CityVille’s Numbers May Be Record Breaking But Zynga Faces Harsh Reality

Social gamers might be excited by Zynga’s CityVille hitting a record number of users. Investors might by excited by CityVille’s potential revenue. Both may be interested in the impact CityVille could have on the virtual goods market. With a record number of users and revenue for a single game, CityVille’s success might give you the impression that all is well in the social network game world.

A record-breaking user base may not mean hitting a revenue  jackpot for game companies like Zynga due to several key issues:

  • The number of unique users across all games
  • The time between user base peaks in major game hits
  • The unique user spend per month

Below are two charts for a sample game company with three hit games labeled A, B, and C. The left chart, Games Have Short Overlap, shows a user base or revenue curve that assumes a fixed percentage of users spending money on the free social network games. The right chart, Example Revenue Total, shows a cumulative revenue curve based on the same three games and the assumption of a fixed spend per user per game.  The game model has “record” new highs for each game to provide some approximation of the impact of new games with increasingly higher player totals.

Basic Model, Games with Short Overlap

Basic Model, Games with Short Overlap

Basic Model, Example Revenue Total

Basic Model, Example Revenue Total

This model represents how the rise and fall of each game can lead to uneven and irregular revenue. Game users for each game are unique, a weakness that could make this curve too optimistic.

If the users were unique, and each user spent a fixed amount per month, then the revenue could be linearly summed to yield the revenue curve on the right. For advertising where a fixed percentage of users click on ads this expectation is generally true. However, playing more than one game isn’t uncommon for social network gamers.

Chasing After Revenue

Another issue to look at is the time overlap between game hits. Games have typically been a hit-driven business, with the time between hit games a major source of uncertainty. The fewer and farther between hits, the bigger each hit has to be to even out revenue flow. With this reality in mind, I modified the previous charts (see below) by shortening the time between hits, but keeping the same peaks of users. I also used the same rates of user increases and decreases since rates largely impact the horizontal timeline.

You’ll notice in the following charts that the points between the peaks of A and C have a more regular shape in a more believable linear direction, slowly climbing up and to the right.

Aggressive Model, Games with Longer Overlap

Aggressive Model, Games with Longer Overlap

Aggressive Model, Example Revenue Total

Aggressive Model, Example Revenue Total

Connecting Users Curves to Revenue

What do these models suggest? The timing or spread of hit games can yield an uneven or even irregular user curve. This outcome can lead to unstable revenues if each user in each game was unique, did not play other games, and spent a fixed amount of money each month. To make matters even more challenging, consider the anecdotal  evidence that active users usually play two to three games at the same time each month.

This behavior means that the total unique user curve  will not enjoy the steeper peaks of the Basic Models shown first. The record user numbers may represent borrowed users who play two to three games. Assuming that users tend to have fixed budgets (e.g., $30/month for games vs. $30/month for each game), the revenue curve tends to shift from one of increasing to the right to decreasing to the right.

In the Decreasing Models below, I use a 80 percent unique rate for the second game and 60 percent unique rate for the third game.

Decreasing Model, Unique Users

Decreasing Model, Unique Users

Decreasing Model, Total Revenue

Decreasing Model, Total Revenue

What’s Next for Social Gaming

Where does that leave game companies like Zynga with their record user numbers? After they pat themselves on the back (and they should for a job well done) there’s the realization that they face the same hit-driven realities of established game companies like EA.  Since most social network games are “free to play,” game companies can’t really affect the player overlap between games, but they can continue to use them as a feeder system into new games. Making hit games is a tall order, so Zynga and its competitors should continue to use their analytic smarts to build games that engage users and increase the odds of creating a new hit.

The last item to consider is the revenue per user, which remains central to turning that downward sloping curve back up and to the right. From personal experience, social network games have started to take time away from other activities and not just gaming. As such, there’s an opportunity to capture the discretionary revenue from the  indirect competition that currently captures those entertainment dollars. Doing so may require some aggressive positioning, and it may take some time, but unless they find a way, a revenue curve with a downward slope may prove growth limiting.

Based on my personal experience with friends and relatives playing these social network games and the models I’ve created, record user numbers for social network games are only a start. Indeed, creating hits and attracting a large user base may be the minimum requirements for keeping a social network game company in the black. Without the up-front revenue of a retail store or downloaded software, total users per game don’t directly translate into big revenue gains when users tend to spread their revenue over multiple games. The monthly recurring revenue potential is there if the social game companies can capture indirect competitive entertainment dollars.

About Duane Kuroda

Business ninja, deal hunter, Internet marketer, and technology fiddler obsessed about growing companies and launching products. Currently at Peerspin, Duane’s past lives include Vice President of Marketing roles at companies leading micropayments, Internet video, and online communities as well as research and consulting for mobile advertising. Duane has spoken at conferences including Digital Hollywood and Digital Video Expo on topics covering monetizing online content and online video, has appeared on TechNowTV and KNTV, and has been quoted in various magazines. Follow Duane on Twitter: @dkuroda.

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Business ninja, deal hunter, Internet marketer, and technology fiddler obsessed about growing companies and launching products. Currently at Peerspin, Duane's past lives include Vice President of Marketing roles at companies leading micropayments, Internet video, and online communities as well as research and consulting for mobile advertising. Duane has spoken at conferences including Digital Hollywood and Digital Video Expo on topics covering monetizing online content and online video, has appeared on TechNowTV and KNTV, and has been quoted in various magazines. Follow Duane on Twitter: @dkuroda.

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