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Gamification Tenet #6: Guide Your Users with Frequent Feedback

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

Sorry for the delay in publishing this post. I've been pickpocketed while traveling Barcelona and lost my smartphone with tones of data in it. It's a horrible experience losing your phone; and in this digital age, it strangely feels worse then losing your wallet. I wish there is a way to gamify citizen crime watch to stop the theft problem in Barcelona. It's a pity because it's such a beautiful city. It would've been much more pleasant if visitors can enjoy it without constantly worrying about pickpockets, scams, robberies as well as other crimes.


Alright, on to the next tenet for success gamification. We’ve covered a lot of details so far with the first 5 tenets of a successful gamification program. Here are the first 5 for your reference:

  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
  4. Change and Adapt Faster than your Players
  5. Level Up in Baby Steps


In the previous tenant, we learned the formula for creating a level-up ladder to keep your players (or users, customer, audience, etc.) engaged over the long term. The secret is to take baby steps. Although this is the general idea, how it’s done in practice requires some finesse and subtlety. Surprisingly it’s not about making every step as easy as possible. Many practitioners still do not realize that making every step too easy may actually harm your strategy.


Using baby steps is about finding the perfect balance between too easy and too hard—that fine line of flow between certainty and uncertainty. If you are interested, here is a more detailed post about designing the precise leveling criteria. This is not a trivial task considering that it has to work for anyone and be able to adapt to everyone’s level of skills. This is also why we were awarded a patent at Lithium for our gamified community platform based on this principle.


Participation Inequality—the Power Law Distribution

power law distribution 300px.png

Using immediate feedback ensures your gamification will engage the largest audience. However, not everyone will be equally engaged. The participation level of any voluntary activities usually follows a power law distribution. That is, few of your players will quickly level up to elite status, while many others remain fairly stagnant on the ranking ladder.


No matter how fun and engaging your game is, there will always be people who don’t play and don’t want to engage at all. That is just the nature of the fact that we are unique, and every one of us is different. This gives rise to the universal power-law distribution. (If you are interested in a deeper post about why the power law is such a universal description of human behavior, then we need to devote another blog to address this question. Just let me know in the comments section below).


For example, the “elite” members of most airline or hotel loyalty programs are typically a small fraction of the brand’s customer base—these are the MVPs. However, a substantial portion of the customers are occasional travelers, and their status remains fairly stagnant, and it would take them a long time to move up to the next rung of the ladder. If it takes someone years to move to the next level of status, then it’s doubtful that he cares about the loyalty program at all. He is merely collecting the loyalty points (a.k.a. reward points) because it’s convenient and doesn’t cost anything extra, but these slowly accumulating points contribute little to his loyalty to the brand.

Building the right level-up ladder to engage at scale is not just about engaging the widest possible audience; it also means moving more players toward deeper engagement with your gamification. But how can we achieve this with players who are not even engaging with our simplest game (i.e. the first rung of the level up ladder—collecting points)?


Guide Your Players through Missions and Behavior Coupling

Gamification Tenet06a.png

There are many ways one can drive deeper engagement with the ladder you build, here are three of them:


1. Simply design more rungs to fill the ladder more densely.

This leads to more frequent feedback, and thus guides your players more closely to the path of success. This approach works well for casual players who are engaged, but will not motivate an audience with little engagement (e.g. the infrequent travelers). How can you help these infrequent travelers earn points and status faster?


2. Link your loyalty points with some other actions that these players can take frequently.

A common mechanism that has been implemented in the industry is by coupling the reward points with dollars spent on one’s credit card. That means your players can now earn rewards points simply by using their credit card, and this can happen much more frequently than taking a flight or staying at a hotel.


Consequently, players earn points faster. If your players can see how quickly they are accumulating points towards a flight or a hotel stay, they will be more inclined to contribute to it. As the players invest more towards the reward, they’ll be much more likely to make use of it when they’ve earned that level of reward. And the more frequently the players can make use of the reward, the more they will realize the ongoing benefits and continue to contribute. This creates a positive feedback that drives much stronger loyalty.


Clearly, this requires hotels and airlines to partner with credit cards. But it doesn’t have to start big. The frequent actions that are linked to the loyalty points can be literally anything, as long as you can measure it accurately. Furthermore, there can be more than one frequent action (e.g. retweet us, watch a video from us, share your story with us on social media, etc.) This will provide the players with different ways to earn reward points and many ways to win, so that everyone can play and play often.


3. Use missions to target a specific group of users who are stalling at a specific stage of the level-up ladder.

Through the 2nd tenet, we should have an abundance of behavior data to help us understand why certain groups of users are not moving up the ladder fast enough. With this understanding, we can either change the leveling criterion or we can make use of missions. We basically design specific missions to change the behaviors that are preventing the target group from moving up the ladder.


For example, one of the requirements to gain platinum status with an innovative loyalty program (with an airline, a hotel, or any loyalty programs) may be to share your experience on social media. However, the behavior data could show that many people are not getting the platinum status because they are relatively inactive on social media. Then you can create a mission(s) for the target group (i.e. those who are just short of platinum status) that awards an attractive amount of rewards points to those who shared their experience on social media under some time constraint (e.g. share a video of our hotel in the next 3 month to get 1000 points).


It’s not unusual to deploy several missions to help a target group meet the requirements of the next level status. This effectively guides the target group up the next rung of the ladder, so they learn what’s required to achieve the next status while completing the mission. 


Stay tuned. Up next: Knowing your players.

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

Sorry to hear you got pickpocketed, @MikeW. If anyone can come up with a way to gamify citizen crime watch, it's you! 

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

Hello @JaniceK,


Sorry for the late reply. I'm actually on a cruise somewhere in the South Caribbeans now. 


Thank you for the vote of confidence. One day when I get the resources, I'll definitely do something about it. It's a terrible experience that impacts many people, giving them very negative experiences.


I hope I can contribute to the society by doing something about it to stop these theft and pickpockets.


Honored Contributor Honored Contributor
Honored Contributor

I was re-reading this article again today. I would love to hear more of your thoughts on the power law distribution. I hope to see a blog post from this on you soon! Cat Happy


Me too!

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

Hello @lilim and @Jochen


Apologize for the late reply. Somehow my blog reply notification emails are all routed to my outlook's clutter folder, so I missed a lot of blog replies and I am just slowly getting to these now.


The Power-Law distribution is a fairly universal distribution of that characterizes many natural phenomena. It has relevance to basic science (e.g. physics, chemistry, astronomy, biology, etc.) economics (e.g. income distribution, wealth distribution, GDPs, etc) and distribution of rare events (like earthquakes, etc.), all the way to voluntary participatory behaviors (like social media and gaming motivation). 


The fundamental reason that power-law arise is because people are different and participate at different rates. For example I may like to play game for 1 hour/day, but you like to play just slightly longer say 1.5 hours/day.  But this difference is accumulated over time to some huge difference. That is if we only play game for a single day, then you would just have 30min (0.5 hours) more play time than me. But what happens if we play games for a year. You would be 182.5 hours ahead of me. The small difference in participation rate due to our individual difference become magnified and accentuated over time. That is the mechanism why the power-law arise.


It is natural, because there is no way to force everyone to behave the same way, we are not robots. And we can't stop time, or slow it down or fast forward it. These are just natural ways that things happen. That is why this power-law distribution not only describe people's level of motivation very well in playing a game. It is also precisely the reason that give rise to the 90:9:1 rule in community participation. I've also written about this subject in a few earlier blog posts.


I hope this gives you a deeper understanding of the power-law distribution.

Let me know if you have any questions that you like to discuss further.



Thank you @MikeW for the elaborate response, I'll definitely check those articles as well. I have a lot of very interesting reading ahead of me, thanks to your blog posts and all the links to external articles in them. Loving it 🙂

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

You're welcome @Jochen,


Glad you like my blog. Thank you for the support and being an avid reader who's not afraid to raise questions.


Loving this too.  😉