Economics of an Ad Network: 5 Year Financial Model

An ad network connects ad inventory from publishers to advertiser demand. It can be considered a marketplace in most cases. By connecting these two groups, the ad network provides value and takes a fee for such value. This model was designed to show the expected financial performance of an ad network based on assumptions related impressions / CPM / fee percentage.

$45.00 USD

The template will be immediately available to download after purchase. This template is included in the SaaS Financial Model template bundle as well as the industry-specific financial model bundle.

ad network

The model is driven by defining up to three types of publishers. The following attributes are available for configuration in each type of publisher, which will drive impressions and revenue:

  • Start month
  • Starting count
  • Monthly compounded growth rate of count over 5 years (can change each year)
  • Starting monthly impressions
  • Monthly compounded growth rate of impressions (can change each year)
  • Average CPM per year
  • Percentage of impressions that are filled by advertisers (can change each year)
  • Fee rate that the ad network charges on ad revenue facilitated by the ad network
The above assumptions allow for varying configurations. For example, you may have averages for desktop based publishers, mobile publishers, and offline publishers. There could be infinity types of ways to do this, but the goal of this model was to provide enough granularity to plan out different kinds of publishers with varying CPM rates without being too overwhelming to the user of this financial model.

One of the biggest things I liked about this model is that it did require a matrix style logical structure in order to know the amount of impressions produced by publishers over time and being able to isolate each monthly cohort to show that impressions can grow for a publisher over time based on the age of a publisher on the ad network.

Beyond revenue logic, there were plenty of assumptions for operating expenses. The user can define the start month and monthly cost by each cost line item over 5 years. 

For cost of goods sold (COGS), there are up to 4 way to define it. The user can use all 4 or just 1 or some amount in-between. These include being able to flat out define it as a % of revenue and zero everything else out, or you can define COGS by cost per publisher per type, cost per impressions by publisher type, and/or a hard coded value for COGS for each type that is not directly tied to any other reference.

The goal of this model is to make it useful and clear. Some of that means calling out as many calculations as possible so that even further analysis can be done. This means not putting too much information into a single row. 

One interesting data callout here is the average CPM of the network. 

There are visuals for those metrics and a wide range of other financial items.

The user has the ability to define the source of funds (debt, investor equity, owner equity) as well as the exit month if applicable and sales revenue multiple for valuation. 

A DCF analysis exists for the project as a whole and for the investor/owner distribution legs if applicable as well as visualizations therein. A high level executive summary was built to show specific items that are more akin to a financial statement. 

Other key metrics exist for all pools: IRR, NPV, Equity Multiple, ROI

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