Updating the user interaction model

by nihaar

After some insightful feedback from Khalid Harun, I wanted to revise the user interaction model in my last post. As Khalid rightfully pointed out, the model stated below can be broken down further into two independent models, a user attraction and the user retention model.

User Attraction model

User Attraction model

This is the FSM modeling a user when she first comes into contact with your product. Transition to any state is dependent on the perceived value of the product. Let’s examine each state a little closer:

  • Web Surfer: This is self-explanatory. The user can remain a web-surfer oblivious or indifferent to your product or become a “contacted user”. That probability is a function of your marketing, brand-awareness, product virality and other variables.
  • Contacted User: A user when she has first come in contact with your product. From here, the user can either return back to being a web-user or transition to an “interested user”. A user in this state is forming her perception of the value provided by your product and how useful/relevant she thinks it might be to her.
  • Interested User: Once a user perceives there is value in the product and she could seek out reviews, ask friends about their experience, read blogs etc. If she is still interested, she will transition to a converted user. Alternatively, the user could also lose interest in the product and transition back to a web-surfer. The probability of transitioning to a converted user is dependent on product reputation, buzz as well as the complexity of a user becoming a converted user.
  • Converted User: After a user has converted it is impossible for him to become just a web surfer who needs to be contacted again. Therefore, he has no place in this model anymore and must graduate to the Retention Model.

User Retention model

This is slightly more complex and dynamic than the User attraction model. Transitions here are dependent on the actual value that the product delivers to the user. A user’s current state is not as easy to measure as previously (in the User Attraction model) and transitions may occur frequently. In my previous post we assumed there were two states once a user has converted (including the converted state), but these can be further broken down into four states:

User Retention model

  • New User: A newly converted user will start by experimenting with the product, learning how to use it and apply it in her day-to-day life. This is when the user will gauge the utility (actual value) of the product. From here the user can transition to either become a casual user, a power user, or a dormant user. The probabilities are dependent on the utility of the product to the user as well as its addictiveness.
  • Casual User: A user in this state understands the utility of the product and is a repetitive user. She has realized its value in her day-to-day activities. At any given time she can transition to being a power user (if she notices a sudden boost in utility derived from the product via a change in her lifestyle or change in) or a dormant user (if the utility derived from the product starts to decay). The probability of staying in this state is highly dependent on the addictiveness of the product.
  • Power User: According to wikipedia, the definition of a power user is “[…] a user of a personal computer who can use advanced features of programs which are outside the expertise of “normal” users…” This is a frequently returning user who also knows the maximum utility of the product and has a dire need for it. They are usually your evangelists who will help spread the word about your product to their peers. From this state, a user can transition to a casual user or a dormant user
  • Dormant User: If the benefits derived from the product start to decay (either a change in the product, market landscape or user’s habits), a user will transition into a dormant state, where she rarely uses the product. Barring any changes, this user will eventually transition into a quitter as the utility of the product goes to zero. With a small probability the user can transition back to a casual user. The probability of this is a function of the user’s tolerance and loyalty to the product and the change in the utility of the product.
  • Quitter: Once the utility of the product reaches zero, a user quits using the product. Upon reaching this state, the probability of the user returning is zero. The goal of any entrepreneur/product developer is to minimize the probability of a user reaching this state.

Next up, I’ll elaborate on the interestingness and addictiveness qualities of a product.