll through. However, this is very much not a case of “the more the merrier”. For example, around 36% of the profiles encountered by a U.S. user would be from users located in China and India (based on their share of the global population size). This is not of great use if you’re looking to spontaneously meet up with that person for drinks the following night.
While in this extreme scenario Tinder will have reached maximum user liquidity, the user experience would diminish to a point where the app becomes unusable. The only solution would be better user profile curation. Alas, and here is the core of the issue: Tinder doesn’t have the best information to curate profiles and overcome the issues of network contaminants. Relative to other apps that collect more data during the sign-up process, Tinder is disadvantaged in its ability to efficiently connect users.
This potentially means users must wade through more profiles until they find users they swipe right on, an issue that worsens with greater user scale. Tinder could address this issue via a more rigorous approach to user data collection when they first download the app. However, greater friction during onboarding could also potentially hurt net additions which are already an issue, as we will explore.