Revenue model for cooking app


Published on

Statfords University project. Venture Lab 2012.

Published in: Technology, Business

Revenue model for cooking app

  1. 1. REVENUE MODELfor an iOS (iPhone/iPad/iPod Touch) cooking application
  2. 2. The mobile appecosystemAccording toGartner, worldwide mobile apprevenue exceeded $15 billion in2011.To monetize free apps, one canuse in-app advertising, in apppurchases, or a freemium version. The predictions for the mobileadvertising space are to hit $5.4billion by 2015 in the U.S .
  3. 3. Crucial concepts to understanding mobile advertising: eCPM (Effective cost per mille): The revenue the developer receives per every 1000 impressions. CTR (Click-through rate): This is obtained by dividing the number of users who clicked on an ad by the number of total impressions. The primary contributor to a high CTR is the relevancy of the ad and the ad placement strategy. In order to increase the relevancy of ads, the campaign should be of a premium and local nature: You want to display ads to users in their native language, and the topic of the ads should be relevant to the type of app in which the ad appears. In terms of the ad placement strategy, the location and format (text vs banner) of the ad also have a significant effect on the overall CTR. For this, it is important that you work with a company that will walk you through the process following the integration in order to maximize the effects of the ads. Global Fill Rate: The percentage of the total ad inventory that is populated by paying ads. Due to many different factors, in some instances ads will either not appear at all, or a “house ad,” essentially a self-promotional ad, will appear in its place. If your app has a 100 percent global fill rate, out of which 60 percent are house ads (a common number in this case), you are essentially leaving that 60 percent of your potential revenue on the table. In fact, a lower fill rate with all “paid ads” is more effective than a high fill rate with house ads. So don’t be misled by a high fill rate; the paid ads are the only ones that count.
  4. 4. To estimate the revenue model we should calculate:• conversion rate• partial CLV• eCPM• fill rate• how much time a person who doesnt convert spends using our app• and what percentage of the install base is network connected
  5. 5. The average conversion rate for the entire mobile apps industry is around 10%• Let´s take 100,000 downloads as the original amount• 100,000 * 0.1 = 10,000 converts
  6. 6. Now we need to calculate CLV (customer lifetime value)• The most simple CLV is how much the person pays for the premium version of our app (or the average spend on in-app purchases) plus the value of the advertising they are served.• How long is a user considered a customer? At some point theyll get tired of your app and stop using it. Lets say they use it for an average of 3 weeks. During those three weeks, they use it for an average of 15 minutes a day.• 7 days a week * 3 weeks * 15 minutes/day = 315 minutes.• So a customer uses your app for 210 minutes while theyre a customer.
  7. 7. How many ad impressions did we serve them?1) Lets assume a 100% fill rate.• For an ad display to count as an impression, it has to be up for 30 seconds, so thats 2 impressions per minute.• 315 minutes * 2 impressions/minute = 630 impressions.2) Lets assume $3 eCPM• 630 impressions / 1000 (CPM is per 1000) * $3 = $1.89
  8. 8. How much were we paid for those impressions?• Lets assume $3 eCPM• 630 impressions / 1000 (CPM is per 1000) * $3 = $1,89• So we could make $1,89 per customer serving ads.• There were 10,000 converts, but not every customer is network connected.
  9. 9. How many of those devices are network attached?• Lets use 70%.• 10,000 converts * 0,7 * $1.89 per convert = $13,230
  10. 10. Then…• Let´s calculate the other 90% of the average conversion rate  100,000 * .9 = 90,000• Lets use the same 70% of the network attached devices  90,000 * 0.7 = 63,000
  11. 11. How much time did they spend evaluating the app?• If we assume that all of the non-converts just installed, tested, and deleted the app, lets say 6 minutes.• We remind you that for an ad display to count as an impression, it has to be up for 30 seconds, so thats 2 impressions per minute.• 63,000 * 6 = 378,000 minutes * 2 impressions/minute = 756,000 impressions.
  12. 12. If we get 100% fill rate for ads and our eCPM is $3. Weve served 756,000 ads. So...• 756,000 / 1000 (CPM is per 1000) = 756 * $3 = $2,268 (or about $0.09 per download).• So from the original 100,000, those 90,000 that downloaded, tried, didnt like, and deleted the app you made $2,268.
  13. 13. And then converts + non-converts:• $13,230 + $2,268 = $15,498• So from 100,000 downloads we would make $15,498 in ad revenue in this scenario (about $0.15 per download).