Instructional Video:

Revenue Assumptions (Dynamic start month input included):

Three income stream configurations (recurring contracts, volume-based fees, one-time revenue)
Up to 4 recurring revenue pricing tiers, each with the option for varying contract length and retention.
Define the expected transaction volume facilitated per customer per month and the fee earned if applicable. An example situation of this fee would be if the AI-based platform is a financial advisor that lets users buy and sell securities. The platform may earn a fee on the transaction volume of its customers.
Define the number of new customers that have a one-time fee and what that fee is for each tier.
Each type of revenue is options.

Acquisition Assumptions (Dynamic start month input included):

Paid Traffic – Configure ad spend per month per tier and average cost per customer acquisition (CAC) per tier. Also, there is a global ad spend with a CAC input and the user can define the percentage of those customers that end up in each tier. There is also an assumption for ad spending for the free customer pool if this is relevant.
Organic Traffic – Define starting monthly organic traffic and monthly growth over time. Of this traffic, configure the conversion rate to a free pool as well as directly to a paid pool. Define the conversion of free pool customers to paid customers each month. The free pool has its own retention schedule.

Customer Retention:

Each of the four customer tiers has an input for the expected customers retained at renewal. The model assumes be default an average decay of customers at each renewal period based on this input.
If you wish to override this assumption, simply go to the ‘Validation’ tab and manually define the expected percentage of customers that you estimate to remain after each renewal. This is adjustable for each year and for the free pool.
There is an assumption in each tier to account for an increase in the average contract value. This makes it easier to model negative churn.

Scaling Costs:

Both customer service reps and sales reps have their own ratio-based assumptions for how many the platform needs in order to support existing and newly added customers. If you don’t want to scale reps this way, simply 0 out the assumption.
There is an input for cost per month per customer that flows to cost of goods sold (COGS) as well as two different assumptions that define costs as a percentage of total revenue. One set is for general and administrative, the other is for COGS. A final input for COGS can be based on a defined annualized cost that is adjustable each year and has an adjustable start month.

Fixed OPEX Costs:

To account for executive salaries, legal costs, and other operational overhead, there is a robust section for these items. It is split into General and Administrative, Sales and Marketing, and Research and Development. Each section has a dynamic start month for each cost item and can be adjusted each year. This input section is designed to be an annual input.

Other Assumptions:

The user can account for a terminal value (optional) that is based on a trailing 12-month revenue multiple from the selected end month of the forecast.
There is a cap table to define how much of the minimum cash requirement is coming from inside vs outside investors as well as their share of the profits.
I also included a CAPEX schedule to account for the purchase of depreciable items if applicable.

Output Reports:

Monthly and annual Income Statement, Balance Sheet, and Cash Flow Statement.
DCF Analysis, IRR, ROI, and Equity Multiple metrics.
Annual executive summary.
Lots of visualizations for KPIs such as customer lifetime value, CAC, LTV to CaC, churn (in $), and more.
The pro forma tabs drive down to EBITDA and cash flow.
There is an option to collect revenue from contracts that are longer than 1 month up front or evenly over the contract period. This will effect cash flow requirements.

This model is also included in the following template bundles:

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