Data-as-a-Service Financial Model - Includes Financial Statements

Description
If you are looking to provide data to customers for a recurring monthly fee, or a pay per API use model, this template is going to help you. I did quite a bit of research to get down to brass tax assumptions that specifically relate to a data-as-a-service (DaaS) enterprise.


The general business model:


Either acquire and re-sell or grant users access to valuable data streams or one-time data downloads of various types. This type of data provider is going to have heavy investments in cloud infrastructure as well as bandwidth. Data generation itself could also be expensive. The model lets you account for all of these revenue streams.


Template Assumptions:


For customer acquisition, the model has up to 6 paid acquisition channels that drive off of ad spend / month and average cost per customer acquisition. There is also an input configuration for organic traffic / conversions of that traffic to new customers.


Once a customer is acquired, the user defines the percentage of new customers that sign up to each customer tier. There are up to 6 customer types that are configurable based on various monetization strategies.


These are customers that sign on for recurring contracts that last for 1 month or more (dynamic input per type). When a customer signs on, there are assumptions for how these customers interact with your DaaS. It could be based on the estimated API calls per customer per month and the price per API call. Or, you can define the average amount of data downloaded per month per customer and charge based on that. Or, you may be selling one-time downloads of data (this would be far less volume, but far more valuable per file).


Another very important input for each customer type is their retention schedule. For each type, the user can define the average percentage of customers that remain after the initial signup and this can be defined over 72 months and will apply as new customers join. I also added an option to offer a free first 'n' number of months for promotional strategies. For that, you can define the percentage of the base price that is paid in the first few months, or it could just be the full 100%.


If you don't want to charge per API use or amount of data downloaded, you can simply charge each customer type a fixed monthly fee (or that could be in combination with the other monetization options). This would be more like what you see with software-as-a-service, but the idea translates pretty good.


Next up are costs. There is a separate section for CAPEX items, which will be any spend for servers and general infrastructure. This is considered a cost of goods sold (so the depreciation expense in this case will hit COGS and is a non-cash item). You also have variable costs related to data transmission. The is something that can be defined for each customer tier, so as they consume data, the DaaS provider will incur costs based on this activity. I broke it down into a few different inputs, there is a flat cost per customer per month, a cost per API call, a cost per GB downloaded, a cost for one-time downloads per GB, and data generation costs if applicable. 


Also, there is a cost to store the data that your customers are accessing. I put in up to three types of data storage, each with a varying cost per GB per month. This could be for fast storage, slow storage, or some other third speed.


There is a robust fixed expenses schedule to account for things like corporate overheads, managers, executives, legal fees, rent, and other things required to keep the lights on. In this section, the user can define the various cost descriptions, their start month, and the monthly cost in each year.


I also put in a section for other one-time non-depreciable startup costs, a cap table to define how the minimum equity investment is sourced, and an option to use debt for some of the startup costs.


Upon exit, the user can choose to display an exit value or not, if so, then there is a multiple applied to the trailing 12-month revenue. I also added a sensitivity for various exit values per different multiples.


All of these assumptions come together to produce monthly and annual Income Statement, Balance Sheet, and Cash Flow Statements as well as a DCF Analysis, IRR (for the project, investors, and owners/operators), and a monthly and annual pro forma detail.


This template is also included in two bundles:
- All Models Bundle: https://www.eloquens.com/tool/P8Y4TX4v/finance/financial-forecasting-models/financial-models-120-useful-and-usable-logic
- SaaS / Subscription Models: https://www.eloquens.com/tool/wmyQI0eE/finance/venture-capital/the-complete-venture-capital-bundle