Welcome gamers and players,

today we will focus on calculating the Roi of User Generated Content.
Keep in mind the distinction I pointed out in the previous article [gamification #2].
Here I am talking only about what I called “Implicit UGC“. The kind of UGC’s I called “Explicit” can be any creative stuff anyone can do, taking inspiration from your game. So this is more likely field of social and viral marketing, rather than gamification.

So, you have to keep the focus upon the UGC implicit in your game: you can directly control it. How? By your game, obviously!

A last introductory note: my indication here need some game-designing skills: you have always to remember that we are talking about gamification, which means we are talking about games. Without a solid game, your calculations are worthless, and so is your gamification.

User Generated Content

Usually considered as Revenue (but very hard to be evaluated), it could cause you to sustain additional Cost

Tips about Calculation

To calculate the impact and usefulness of the UGC, you have to estimate at first  your technology infrastructure to collect data, your refreshing rate and the other “technical” component of your data collection activities. These elements worth: even the best written game is worthless if you don’t collect what your players create. You have to evaluate very carefully what kind of interaction you want in your game, and measure it.

γ [Data Collection] – The first item to define, so has to be a factor to control the technological impact upon revenue. It could be written like x[Data Collection Capabilities] (which means that it varies from 0 to 1), and it should be a “sum” of Data Quality, % of erroneous data, % of data loss and so on. This should includes the percentage of plays you could monitor, or the percentage of plays make online.
If, for example, you know that your infrastructure could collect 50% of the data with a 1-month delay time, and your project last for 6 months (and you need the UGCs in real-time), you take a direct 59% loss on the UGCs revenue (which means a x0,42 factor – ask if you need the math of this example).
None, except you or your IT wingman, could lead you through the right assignment of this factor. You can think to avoid that: “I can value by myself, after, how to fix the revenue rate”. “I’m experienced, I can take this measurement later”.
In fact, you can’t. There is a very good, mathematical and logical reason to be absolutely sure of that. And I will write it in the next post.

δ [Game Dominance] – This factor is known to everyone who ever talk about gamification. In fact, within the border of actual, poor gamification standard, this factor is all you need to calculate the Roi of your project and start gamifyng. This factor values the extra-time and resources your average player will put in gaming, considered apart from a “normal” game. It is added as +[Game Dominance] to the value you use in calculating income from a single game.
In fact, taking a measurement of how much your game likes, how many times people play it, how many times they prefer your game instead of another, will seem impossible. And probably it is. But we are not looking for a sharp measurement: we’re looking for a probability, a prediction. And we can make prediction of how your game will spread.
The Game Dominance, in fact, is the core of calculating Roi in gamification. If you make a game that is played instead of others, you win. Keep an eye, however, on your goals. Many game at high-dominance get a very rapid attention curve decrease: which can be uninfluential o very important to your project. Basically it’s all a matter of time: what is your temporal limit?
Game Dominance is composed of many different tendencies: putting them all together need a deep knowledge of the game market, of your game mechanics and hand full of self-criticism. But, in fact, simply listing all the value you think are important.
δ1 [Time Consuming] – How long is the average game? More it last, more you are engaging your customer, less it last, more are your leaving ground for competitor. Be careful: the longer is the game, lesser number of games will be played. Do you want your games be fewer but richest, or quicker, briefer and more frequent?
δ2 [Real Time Related] – This is a very crucial point in gamification project. Is the time in your game the same as reality? Here I mean not only web and browser-game wich work on real-time clock (like OGame), but also board game or card game which involves a measurement of time to base the game itself (think about Pictionary). The real-time clock for web and browser game is a really powerful tool to engage the users, and the predetermined length of a game is useful to keep under control the duration of plays (see Time Consuming, before). Both are value add to your game, but be careful to not exaggerate (I quit OGame, for example, because I cannot be awake at 4,30 a.m. to reroute my fleet in that split second and avoid destruction).
δ3 [Average Game Length] – Obviously, the average length of a game impact on the players engagement. What is interesting to pinpoint is that, in fact, the more the game will last, the better it is. You have to avoid game too long, obviously, but in term of gamification, if a game works, the more it will last, the better it is (engagement and all this kind of parameter will grow up with time). Be careful when you consider your game length, however: having shorter game and a single long game could be equivalent or not, depending on the UGCs you need (the UGCs you’re seeking is the final output of a full game? They are the dynamics and data players create during a game? It based upon players choices? Different answers mean different strategies).
δ4 [Game Replicability] – What are you seeking from UGCs? Anything you are looking for, you prefer structured data, right? Then, if your game allow to recreate very similar conditions and actions from players any time they play, this is a point you score in term of UGCs.
δ5 [Number of Players] – Obviously, if we are talking about UGCs, more is better. More players your game support, more useful UGCs data you will collect. Think about the entropy of the game, however. In your game systems player are influencing each others? And in terms of output this is good or bad? You have to set up number of players accordingly to this kind of evaluation.
δ6 [Game Variety] – Starting from the same frame (see Game Replicability before) how much will differ the games? More variety you have, more different data you collect. In fact, your game should have different “winning strategies” and not a single algorithm that allow to win: if this applies, then you will have, with time, a copy/paste UGCs of the best strategies to win.
δ7 [Game Learning Curve] – The lower the curve, the best it is. More players (“Eh, it’s an easy game”), and good data from the very first plays. In any game, indeed, the first play is to “test” the game and learn it. Probably those will generate non-useful or erratic UGCs, so a well-balanced learning curve will help you to take the best from your players.

Tips about UGC as a Cost

The simplest of the factor we’ll face, UGCs could be a cost only in 2 ways:

1. Some UGCs will make bad marketing for your game.
2. Some UGCs (explicit) work even better than your game, resulting in a point 1 (bad marketing: someone else write your game better than you) and a loss of players.

Both these situation applies more easily to explicit UGCs, and are very, very difficult to foresight. So I don’t give you math to calculate it: simply think about it, and make that these situations simply do not happen!

Some link about what are and what to expect from UGCs

This time, I’ve got very little links. Because, in fact, there is no case history about explicit gamification as I intend. If you know some history case, please send it to me. However, there is a couple of interesting articles..

A brief presentation of Margaret Wallace, Ceo of Playmatics (on Gamification in general)

The allkpok case study – by Colin Cheng