One of the reasons games are on an upward trend is that the consumer cost per hour is such a high value–games, particularly subscription and virtual-goods social games–are a lot less expensive than many other types of entertainment. Here’s a breakdown:
- Borrowing a book from library: free (taxpayer supported)
- Playing a freemium/social game: free to pennies/hour
- Cable Television ($71/mo, 153 hours/person/mo., 2.54 people/household): $0.18/hour
- Playing World of Warcraft 10 hours per week: $0.35/hour
- Playing Call of Duty for 30 hours ($60 retail): $2/hour
- Seeing a 2-hour movie for $7.95: $3.98/hour per person
- Upper Bleachers Red Sox ticket ($12) for a 3-hour game: $4.00/hour per person
- Average US Family Vacation (AAA data: $250 per day): $10.41/hour
- 2-hour Broadway show: $50-$150 per hour
It’s hard to beat the cost per hour of games, which is one of the reasons games are growing in popularity: they’re cost-competitive with television while being far more immersive, social and engaging. And yes, the 153 hours/month is the average number of hours watched per month for people in the United States — gamers, as a group, probably spend far less time in front of the television.
One thing the above chart excludes is the cost of hardware, but you’d need to amortize that across all of your uses. For most people, this will come down to pennies per hour for computer usage (likewise, the television usage doesn’t include the cost of the TV or home theater). Similarly, I didn’t include energy and transportation costs. For a computer game, the energy costs are going to be minimal (pennies per hour). For some of the types of entertainment, the energy costs could be rather substantial–driving to a movie could easily drive up the cost of seeing the movie by double (or more!), if we use the IRS’s rate of $0.50 per mile for fully-loaded automobile transportation costs.
Sources for Data Used Above
I’ve put together an Excel spreadsheet to help model growth curves within social games and social applications. I thought I’d put it into the wild and let it benefit from the “wisdom of the crowds” to make it even better.
Because social games and applications on social networks like Facebook fluctuate daily (if not more often!) the model breaks every individual day into its own cohort. This is because each individual cohort will experience its own growth (due to the new users within the cohort introducing the application to their friends) and decay (as individuals in the cohort stop playing). These growth and decay curves happen along a normal distribution. Because of the complexity of this model, it means that the spreadsheet is 365 columns wide and over a thousand rows–so on some computers, it will load a bit slowly.

Here are the main input variables you can manipulate:
- k-Factor, which is the rate of growth for a social application based on how man people, on average, a product will spread to from one other person (the concept is drawn from infection rates within epidemiology).
- The rate of spread that the k-Factor reveals isn’t enough on its own; you also need to know how fast it is occurring, so the model also allows you to manipulate the mean time to spread to another person.
- Likewise, you can manipulate the mean time to remain a customer, which is also central to measuring how many total active customers you have.
- There are other variables you can play with, such as revenue/user, reinvestment of revenue in customer acquisition costs (i.e., advertising),
What this doesn’t attempt to do is establish a ratio between daily active users (DAU) and monthly active users (MAU). Clearly, that’s an important set of information for determining the engagement level of an application or game’s customers, but it’s probably dealt with better in a separate model. For purposes of this, you can think of the DAU/MAU ratio as a determinant of the assumptions used for revenue and mean time to remain a customer as used in this model.
Comments are welcome and appreciated. If anyone has helpful criticism, feedback–or even if you want to modify it and share your evolved version with me, I would be happy to post updates here.
Download the spreadsheet:
(Other helpful spreadsheets, for those interested: The Excel Nexus)