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Gamification Tenet #4: You Must Change Faster Than Your Players

Lithium Alumni (Retired) Lithium Alumni (Retired)
Lithium Alumni (Retired)

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Before I begin today, I just have a quick announcement. For those of you who are interested in applying some of the gamification ideas I talk about, I have good news. I’ll be presenting a webcast on Oct 29th about transforming your digital customers—beyond engagement. Today, many brands understand the importance of engagement, and some social savvy brands are getting the hang of it. But what’s beyond engagement and how do you get there? This webcast will show you the next phase of the social media revolution—beyond engagement—and how to get there with the help of properly designed gamification. Please register here to attend.

 

OK back to today’s topic. We all know that Gartner identified gamification as an emergent technology in its 2011 Hype Cycle report. But perhaps not everyone knows that they also published a report in 2012—the very next year—suggesting “80% of the currently gamified apps will fail due to poor design.” After all, gamification is not that simple. There are many nuances that could undermine its success. So how can we design gamification better, so we don’t repeat the mistakes of those other 80%?

 

Well, we already have 3 tenets that could help you increase your odds of success in gamification:

  1. Have a Granular Understand of Your Desired Behavior
  2. You Can’t Change a Behavior that You Didn’t Track
  3. Always Watch Out for the Unintended Consequences

 

Today, let’s talk about the 4th tenet.

 

The Better it Works, the Faster You Must Change

In business, you probably heard this many times: “if it ain’t broke, don’t fix it.” This is because most people probably believe things in the business world operate under some sort of inertia. If you don’t do anything, then everything will just stay the same. So it’s very tempting to apply this adage when implementing gamification programs, especially in business applications—if it’s working, don’t change anything.

 

The problem is that gamification will always work in the short term. Even if you have created a very silly or simple game, there will still be plenty of people who will play with you for a few minutes. But very soon, these people will realize how boring the game is, and they will quickly stop playing. This is why gamification is so dangerous, whether you design it perfectly right or completely wrong, they will always work for a short time, giving you the false impression that things are working. But after a while, it will lose its efficacy while leaving the player a sour taste because they’ve wasted valuable time on a seemingly pointless activity. Not only is this ineffective, it’s counterproductive, and could even lead to gamification resistance and backlash.

 

However, we also know that no games last forever. Gamification is no different. There isn’t a single gamification tool that will work forever. Although no one knows precisely how long a gamification tool will work, because that’s context sensitive and problem specific, the gamification spectrum can help us get a ballpark estimate. Through the gamification spectrum, we learn that tools that are easy to achieve tend to work faster and engage a larger population. However, because these gamification tools are easy to achieve, they are easier to master and therefore people also get bored of them faster.

 

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So for gamification, if it’s working now, you need to start thinking about the next game. In fact, the faster and better it works, the faster you have to change it to continue to keep the players engaged. If you don’t have the next game ready when your players get bored, you risk losing those players for good.

 

This is what happens to gamified apps (e.g. FourSquare), as well as games (e.g. Draw Something). Their adoption rates are extremely high because of the game mechanics they employed. Draw Something reached about 50 million users in just 50 days. However, they didn’t have next game ready. So their players are just playing the same game over and over again. Consequently when their players get bored, they leave for good. As a result, their churn rates were also extremely high. Do you know anyone still playing Draw Something now?

 

On the contrary Angry Birds also has an amazing adoption rate—reaching ~50M in 35 days. The difference is that Angry Birds has many levels (which we discussed previously) and each new level is like a new mini-game within the bigger game. These new mini-games (a.k.a. levels) are ready, waiting to be unlocked. That is why Angry Birds didn’t suffer such a steep drop of players when they mastered the levels.

 

So if your gamification is working very well, congratulations. Now get moving, because you have more work to do! If you don’t already have it, you need to start crafting next game and do it fast. Game-on folks!

  


 

Michael Wu, Ph.D.mwu_whiteKangolHat_blog.jpg is CRM2010MKTAWRD_influentials.pngLithium's Chief Scientist. His research includes: deriving insights from big data, understanding the behavioral economics of gamification, engaging + finding true social media influencers, developing predictive + actionable social analytics algorithms, social CRM, and using cyber anthropology + social network analysis to unravel the collective dynamics of communities + social networks.

 

Michael was voted a 2010 Influential Leader by CRM Magazine for his work on predictive social analytics + its application to Social CRM. He's a blogger on Lithosphere, and you can follow him @mich8elwu or Google+.

About the Author
Dr. Michael Wu was the Chief Scientist at Lithium Technologies from 2008 until 2018, where he applied data-driven methodologies to investigate and understand the social web. Michael developed many predictive social analytics with actionable insights. His R&D work won him the recognition as a 2010 Influential Leader by CRM Magazine. His insights are made accessible through “The Science of Social,” and “The Science of Social 2”—two easy-reading e-books for business audience. Prior to industry, Michael received his Ph.D. from UC Berkeley’s Biophysics program, where he also received his triple major undergraduate degree in Applied Math, Physics, and Molecular & Cell Biology.