$75.00 USD
Recently updated with financial statement reports (Income Statement, Balance Sheet, Cash Flow Statement) and a capitalization table.
This template has 3 revenue drivers:
- Ad revenue (driven from expected new downloads that don't pay for ad removal)
- Ad-free service revenue (driven from expected new downloads that do pay for ad removal)
- In-App Purchases (a percentage of all active users will engage in this revenue stream)
- The in-app purchases can be treated like recurring revenue if the user is trying to model subscription services. The business logic / churn works in the same way.
I have never done just those three revenue streams before. Here is how the revenue assumptions work: User growth is driven from two main sources. The first is ad spend and a defined CPA. Based on that CPA, you will acquire a certain number of users. The second is organic i.e. search traffic and things of a viral nature (word of mouth/link sharing). A certain % of that traffic will download the app.
Based on the two ways users are acquired, a whole swath of assumptions take into effect to determine revenues.
For in-app purchases I made up to five slots just to give it a little flexibility. Most apps would probably boil their average user spend per month on in-app purchases to a single number, which you can do with this model. However, those assumptions are not mutually exclusive and you can have different avg. spends per month and different percentages of users that spend each amount per month.
One of the more important assumptions I decided to do was a retention rate, instead of an average monthly churn rate. They are different and the monthly churn rate is actually derived from retention rate. Now, you can define the average amount of years you think a user will remain active and based on that, there are a few matrix tabs that do all the complicated logic to figure out how many users remain over time vs. how many are added per user acquisition assumptions. These things are actually a great way to articulate the aspect of having users that may leave over time.
The fixed expenses are pretty standard for what I normally do and I did add logic for corporate income tax, depreciation, and payroll tax/benefits.
There are plenty of visuals and I specifically took a bit of time to try and do some new things for this kind of business model. I combined some of the key metrics into a single chart as well as showed them separately. It gave some cool overlays.
General SaaS KPI outputs include LTV, CaC, months to pay back CaC, LTV to CaC ratio, monthly churn, and more.
You have assumptions for the potential of debt raising from a traditional bank as well as raising money from investors and then the default cash source is owner/operator equity. There are assumptions for the exit value and everything that happens on the exit (like repaying any debt that exists on the exit month). Also, the exit multiple is based on EBITDA.
I have built a DCF analysis for the project and for the investor and owner/operator legs, which shows everything from IRR to NPV and equity multiple.
For pricing help, see this SaaS pricing simulator and for ongoing forecasting check out this SaaS rolling revenue forecast.
More Subscription / Membership Recurring Revenue Financial Models:
- B2C SaaS Model for AI-Powered Platforms
- SaaS CFO Dashboard
- Data-as-a-Service (DaaS)
- Function-as-a-Service (FaaS)
- Subscription Box
- B2B/B2C SaaS with 3 Pricing Tiers
- Marketplace
- 5 Tier SaaS Driven by Traffic Conversion
- Freemium
- Customer Cohort Modeling (historical data analysis)
- Marketplace + Subscription
- Product + Service Subscription
- SaaS Pricing and Margin Simulator
- Product-as-a-Service (PaaS)
- Basic 4 Tier SaaS with One-time Onboard Fee Option
- Security Monitoring Service: 3 Tiers
- Ratio-Driven SaaS
- LaaS - Lending as a Service
- Property Management Business
- Professional Services Firm / Talent Agency
- Mobile App / SaaS Ad Spend Guide
- SaaS MRR Calculator
- SaaS Rolling Revenue Forecast
- Ad Network
- Car Wash - With Membership Option
- Private Golf Course - Membership Fees
- Customer Spend Patterns