How Do I Use My App's Data to Get More Funding?

A social media scheduling app launched with 50,000 downloads in its first month and the founder thought investors would be queuing up to write cheques. They weren't. The app had decent download numbers but the data told a different story...daily active users sat at just 8%, retention after seven days was below 15%, and most users never scheduled more than two posts before disappearing. The numbers showed that people were curious enough to download but not engaged enough to stay, and that's exactly the kind of red flag that makes investors close their wallets.

Investors fund growth patterns, not download counts, and your app's data either proves you have a business worth scaling or reveals that you're still searching for product-market fit

I've watched dozens of funding conversations over the past ten years and the ones that succeed share something in common...they walk into the room with data that tells a clear story about user behaviour, growth potential, and the path to profitability. Your pitch deck matters, your vision matters, but when an investor starts asking questions about retention curves and unit economics, that's when the real conversation begins. The founders who can't answer those questions with specific numbers don't get a second meeting. It's that simple.

The data you collect from day one becomes your evidence that real people find real value in what you've built. This matters more than any projection or market size estimate because it's based on what's already happening, not what you hope might happen. A healthcare app we built tracked every user interaction from launch day, which meant that when the founders went looking for their Series A six months later, they could show exactly how doctors were using the clinical decision support features and which workflows were driving the most engagement. That data helped them raise 1.2 million quid.

The Six Numbers That Matter Most to Investors

Investors see hundreds of apps each year and they've learned to cut through the noise by focusing on a handful of numbers that reveal whether your app has legs. These six numbers come up in every serious funding conversation because they tell the story of whether you've built something people actually want and whether you can turn that into a sustainable business.

The Core Six

1. Monthly Active Users (MAU) and how quickly this number is growing month over month
2. Daily Active Users (DAU) and the DAU/MAU ratio which shows how sticky your app really is
3. Day 7 and Day 30 retention rates which prove users come back after the novelty wears off
4. Customer Acquisition Cost (CAC) which shows how much you're spending to get each new user
5. Average Revenue Per User (ARPU) or Lifetime Value (LTV) depending on your monetisation model
6. Monthly Recurring Revenue (MRR) growth rate if you're running a subscription model

Each of these numbers means something on its own but investors look at how they relate to each other. An e-commerce app might have brilliant retention numbers but if the CAC is higher than the LTV then you're losing money on every customer you acquire, and that's not a business an investor can back. A fintech app we worked on had to completely rethink their user acquisition strategy when the data showed they were spending £47 to acquire users who generated an average of £31 in lifetime value. The numbers don't lie.

Building Your Data Collection System From Day One

The biggest mistake I see founders make is treating analytics as something they'll add later, after they've got some traction. This is backwards. If you're not collecting data from your first real user, you're making funding conversations harder for yourself down the line because you won't have the historical data to show growth trends or prove that product changes actually improved key numbers. This is just one of the common obstacles that prevent apps from reaching their full potential.

Set up your analytics implementation before you launch, not after, and make sure you're tracking events that matter to your business model rather than just page views and session duration

What You Need From Launch Day

A meditation app we launched collected detailed data about which meditation lengths users preferred, which voice guides they responded to, and what time of day they were most likely to open the app. This granular data became the foundation for their seed round pitch because it showed they understood their users at a deep level and could make data-driven product decisions. When investors asked how they planned to improve retention, the founders could point to specific features that the data suggested users wanted. Understanding your first-year budget requirements for proper analytics infrastructure is crucial for setting yourself up for funding success.

Monthly Active Users vs Daily Active Users: What The Difference Tells Investors

The relationship between your monthly active users and daily active users reveals how often people actually use your app, and this tells investors whether you've built something that becomes part of users' daily routines or something they check occasionally. A high DAU/MAU ratio (above 20%) suggests you've created a habit-forming product, whilst a low ratio indicates you're more of a utility that people use when they need it but don't think about otherwise.

What Different Ratios Mean

A property management app we developed had a DAU/MAU ratio of just 12% but this wasn't a problem because landlords only needed to use it a few times a month to collect rent and handle maintenance requests. The key was showing investors that this usage pattern was intentional and that the business model (transaction fees) matched how people naturally used the app. Context matters. An education app for exam revision might have terrible engagement during summer months but spike during term time, and showing investors that you understand these patterns proves you know your market.

Retention Rates and Why 40% Day-7 Retention Changes Everything

Retention rates measure what percentage of users come back to your app after specific time periods, and this single number probably matters more to investors than any other because it proves whether you've solved a real problem or just created a novelty that people try once and forget. Apps with strong Day 7 retention (above 40%) are rare and valuable because they suggest users have integrated the app into their lives.

Getting a user to download your app is expensive but getting them to come back seven days later is what separates viable businesses from vanity projects

I've watched apps with 100,000 downloads fail to raise funding whilst apps with 5,000 downloads and 45% Day 7 retention get oversubscribed rounds. The maths is simple...if most of your users disappear after their first session then you need to keep acquiring new users just to maintain your numbers, and that's an expensive treadmill that doesn't lead anywhere good. A recipe app we built focused entirely on improving Day 7 retention for their first six months, testing everything from push notification timing to onboarding flows, and managed to get it up to 38% before they started spending serious money on user acquisition. This kind of focus on strategic user acquisition spending is what separates successful apps from those that burn through their budgets.

What Good Retention Looks Like

Day 1 retention should sit around 40-50% for most consumer apps, Day 7 retention above 25% is decent and above 40% is excellent, whilst Day 30 retention above 15% suggests you've built something sticky. These numbers vary by category...a game might need higher retention to be interesting whilst a B2B productivity app might have lower frequency but much longer lifetime value per user.

Revenue Per User and Unit Economics That Make Sense

Investors want to know if your business model works at the unit level before they help you scale it, and that means showing them that the revenue you generate from each user exceeds what you spend to acquire them by a meaningful margin. The standard rule is that your LTV should be at least three times your CAC, which gives you room for all the other costs of running a business whilst still being profitable.

A subscription box app we worked on had average revenue per user of £127 over a twelve-month period and their CAC sat at £28, which gave them a healthy LTV/CAC ratio of about 4.5x. This made the funding conversation much easier because investors could see that every pound spent on marketing generated several pounds back, and that's a machine worth scaling. The math needs to work. Some apps in our portfolio have taken eighteen months to figure out the right combination of pricing, retention, and acquisition costs that creates positive unit economics. Understanding your app's cost structure is essential for creating realistic unit economics that investors will believe.

If you're pre-revenue, investors will want to see proof that users engage enough to potentially pay later. A productivity app we built launched free and tracked how many users were hitting their "aha moment" (creating their third project in the app), which became a proxy for future monetisation potential. When they eventually launched a premium tier, 23% of users who hit that milestone converted, which validated the hypothesis that engagement predicted willingness to pay.

Creating Your Funding Dashboard: What to Show and What to Leave Out

Your funding dashboard needs to tell a clear story in under two minutes because that's how long you get before an investor decides whether they're interested or not. This means choosing the 6-8 numbers that best demonstrate your growth trajectory and unit economics, then presenting them in a way that makes the story obvious without needing much explanation.

Build your investor dashboard in a tool like Google Data Studio or Tableau so you can share a live link rather than a static PDF, which shows confidence in your numbers and lets investors explore the data if they want to dig deeper

What Belongs on Your Dashboard

Start with your growth chart showing MAU or revenue over time with a clear upward trend (even if the absolute numbers are small, growth rate matters more in early stages). Include your key engagement metric whether that's DAU/MAU ratio, session frequency, or whatever best shows that users stick around. Add your retention curves for Day 7 and Day 30 cohorts. Show your unit economics with CAC and LTV clearly labelled. If you're making revenue, include your MRR growth chart with the gradient of increase visible.

What you leave out matters too. Don't include vanity metrics like total downloads or social media followers unless they directly tie to your business model. Avoid showing too many different cuts of the same data which just creates confusion. Skip any metrics that have been declining unless you can explain why that's not a problem. A food delivery app we built left geographic expansion data out of their seed round dashboard because it diluted the story...they focused on proving the model worked in one city first before talking about scaling to others. The key is building user trust and credibility through transparent, meaningful data rather than overwhelming investors with information.

Common Data Mistakes That Kill Funding Conversations

The fastest way to lose investor confidence is to show data that doesn't add up or to be unable to answer basic questions about your numbers. I've sat in meetings where founders claimed 80% retention but couldn't explain how they calculated it, or where the growth charts showed hockey stick increases that didn't match the absolute user numbers they mentioned earlier. These inconsistencies make investors wonder what else doesn't add up.

Mistakes That Raise Red Flags

• Mixing up registered users with active users and hoping investors won't notice the difference
• Cherry-picking date ranges to show growth whilst hiding recent plateaus or declines
• Calculating retention rates incorrectly by including users who never came back as "retained"
• Showing percentage growth without absolute numbers which makes small increases look bigger than they are
• Forgetting to account for seasonality in your data which makes growth look more consistent than it is

A delivery app founder showed investors a graph of 300% month-on-month growth but when asked about absolute numbers admitted they'd gone from 20 users to 60 users to 180 users. The percentage growth was real but the scale was too small to be meaningful. Better to show 50% month-on-month growth from a base of 1,000 users because that demonstrates you've found something that works at a meaningful scale. Another common mistake is not segmenting your data by acquisition channel...investors want to know which marketing efforts actually work so they can fund more of that. Understanding what drives social media conversions versus other channels helps you present a clearer picture of sustainable growth.

Your Data Story Needs to Match Your Growth Story

The numbers you show investors need to support the narrative you're telling about where your app is going and why now is the right time to invest. If you're pitching that you've found product-market fit, your retention and engagement data needs to back that up. If you're saying you're ready to scale, your unit economics need to prove that more marketing spend will generate profitable growth.

An app that helps freelancers manage invoices came to us wanting to raise 400 grand to spend on marketing, but their data showed that 60% of users never sent a single invoice through the app. That's not a marketing problem, that's a product problem. We helped them pivot the pitch to focus on product development funding instead, which was the honest story their data told. Six months later after they'd improved onboarding and activation rates, the marketing pitch made sense because the data showed users who got past setup became long-term customers. Sometimes implementing growth tactics like referral programmes only makes sense once your core product metrics are solid.

Your data collection system, your investor dashboard, and your pitch all need to work together to tell a coherent story. The apps that raise funding aren't always the ones with the best numbers, they're the ones where the numbers prove the founder understands their business and has a clear plan for what comes next. If your data shows problems, address them directly rather than trying to hide them because investors will find them anyway. This is where our experience building apps across different industries helps founders understand what investors expect to see in their specific market.

If you need help setting up the right analytics infrastructure or preparing your app's data for funding conversations, get in touch with us and we can walk you through what investors will want to see.