This model was built to forecast the required initial investment and resulting operating income / burn over a 5 year period for an ad network. In general, an ad network connects publishers that want to monetize their content and advertisers that want to spend money to promote things that they are trying to sell or draw attention to.
In my opinion, the best way to model this was to show the supply side (publisher impressions) and the percentage of those impressions that get filled over time. I approached this model a few different ways, but in the end that was the most stable and logical way to figure out potential revenue that flows through the network and the fee that the ad network itself takes.
There are three publisher types that can be configured in the following ways:
Average Monthly Growth (varied per year)
Average Monthly Impressions
Average Monthly Impression Growth (varied per year)
Average CPM for Publisher Impressions (varied per year)
% of Available Impressions Being Filled by Advertisers (varied per year)
Average Ad Revenue Share Percentage Retained by Network (fee rev.) (varied per year)
Costs are able to be modeled based on a few dimensions. The first is general fixed operating expenses, defined by start month and cost amount (varied by year). The second is based on each publisher tier and they have their own cost of goods sold based on a per tier basis and a per publisher per tier basis as well as COGS based on a direct percentage of revenue.
Final results are displayed in a few different ways and include:
Executive Summary (annual high level financial forecast, IRR, ROI, equity multiple, and visuals)
Distributions (DCF Analysis for project level and investor / owner level)
Visuals (12 total visualizations)
Monthly and Annual P&L detail that drives down to EBITDA and Cash Flow before taxes