F4 Fund: How To Evaluate Mobile App Opportunities
At F4 Fund, we cast a wide net across the consumer mobile landscape, investing in apps and games that span diverse categories. From pre-seed startups with promising prototypes to seed-stage companies looking to scale, our portfolio reflects our belief in the potential of new consumer experiences, especially the ones being reshaped by AI.
My journey to founding F4 Fund with David Kaye was shaped significantly by my time as Supercell’s Director of Analytics, where I witnessed firsthand how data could transform decision-making in the mobile gaming industry. This experience, coupled with my subsequent role at co-founding Next Games, instilled in me a deep appreciation for how metrics can reveal the underlying story of an app’s potential for success.
This analytical mindset forms the cornerstone of our investment approach at F4 Fund. We’ve developed a systematic methodology that leverages data not just as a supplementary tool but as a fundamental component of our evaluation process. By examining KPIs across user acquisition, engagement, retention, and monetization, we can identify patterns that signal promising opportunities often before broader market recognition.
But numbers don’t tell the whole story. Our approach combines hard data with a human perspective on what makes products and the teams working on them special. We evaluate the vision and capability of founding teams, the uniqueness of their product approach, and their understanding of user psychology. This holistic perspective allows us to make investment decisions that are both data-informed and qualitatively analyzed.
In the following piece, I’ll share two deal types and how we apply this philosophy in practice, exploring the specific metrics we prioritize when evaluating mobile apps and games, and how these insights have guided some of our most successful investments to date.
Deal Type 1: Inbound Opportunities – Evaluating Early-Stage Apps
When early-stage developers approach F4 Fund, they typically come with a prototype or a pre-launch build. Without real users, who are using the app at their own volition, there are no established metrics to analyze like retention data, monetization data, or engagement patterns like session times per day or average session lengths. The developer might have their friends and family using the app, but that data is tainted because they might be incentivized to see the developer do well, and are sticking around and spending money to make the developer look good in the eyes of investors.
The lack of real user data often creates a challenge, especially in mobile gaming. Of course, traditional KPI analysis methods don’t work for pre-launch products. This forced us to develop alternative approaches to assess potential before a product launches.
Here’s our evaluation framework for early-stage app and games companies on mobile:
1. Founder Assessment
We place much value on previous entrepreneurial experiences. Founders who have built startups before, regardless of whether those ventures succeeded or failed, bring invaluable insights to their current project. They’ve typically developed resilience, pragmatic problem-solving skills, and a nuanced understanding of product-market fit that first-time founders are still acquiring. This battle-tested experience often makes the difference between teams that can navigate the inevitable challenges of scaling a mobile product and those that stumble at critical junctures.
Then, we evaluate the founding team’s track record and relevant experiences. Previous successful product launches, domain expertise, and the team’s technical capabilities all factor into our assessment. These indicators often serve as strong predictors of execution capability.
Equally important is the founder’s vision clarity and their deep understanding of their target audience’s needs. We look for teams who can articulate not just what they’re building, but why it matters to users and how it solves real problems. This user-centric thinking typically translates into products with stronger engagement and retention potential.
2. Product Evaluation
We test the product ourselves to see what the user experience is like, assessing the interface design and any innovative elements. We actually download and use the app to experience it like a real user, noticing both what works well and where there might be friction. This hands-on approach helps us understand if the product can create an engaging experience that keeps users coming back.
We take a close look at the monetization strategy too, using data tools like AppMagic to see what works for competitors. We also check out how the product stands out from others on the market. Maybe it through unique features, a better user experience, or meeting needs that others aren’t addressing. This kind of differentiation is usually what helps a product get noticed in crowded app stores and keep users interested over time.
3. Market Analysis
We analyze the category’s growth trends and user acquisition costs to understand the market dynamics at play. This includes examining whether the app category is expanding or contracting, and whether user acquisition costs are sustainable for new entrants. Using AppMagic’s data, we map out the competitive landscape to identify market leaders, rising challengers, and potential strategic partners or acquirers. This competitive analysis helps us evaluate whether there’s sufficient space for a new product to gain traction.
Language learning apps and their worldwide revenue in the past 12 months
The top 10 by Retention Day-7 tells a different story (who is buying traffic to boost revenues vs. providing lasting value?)
Additionally, we assess geo market opportunities across both US and international to determine scaling potential. We also establish monetization benchmarks by studying comparable apps in the same or adjacent categories. These benchmarks provide realistic targets for revenue potential and help validate the proposed business model. By understanding what similar products have achieved, we can better project the financial trajectory of a potential investment.
When we’ve already looked into an app category, we don’t reinvent the wheel the next time we see a similar pitch. We save these analyses and use them as a reference when new startups pitch us something in the same space. It helps us have context and speeds up the evaluation process. We also update these category analyses at least twice a year because the mobile space moves fast, and data from a year ago can be basically irrelevant.
4. User Psychology Assessment
We look closely at the psychological hooks that keep users coming back. A strong app needs ways to pull users back repeatedly, like rewards, progress tracking, social validation, etc. We check out these retention hooks alongside engagement mechanics to see if they’ll actually build long-term user relationships, not just one-time use. For social apps and games, we also consider the viral potential and social features that could drive organic growth.
We also break down the app’s core loop, the main activity users repeat, to see if it’s genuinely satisfying and how it changes over time to keep users interested. The best apps, and best games, have progression systems that deepen engagement as users get more experienced, keeping them around longer than just the initial “new app” phase. These psychological elements often separate apps that have lasting success from those that are just a quick trend.
Case Study: AfterHour
When we invested in Kevin Xu’s AfterHour, the social stock trading app, we discovered the following in our assessments.
Founder Assessment
Kevin Xu has a unique mix of experience as a successful trader and a tech professional. Growing $35K to $8M as “SirJack” on WallStreetBets gives him real credibility with younger investors, while his time at Stripe and YouTube shows he has the technical know-how to build a complex platform. This blend of financial success, technical skills, and community recognition makes him especially well-suited to understand what the target audience wants and build something that actually resonates with them.
Product Evaluation AfterHour stands out by combining pseudonymous social features with brokerage account verification, creating a more trustworthy space for financial discussions in a world full of misinformation. The verification system helps filter out empty talk from real expertise, solving a key problem in online investing communities. Plus, the product fills a clear gap for reliable financial education platforms aimed at younger investors. The small but active user base shows some early product-market fit, and strong engagement is especially important for a social platform like this.
Market Analysis
AfterHour’s target market is large and growing, with millions of younger investors stuck using platforms like Reddit, Discord, and TikTok that aren’t really built for financial discussions. Competitors include traditional financial media, which younger people don’t really trust, unverified social platforms that lack credibility, and fintech apps that focus more on transactions than building a community. AfterHour sits at the sweet spot between verified credentials and social interaction. This unique approach opens up multiple monetization paths, like premium features or partnerships with brokerages looking to connect with verified active traders.
User Psychology Assessment
AfterHour taps into several key psychological drivers: social validation of investment ideas, status from proven performance, and the intrinsic motivation to improve financial outcomes. It allows users to build reputation capital without sacrificing privacy, thanks to its pseudonymous approach. The core engagement loop of sharing ideas, making trades, tracking performance, and earning community recognition has strong retention potential and natural viral growth, as successful investors attract followers who adopt their strategies. The ongoing nature of investing keeps engagement fresh, with market shifts constantly fueling new content and discussions.
Watch David’s chat with Kevin from AfterHour on Youtube.
Deal Type 2: Outbound Deal Generation – Data-Driven Lead Creation
We’re currently exploring a new approach to finding the “needle in the haystack,” those under-the-radar apps with breakout potential. It’s a challenging process, but we believe that with persistence and a more structured approach, we can consistently uncover strong leads. Many mobile game developers already do this, actively scouting the market for new app launches and deconstructing successful ones. We’re aiming to adapt and refine this strategy for our investment approach.
Here’s how we’d do it.
1. Developing Our Market Scanning Methodology
We’re exploring the use of AppMagic to regularly scan for apps showing unusual growth patterns or engagement metrics. The idea is to run consistent checks across various app categories, searching for statistical anomalies that might indicate a strong product-market fit. We’re particularly interested in apps with high retention rates and low acquisition costs since these often suggest a compelling value proposition.
We’re also looking into integrating the AppMagic API to set up real-time alerts for apps with limited marketing budgets but impressive organic growth or standout KPIs. By doing this, we hope to catch emerging winners early, even in the crowded app marketplace.
2. Building a Targeted Outreach Strategy
Once we identify a promising app, we plan to take a hands-on approach before reaching out. We’ll download the app, use it ourselves, and get a feel for what makes it unique. This firsthand experience should help us have more genuine and informed conversations with the team. We’ll also research the founding team’s background and the company’s history to better understand their journey.
Our outreach will be personalized and value-driven, focusing on the specific aspects of the app that impress us and how F4 Fund could help accelerate growth. We’re also considering leveraging LinkedIn Sales Navigator for this, aiming to find mutual connections for potential warm introductions.
Final Words
The mobile app ecosystem offers unique advantages for data-driven investors. Unlike many other sectors, the transparency of app store metrics and user behavior gives us the insights needed to make more informed decisions. At F4 Fund, we attempt to take full advantage of this by combining two approaches: rigorously evaluating inbound opportunities and proactively generating leads through systematic market scanning. This strategy should prove effective in spotting exceptional investment opportunities in the mobile space.
As data becomes more abundant and AI tools keep improving, our investment processes will get even more sophisticated. That said, we believe the human element will always play a crucial role. Data makes us informed and helps us to make decisions, but it doesn’t replace judgment, especially when it comes to evaluating founding teams or breakthrough product ideas.
