Startup or Ongoing Ad Network Financial Model
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Sometimes it may be hard to figure out where to start when doing an Ad Network financial model. Do you build assumptions for advertisers? or do you build assumptions for publishers? Do you do both and then try to match them somehow?
Well, an ad network at the highest level simply connects advertisers who want to buy visibility with publishers that want to monetize their content.
To me, the easiest way to show this connection was to drive the model based on 3 types of publishers. The user can define specs for each type. For example, one type could be 'desktop' and another could be 'mobile' while a third could be 'TV'. There could be all kinds, but I thought having 3 types of publishers was enough granularity without overwhelming the user, but still allowing for proper modeling flexibility.
So, this model lets the user define assumptions that result in some total amount of impressions. Then, total ad revenue going through the ad network is based on a percentage of impressions that are filled by advertisers and a CPM. A percentage of that will then flow as top line revenue for the network.
The assumptions used for each publisher configuration include: start month, start count, growth rate of count, impression start amount, impression growth per publisher, CPM, fill rate, network fee. All inputs are configurable over 5 years where applicable.
There is an input for 'average impressions purchased by advertisers per month, which will back into total advertiser count.
This model has strong clarity for the timing of operational start and exit if applicable. There is variability in the start month of each publisher type as well.
Cost of Goods Sold (COGS) is defined by up to 4 sections that vary from a hard coded percentage of revenue to a cost per publisher per month and/or a cost per impression.
Fixed operating expenses are granular enough to show G&A, S&M, and R&D with plenty of slots and a 'start month' input for each line item. One-time startup costs have their own area as well as future one-time capex.
Monthly and annual P&L details are displayed based on the assumptions. That rolls into a DCF analysis for the project as a whole as well as investor/owner pools. There is a high level executive summary for the project as well as plenty of visuals that show the resulting of all assumptions.
The excel model is fully editable upon purchase.
Startup or Ongoing Ad Network Financial Model
Available:
In Stock
$75.00
Sometimes it may be hard to figure out where to start when doing an Ad Network financial model. Do you build assumptions for advertisers? or do you build assumptions for publishers? Do you do both and then try to match them somehow?
Well, an ad network at the highest level simply connects advertisers who want to buy visibility with publishers that want to monetize their content.
To me, the easiest way to show this connection was to drive the model based on 3 types of publishers. The user can define specs for each type. For example, one type could be 'desktop' and another could be 'mobile' while a third could be 'TV'. There could be all kinds, but I thought having 3 types of publishers was enough granularity without overwhelming the user, but still allowing for proper modeling flexibility.
So, this model lets the user define assumptions that result in some total amount of impressions. Then, total ad revenue going through the ad network is based on a percentage of impressions that are filled by advertisers and a CPM. A percentage of that will then flow as top line revenue for the network.
The assumptions used for each publisher configuration include: start month, start count, growth rate of count, impression start amount, impression growth per publisher, CPM, fill rate, network fee. All inputs are configurable over 5 years where applicable.
There is an input for 'average impressions purchased by advertisers per month, which will back into total advertiser count.
This model has strong clarity for the timing of operational start and exit if applicable. There is variability in the start month of each publisher type as well.
Cost of Goods Sold (COGS) is defined by up to 4 sections that vary from a hard coded percentage of revenue to a cost per publisher per month and/or a cost per impression.
Fixed operating expenses are granular enough to show G&A, S&M, and R&D with plenty of slots and a 'start month' input for each line item. One-time startup costs have their own area as well as future one-time capex.
Monthly and annual P&L details are displayed based on the assumptions. That rolls into a DCF analysis for the project as a whole as well as investor/owner pools. There is a high level executive summary for the project as well as plenty of visuals that show the resulting of all assumptions.
The excel model is fully editable upon purchase.
