Skip to main content

Why is Gamification relevant?

In the last post I talked about Gamification and different concepts behind Gamification.   In this post I intend to cover why Gamification has become important.

Let us accept it.  Today we live in a world which is increasingly becoming online.  More and more businesses  are moving online and one of the prime focus for these businesses is to sustain and improve the engagement levels of its users.   Gamification acts as key driver in increasing the engagement level.

Before we delve into how Gamification impacts engagement; let us try to understand what "Engagement" means.  The dictionary definition of Engagement which would applicable to this scenario will be "emotional involvement or commitment". Given this definition - the first aspect to analyze is what drives this involvement and commitment.  The generally accepted hypothesis is that it is "Motivation" that drives commitment which implies that Motivation is the key contributing factor to increase or retain engagement levels.

The image below encapsulates the classic definition and classification of motivational attributes. 








The next aspect we need to look at is how an User can be engaged.    Traditionally  Engagement can be grouped under four broad categories
  • Expressive Engagement - Where in the User expresses his/her opinion,  contributes creatively and personalizes his experiences with the product, application or the system.
  • Exploratory Engagement - Where in the User is motivated to search, explore and find creative ways of using the product, application or the system.
  • Collaborative Engagement - Where in the User is willing to share his experiences, team up with other users of the system and solve problems collectively
  • Competitive Engagement - Where the User actively competes with the other Users to score points, gain recognition or improve his standing among a peer group.
Gamification concepts when used correctly and in proper context can be used to drive the above mentioned Engagement models.  For example;  Avatars and other personalization features can drive expressive engagement;  Challenges and Quests can drive exploratory engagement and levels, badges can drive competitive engagement.

Before we close on this topic, I want to touch upon another important aspect on this subject. Nothing is concrete unless we have an ability to measure the impact.  The same applies to Gamification and its impact on Engagement level. This brings us to an issue of how to measure Engagement.  Engagement can be measured across the following dimensions
  • Recency - How recently an user has actively used the product, application or system
  • Frequency - How frequently does an user uses the product, application or system
  • Duration - How long does the user actively stays and uses the product, application or system
  • Virality - How often does the user talk about, shares or amplifies the information about the product, application or system.
  • Ratings -  What are the ratings provided by the various users of the system,

Comments

Popular posts from this blog

Dilbert on Agile Programing

Dilbert on Agile and Extreme Programming -  Picked up from dilbert.com - Scott Adams.

Big Data: Why Traditional Data warehouses fail?

Over the years, have been involved with few of the data warehousing efforts.   As a concept, I believe that having a functional and active data  ware house is essential for an organization. Data warehouses facilitate easy analysis and help analysts in gathering insights about the business.   But my practical experiences suggest that the reality is far from the expectations. Many of the data warehousing initiatives end up as a high  cost, long gestation projects with questionable end results.   I have spoken to few of my associates who are involved in the area and it appears that  quite a few of them share my view. When I query the users and intended users of the data warehouses, I hear issues like: The system is inflexible and is not able to quickly adapt to changing business needs.  By the time, the changes get implemented on the system, the analytical need for which the changes were introduced is no longer relevant. The implementors of the datawarehouse are always look

Overview of Hadoop Ecosystem

Of late, have been looking into the Big Data space and Hadoop in particular.  When I started looking into it, found that there are so many products and tools related to Haddop.   Using this post summarize my discovery about Hadoop Ecosystem. Hadoop Ecosystem A small overview on each is listed below: Data Collection  - Primary objective of these is to move data into a Hadoop cluster Flume : - Apache Flume is a distributed, reliable, and available system for efficiently collecting, aggregating and moving large amounts of log data from many different sources to a centralized data store. Developed by cloudera and currently being incubated at Apache software foundaton. The details about the same can be found here . Scribe : Scribe is a server for aggregating streaming log data. It is designed to scale to a very large number of nodes and be robust to network and node failures. Dveloped by Facebook and can be found here .  Chuckwa : Chukwa is a Hadoop subproject dev